Depending on the type of generative AI model you’re working with, you can generate images, translate text into image outputs, synthesize speech and audio, create original video content, and generate synthetic data.

While many AI companies and tools are popping up daily, the generative AI models that work in the background to run these tools are fewer and more important to the growth of generative AI’s capabilities. Todays’ generative AI models are the “unsung” heroes of AI.

Read on to learn more about generative AI models, how they work and compare to other types of AI, and some of the top generative AI models available today.

How Do Generative AI Models Work?

Generative AI models are the massive, big-data-driven models that power the emerging artificial intelligence technology that can create content.

Using unsupervised or semi-supervised learning methods, generative AI models are trained to recognize small-scale and overarching patterns and relationships in training datasets that come from all kinds of sources — the internet, wikis, books, image libraries, and more.

This training enables a generative AI model to mimic those patterns when generating new content, making it believable that the content could have been created by or belonged to a human rather than a machine.

Generative AI models are able to so closely replicate actual human content because they are designed with layers of neural networks that emulate the synapses between neurons in a human brain. When the neural network design is combined with large training datasets, complex deep learning and training algorithms, and frequent re-training and updates, these models are able to improve and “learn” over time and at scale.

Among the many types of generative AI models, there are text-to-text generators, text-to-image generators, image-to-image generators, and even image-to-text generators. In this example, I used a text-to-image generator, Img2Go. I provided an AI prompt – a text description – and the model generated a new image that matched my prompt.

The prompt I used was: “A laughing robot in the sunset.”

For more information about how generative AI is used in business, see our guide: Generative AI Examples

How Are Generative AI Models Trained?

Generative AI models are all trained a little differently, depending on the model type you’re training. Let’s look at how transformer-based models, GANs, and diffusion models are trained:

Transformer-Based Model Training

Transformer-based models are designed with massive neural networks and transformer infrastructure that make it possible for the model to recognize and remember relationships and patterns in sequential data.

To start, these models are trained to look through, store, and “remember” large datasets from a variety of sources and, sometimes, in a variety of formats. Training data sources could be websites and online texts, news articles, wikis, books, image and video collections, and other large bodies of data that provide valuable information.

From there, transformer models can contextualize all of this data and effectively focus on the most important parts of the training dataset through that learned context. The sequences this type of model recognizes from its training will inform how it responds to user prompts and questions.

Essentially, transformer-based models pick the next most logical piece of data to generate in a sequence of data. Encoders and/or decoders are built into the platform to decode the tokens or blocks of content that have been segmented based on user inputs.

GAN Model Training

GAN (generative adversarial network) models are trained with two different sub-model neural networks: a generator and a discriminator. The generator generates content based on user inputs and training data, while the discriminator model evaluates generated content against “real” examples to determine which output is real or accurate.

First, the generator creates new “fake” data based on a randomized noise signal. Then, the discriminator blindly compares that fake data to real data from the model’s training data to determine which data is “real” or the original data.

The two sub-models cycle through this process repeatedly until the discriminator is no longer able to find flaws or differences in the newly generated data compared to the training data.

Diffusion Model Training

Diffusion models require both forward training and reverse training, or forward diffusion and reverse diffusion.

The forward diffusion process involves adding randomized noise to training data. The model is trained to generate outputs using the noisy data (not as refined or specific) as input. The noise introduces variations and perturbations in the data, making the model robust and helping it to learn different possible outputs for a given input.

When the reverse diffusion process begins, noise is slowly removed or reversed from the dataset to generate content that matches the original’s qualities. This process encourages the model to focus on the underlying structure and patterns in the data, rather than relying on the noise to produce the desired outputs. By gradually removing the noise, the model learns to produce outputs that closely match the desired qualities of the original input data.

Noise, in this case, is best defined as signals that cause behaviors you don’t want to keep in your final dataset but that help you to gradually distinguish between correct and incorrect data inputs and outputs.

For a related AI chatbot comparison, see: ChatGPT vs. GitHub Copilot

Types of Generative AI Models

Many types of generative AI models are in operation today, and the number continues to grow as AI experts experiment with existing models.

With the classifications below, keep in mind that it’s possible for a model to fit into multiple categories. For example, the latest updates to ChatGPT and GPT-4 make it a transformer-based model, a large language model, and a multimodal model.

• Generative adversarial networks (GANs): Best for image duplication and synthetic data generation.
• Transformer-based models: Best for text generation and content/code completion. Common subsets of transformer-based models include generative pre-trained transformer (GPT) and bidirectional encoder representations from transformers (BERT) models.
• Diffusion models: Best for image generation and video/image synthesis.
• Variational autoencoders (VAEs): Best for image, audio, and video content creation, especially when synthetic data needs to be photorealistic; designed with an encoder-decoder infrastructure.
• Unimodal models: Models that are set up to accept only one data input format; most generative AI models today are unimodal models.
• Multimodal models: Designed to accept multiple types of inputs and prompts when generating outputs; for example, GPT-4 can accept both text and images as inputs.
• Large language models: The most popular and well-known type of generative AI model right now, large language models (LLMs) are designed to generate and complete written content at scale.
• Neural radiance fields (NeRFs): Emerging neural network technology that can be used to generate 3D imagery based on 2D image inputs.

Generative AI vs. Discriminative AI Models

The primary difference between generative and discriminative AI models is that generative AI models can create new content and outputs based on their training.

Discriminative modeling, on the other hand, is primarily used to classify existing data through supervised learning. As an example, a protein classification tool would operate on a discriminative model, while a protein generator would run on a generative AI model.

Generative vs. Predictive AI Models

Generative models are designed to create something new while predictive AI models are set up to make predictions based on data that already exists.

Continuing with our example above, a tool that predicts the next segment of amino acids in a protein molecule would work through a predictive AI model while a protein generator requires a generative AI model approach.

What are the Challenges of Generative AI Models?

Even though generative AI has been trending since November 2022, one of the major reasons you see only a limited number of startups developing AI models is that it requires deep pockets and vast resources and is very complex. We highlighted some key challenges of generative AI models below.

Mode Collapse in GANs

GANs may suffer from mode collapse, which is when the generator learns to fool the discriminator by producing a limited set of outputs, ignoring the diversity present in the training data. This can result in repetitive or less varied generated content.

Training Complexity 

As stated above, generative models often require large amounts of data and computational resources for training. The resource-intensive nature of training limits accessibility for smaller research labs and individual researchers. It also requires domain-specific knowledge, as a lack of domain-specific expertise can result in the AI model giving suboptimal outputs, or even hallucinating.

Adversarial Attacks

Generative models, especially GANs, are susceptible to adversarial attacks where small perturbations to input data can lead to unexpected or malicious outputs. Learning to effectively combat adversarial attacks is an active area of research.

Fine-tuning and transfer learning

Adapting pre-trained generative models to specific tasks or domains may be challenging. The ability to fine-tune without causing catastrophic forgetting or degradation in performance is an another ongoing research concern, and requires more work and investment.

To learn about the companies actively developing generative AI, see our guide: Generative AI Companies: Top 12 Leaders

What are the Benefits of Generative AI Models?

The benefits of generative AI models are numerous and very important to AI’s growth, particularly in the area of data augmentation and natural language processing.

Data Augmentation

Generative models can be used to augment datasets by generating synthetic data. This is helpful in scenarios where sufficient real-world labeled data is not available, making it useful for training other machine learning models.

Natural Language Understanding and Generation

Generative AI models can be used to create AI chatbots and virtual AI assistants capable of understanding and generating human-like responses in natural language. It can generate human-like text for content creation, including articles, stories, and more.

Creative Applications

Generative AI models can be used to create art, poetry, music and other artistic works. For example, OpenAI’s Jukebox, a generative model, can compose music in different genres. Generative AI models can also be leveraged for content synthesis, as it is capable of producing diverse and creative content, and assisting in brainstorming and ideation processes.

Versatility

AI models can be fine-tuned for various tasks, such as translation, summarization, and question answering. They can also be adapted to different domains and industries with proper training and fine-tuning.

For example, depending on the tuning, the output very serious and proper, or casual and recreational. The mode and mood of the output can be tuned to a remarkably specific degree.

Examples of Generative AI Models

Below you’ll find some of the most popular generative AI models available today. Keep in mind that many generative AI vendors build their popular tools with one of these models as the foundation or base model. For example, many of Microsoft’s new Copilot tools run on GPT-4 from OpenAI.

• GPT-3/3.5/4, etc.: GPT-3, GPT-3.5, and GPT-4 are different generations of the GPT foundation model managed, owned, and created by OpenAI. The latest version, GPT4, uses a multimodal LLM that is the basis for ChatGPT.
• OpenAI Codex: Another model from OpenAI, Codex is able to generate code and autocomplete code in response to natural language prompts. It is the foundation model for tools like GitHub Copilot.
• Stable Diffusion: One of the most popular diffusion models, Stability AI’s Stable Diffusion is primarily used for text-to-image generation.
• LaMDA: A transformer-based model from Google, LaMDA is designed to support conversational use cases.
• PaLM: Another transformer-based LLM from Google, PaLM is designed to support multilingual content generation and coding. PaLM 2 is the latest version of the model and is the foundation for Google Bard.
• AlphaCode: A developer and coding support tool from DeepMind, AlphaCode is a large language model that generates code based on natural language inputs and questions.
• BLOOM: Hugging Face’s BLOOM is an autoregressive, multilingual LLM that mostly focuses on completing statements with missing text or strings of code with missing code.
• LLaMA: LLaMA is a smaller large language model option from Meta, with a goal of making generative AI models more accessible to users with fewer infrastructural resources.
• Midjourney: Midjourney is a generative AI model that operates similarly to Stable Diffusion, generating imagery from natural language prompts that users submit.

Keep learning about AI: Generative AI Landscape: Current and Future Trends

What Can Generative AI Models Do?

Generative AI models support various use cases, allowing you to complete a variety of business and personal tasks when trained appropriately and given relevant prompts. You can use generative AI models to handle the following tasks and many more:

Bottom Line: Generative AI Models

Generative AI models are highly scalable, accessible artificial intelligence solutions that are rightfully getting publicity as they supplement and transform various business operations.

However, there are many concerns about how these tools work, their lack of transparency and built-in security safeguards, and generative AI ethics in general. Whether your organization is working to develop a generative AI model, build off of a foundational model, or simply use ChatGPT for daily tasks, keep in mind that the best way to use generative AI models is with comprehensive employee and customer training and clear ethical use policies in place.

For a deeper understanding of the AI chatbot sector, see our guide: Best AI Chatbots 2024

The post Generative AI Models: A Complete Guide appeared first on eWEEK.

Claude is created by Anthropic and is a newer application in the AI field. It’s used mainly as an AI chatbot, and doesn’t have the full functionality of GPT-4. Claude is supported by Google, Zoom and Slack, and has received significant investment over the last several months.

So which generative AI app is best, GPT-4 or Claude 2? In this comparison of ChatGPT and Claude, we analyze both application’s key features, pricing, and pros and cons to help you determine the best AI solution for your needs.

GPT-4 vs. Claude: Head-to-Head Comparison

Here is a head-to-head feature comparison of GPT-4 and Claude.

What is GPT-4?

ChatGPT is an abbreviation for Generative Pre-trained Transformer, a form of advanced artificial intelligence (AI). GPT4 simulates thought by using a neural network machine learning model trained on a vast trove of data gathered from the internet.

GPT-4 goes far beyond being a chatbot. This generative AI app creates documents and articles and solves problems. GPT-4 can also do image interpretation using multimodal language AI models. This enables it to build websites based on sketches and suggest recipes based on a photo of what is in the fridge or sitting on a countertop.

Below is an example that demonstrates that GPT-4 provides more detailed responses than its earlier version:

For more information, also see: ChatGPT: Understanding the ChatGPT ChatBot

What is Claude 2?

Claude 2 is an AI assistant from Anthropic that is accessible through a chat interface or API. It is capable of conversational and text processing. Use cases include summarization, search, creative and collaborative writing, formulating Q&A and some basic coding.

It gives fast responses to customer service requests and can hand off tasks to a human when needed. Claude is particularly good at editing, rewriting, summarizing, classifying and extracting structured data. It can also follow basic instructions and logical scenarios, analyze strategic risks and opportunities based on annual reports, assess the pros and cons of a piece of legislation and identify risks in legal documents.

Claude can provide lengthy answers to questions requiring fact or opinion. Below is Claude’s answer to “what is the best weather?”

GPT-4 vs. Claude 2: Feature Comparison

GPT4 and Claude are at the center of the generative AI battle royale in the technology sector. Let us compare their key features to help determine the best option for you.

GPT-4 vs. Claude: Chatbot Functions

GPT-4 is used a lot in chatbot applications to automate customer service, answer FAQs, and engage in conversation. It can respond conversationally by tapping into a comprehensive set of online text, as well as news items, novels, websites, and more.

Overall, GPT4 does a good job of analyzing information, evaluating online behavior, and even makes product recommendations as part of the online sales and upselling process. Automation features extend to appointment scheduling, reservations, payment processing, queries about shipping schedules, order progress, product returns, product and service availability, all with a good level of accuracy.

Claude can be viewed as more of a focused AI chatbot than GPT-4. It can be tailored to certain use cases and data sets such as customer service, legal, back office and sales. It can also be taught when to hand off tasks to a human.

You define the data set to analyze, summarize or use for context, and it can respond conversationally. It can speak a variety of common languages, as well as programming languages. However, it doesn’t search the internet like GPT-4. You can provide Claude with text from the internet and ask it to perform tasks with that content.

Verdict: GPT-4 wins overall – but Claude may prove better at narrower AI chatbot use cases.

GPT-4 vs. Claude: Accuracy of Response

ChatGPT can be prone to be error-based, because some of its data may not be current. But most of the time it is accurate. GPT-4 added a greater degree of accuracy. OpenAI stated that GPT-4 is 82% less likely than its predecessor to respond to requests for content that OpenAI does not allow, and 60% less likely to invent answers. But don’t expect it to be perfect. That includes coding – its programming output should always be verified by human eyes.

Claude is also prone to errors. Some believe Claude is better at answering queries as it takes answers from a narrower data set. This is beneficial in areas such as history, geography and entertainment. A big difference between Claude and GPT-4 is that Claude can admit that it doesn’t know.

Verdict: This category is even. GPT4 is more accurate than Claude in many areas, yet Claude’s accuracy is better in some use cases.

On a related topic: What is Generative AI?

GPT-4 vs. Claude: Integration

GPT can be plugged into other applications to generate responses via an API. Plugins are becoming available, including those for the likes of Kayak, Expedia, OpenTable, Slack and Shopify, with more on the way. It is also integrated with a lot of different programming languages.

Claude has done an excellent job of developing partners, too. They include Notion, Quora, DuckDuckGo, Slack and Zoom. Watch out for tighter Google integration going forward, too. Claude can integrate with a wide range of apps via API.

The Claude App for Slack can summarize threads and answer questions. For Zoom, Claude is being integrated into the Zoom contact center, meetings, phone, team chat, whiteboard, and Zoom IQ.

Verdict: Both integrate well, but Claude perhaps comes out slightly ahead.

For more information about the overall AI software sector: Top AI Software

GPT-4 vs. Claude: Security

Unfortunately, there’s not a lot to say about the security of these two AI platforms, because they are so new, and security has not been a driving focus as they’ve been built. Expect this to change going forward, but in any case, it’s never a good idea to create AI prompts from sensitive business information.

Chat-GPT does claim that it has worked with over 50 experts to develop improved security.  Claude, to its credit, uses industry-standard best practices for data handling and retention. But, again, neither AI platform is intended for private business information.

Verdict: Neither is particularly well known for security, but Claude gets the nod.

For more comparisons of generative AI applications: ChatGPT vs. Google Bard

GPT-4 vs. Claude: Pricing

GPT-4 pricing

GPT-4 has a basic version available for free but the main ChatGPT Plus version costs roughly $20/month. Subscribers gain access to ChatGPT at peak times, faster responses, and priority access to new features and improvements.

On top of the basic subscription, there is a pricing scale per 1,000 tokens (chunks of words). 1,000 tokens comes out to about 750 words of material. The higher rate provides access to a larger set of contextual data.

Claude Pricing

Claude 2 has a subscription and a pricing scale options. The subscription plan, Claude Pro, costs $20 per month plus tax. There are three scale versions of Claude. Claude Instant is a lighter, less expensive and much faster option. Claude 2 is the high-performance version that can take care of sophisticated dialogue and creative content generation as well as detailed instruction following. Claude 2.1 offers the same performance as Claude 2 with reduction in hallucination rates.

For context, 100,000 tokens works out to roughly 70,000 words or six hours of audio.

Verdict: Due to the added monthly subscription in GPT-4, it is hard to be certain who wins in the long term. But it looks like Claude 2 wins on pricing.

Pros and Cons of GPT-4

ChatGPT has a higher profile than Claude – more total users – yet it is also prone to hallucinations, and is a little slower.

Pros and Cons of Claude 2

Claude is known to be a fast AI chatbot, but its list of languages is far smaller.

GPT-4 vs. Claude 2: Which is the Best?

The decision of whether to choose GPT-4 or Claude 2 depends on your needs, priorities and budget. To break it down, Claude 2’s standout feature is its ethical framework, while GPT-4 excels as a generalist.

GPT4 can perform complex tasks. It has achieved some success with basic computer programming duties. It ventures well beyond that into territory such as drawing up simple lawsuits, creating elementary computer games, passing exams, checking for plagiarism, generating written content, summarizing documentation, highlighting key passages within the text, and translating languages.

On the other hand, Claude 2 shines in key areas like legal applications, math and science, and safety. Its constitutional AI enables it to understand and apply ethical principles and guidelines when providing output. This makes Claude 2 a suitable choice for professionals in fields that require adherence to ethical standards, such as legal practitioners or researchers in sensitive scientific areas.

For comprehensive conversational applications, GPT-4 still leads in general performance whereas Claude 2’s strengths make it a worthy challenger that can go toe-to-toe with GPT4 in various disciplines.

For a fuller understanding of the generative AI market: Top Generative AI Apps and Tools

Bottom Line: GPT-4 vs. Claude 2

GPT-4 uses a transformer-based architecture as part of a neural network that handles sequential data. It appears to perform capably in coding, and does a very good job on chat, language translation, answering questions, understanding images, and can even determine why a joke is funny. GPT-4 has thrown its hat in the ring with Microsoft – which offers many benefits in terms of development and support.

Claude, on the other hand, favors Google. It is less comprehensive than GPT-4 but can respond without searching the internet. It does a good job of digesting, summarizing and explaining financial documents and research papers. Like all AI chatbots, it may sometimes assess its own ability or memory incorrectly, make up information, and make errors in complicated arithmetic. But certainly GPT-4 makes errors, too.

Claude is very much a work in progress, it’s not as comprehensive as GPT-4 right now. Give it a few months and we’ll see how far it comes. But for now, GPT-4 has greater functionality.

For more about new companies that are influencing the future of AI: Generative AI Startups

The post ChatGPT-4 vs. Claude: 2024 Chatbot Comparison appeared first on eWEEK.

This task is far from easy, due to the enormous range of output created by the advanced algorithms included in generative AI programs. Additionally, the vast data repositories in large language models – data stores that are growing daily – enables generative AI programs to offer an enormous range of outputs.

Consequently, effective prompt engineering requires an overall understanding of prompt engineering, knowing the key tips for a well-crafted prompt, and being aware of key use cases for an effective AI prompt.

Understanding Prompt Engineering

Generative artificial intelligence has become ubiquitous, with a wide array of generative apps and tools for both professional and recreational use. This is largely due to the success and popularity garnered by ChatGPT, Google Bard or any AI chatbot that leverages a large language model.

Users have realized that getting the best answer from a generative AI app can be challenging. One common misunderstanding: users enter casually-worded prompts as if the generative AI program were a fast Google search. This won’t produce optimal results.

Adding to the challenge, today’s generative AI programs span all types of multimedia:

• Image generators, like Open AI Dall-E and Midjourney ,which are ideal for generating 3D assets and AI art.
• Code generators, like Copilot, which are used for generating code snippets and assisting developers in coding tasks.
• Speech synthesis models, like DeepMind’s WaveNet, are used to generate realistic human-like speech.

In sum, there’s growing realization about using generative AI tools: your output is only as good as your prompt. And your prompt must be constructed to include elements based on not just your core concept, but also what type of media (photo, video) you are using to build your content.

A generative AI program is powerful, but it cannot guess your intent – you need to tell it exactly what you want.

How to Engineer a Well-Crafted Prompt: 7 Tips

A well-engineered prompt encompasses skills and techniques that enable you to understand the capabilities and limitations of a model, and then tailor your prompt to optimize the quality and relevance of the generated output.

A carefully crafted prompt should include several core elements, including:

1) Provide Context

This is the big one. Using proper context in your prompt means including all relevant background information, from crucial details and any necessary instructions. Are you creating a prompt in the context of healthcare, or finance, or software coding? Include that context. Similarly, is your prompt designed to output historic material or a forward-looking response? Include all important time-sensitive context in your prompt’s verbiage.

For example, you may want to generate information about the scientific process of photosynthesis. If you’re used to Google, you might simply type the prompt “photosynthesis.”

With a vague, one-word prompt, you would still get some results:

However, for a fuller, more detailed sense of the biological underpinnings of photosynthesis, look at what results from a prompt with fuller and deeper context:

2) Be Specific 

Clearly define the task or question you want the AI model to address. Be highly specific about what information or output you are expecting: add more detail than you think you might need. For instance, specify if you are seeking data or any calculations in your output, and include the full array of project-related data that will enable the LLM to find the one needle in a haystack you’re searching for.

3) Add All Constraints

If there are any limitations or constraints that the AI model needs to consider, such as word count, time frame or specific criteria, make them explicit in the prompt. Realize that all generative AI software have access to an ocean of data; without very tight constraints built into your prompt, you’re asking for more output than you actually want.

4) Use System-Related Instructions

Many generative AI models have a “system” – often thought of as a “user persona” – that specific prompt instructions can influence. Use these instructions to guide the model’s behavior or style of output.

For instance, if you’re really looking for a “dad” joke, then go ahead and spell that out clearly in your prompt: “tell me a joke in the style of a dad joke.” After using this system-related instruction, you can easily produce dozens of dad jokes.

5) Experiment with Temperature and Top-K and Top-P

Adjusting parameters such as temperature, top-k, and/or top-p can control the randomness or creativity of the model’s output. As you craft your prompt, experiment with these parameters to fine-tune the generated output based on your preferences.

Temperature Value

​The temperature value refers to the randomness or creativity of the generated responses. A higher temperature value, such as 0.8 or 1.0, makes the output more random and unpredictable, while a lower temperature value, such as 0.2 or 0.5, makes the output more focused and deterministic. Most likely, you’ll want to create a more formal response for a business project and a more random approach for a recreational project.

Temperature values and what they mean:

Top K Value

The top k value is the parameter that determines the number of next tokens most likely to be considered during text generation. Put simply, a higher top k value allows for a more diverse and creative output as more alternative tokens are considered. Conversely, a lower top k value results in more conservative and predictable responses.

Top K values and what they mean:

Top P Value

Top p value is an alternative method to control the diversity of generated responses during text generation.

Instead of considering a fixed number of most likely tokens like top k, top p sampling involves considering the tokens until their cumulative probability reaches a certain threshold or percentage. This threshold is dynamic and can vary with each token generation step.

For example, if the top-p value is set to 0.8, the model will consider tokens until the cumulative probability of those tokens reaches 80%.

Top P values and what they mean:

6) Test and Iterate Your Prompt

You will likely try various prompts to more efficiently create the output you desire. This is not only a productive approach, it’s one of the most effective possible strategies for improving your prompt engineering.

So don’t hesitate to experiment – again and again – with different prompts, and then evaluate the generated output  to refine and improve your prompt engineering. As prompt experts have learned, you can’t become a top-level prompt engineer without this extensive iteration.

Important point: even if you think you’re getting the output you need, don’t hesitate to dig deeper and try again. There’s no downside to continued attempts.

7) Understand Model Limitations

This is a hard fact for many prompt engineers to accept: a given generative AI model may include an excellent large language model, but that model cannot answer every question. For instance, a large language model that was built to serve the healthcare market may not be able to handle the most upper level finance-related queries that an MBA can type into it.

So it’s essential to engineer the best prompts within the limitations and capabilities of the specific AI model you are using. This will help you design prompts that work well with the model’s strengths and mitigate potential pitfalls of limited outputs.

Use Cases for Prompt Engineering

If you’re wondering about the possible use cases for prompt engineering, realize that the number is far from fixed – the number of potential use cases grows constantly.

As noted below, they currently range from creating blog posts to full-length content summarization. As the generative AI tools grow – and as the field of prompt engineering advances – the number of use cases expands across finance, manufacturing, healthcare and many more fields.

A sampling of current use cases for prompt engineering:

5 Top Prompt Engineering Tools and Software

• Azure Prompt Flow: Powered by LLMs, the Azure Prompt Flow is currently one of the most sophisticated and feature-rich prompt engineering tools. It enables you to create executable flows that connect LLMs, prompts and Python tools through a visualized graph.
• Agenta: An open-source tool designed for building LLM applications. It offers resources for experimentation, prompt engineering, evaluation and monitoring, allowing you to develop and deploy LLM apps.
• Helicone.ai: This is a Y Combinator-backed open-source platform for AI observability. It provides monitoring, logging and tracing for your LLM applications, which can help write prompts.
• LLMStudio: Developed by TensorOps, LLMStudio is an open-source tool designed to streamline your interactions with advanced language models such as OpenAI, VertexAI, Bedrock and even Google’s PaLM 2.
• LangChain: This is a framework for developing applications powered by language models. It includes several modules such as LangChain libraries, LangChain templates, LangServe and LangSmith, which is a platform designed to simplify debugging, testing, evaluating and monitoring large language model applications.

Bottom Line: Effective Prompt Engineering

Prompt engineering is an art and science that requires skills, reasoning and creativity. It is a dynamic skill that merges the precision of science with the artistry of advanced language. When mastered and used effectively, it becomes a powerful tool for harnessing the capabilities of generative AI software.

Of course prompt engineering as a field is brand new – the term hardly existed even as recently as the end of 2022. So be aware that the strategies and best practices for prompt engineering will change rapidly in the months and years ahead. Also realize that prompt engineering is a valuable skill in the AI market; if you’re a top prompt engineering, there will likely be an open job for you.

To gain a fuller understanding of generative AI, read our guide: What is Generative AI? 

The post The Ultimate Guide to Prompt Engineering appeared first on eWEEK.

Clearly the need for AI in security solutions is urgent: Cybercriminals are constantly evolving their techniques to breach security systems and compromise sensitive data. Companies that depend on only traditional cybersecurity solutions may not be able to stop these attacks – support from AI is more important than ever.

We reviewed 10 top-rated AI security solutions along with their features, pricing, and pros and cons. Plus down below we list an additional 10 honorable mentions to help you determine the best AI security tool for your business.

Top AI Security Software: Comparison Chart

Here is a head-to-head feature summary comparison of the top-rated AI security software.

Darktrace: Best for Handling Novel Threats

Darktrace’s cyber AI platform uses AI and ML algorithms to identify and respond to cyberthreats in real time. The platform offers a unified solution that provides protection across the cloud, SaaS, email, IoT, ICS, remote endpoints, and the network.

Darktrace’s self-learning AI technology is designed to understand and adapt to the unique patterns of a company’s network by learning from users and devices as well as the connections between them, allowing it to detect anomalous, novel behavior that may indicate a cyberattack.

The platform offers various AI-supported services, such as AI-based attack simulation and AI incident investigation and reporting. Darktrace’s AI algorithms constantly learn and adapt to the evolving threat landscape, enabling it to identify known and unknown threats and detect abnormal activity that may indicate the presence of previously unseen threats.

To that end, Darktrace is geared to combat LOTL (living off the land) attacks, highly targeted attacks and – increasingly important – AI attacks.

Pros and Cons

Pricing

Darktrace doesn’t advertise its product pricing on its websites. Publicly available data shows the platform has a 30-day free trial for proof of value.

• Small bandwidth with up to 300 Mbps of average bandwidth and 200 hosts: Costs $30,000.
• Medium bandwidth with up to 2 Gbps of average bandwidth and 1,000 hosts: Costs $60,000.
• Large bandwidth with up to 5 Gbps of average bandwidth and 10,000 hosts: Costs $100,000.

For your actual pricing, contact the company for a custom quote.

Features

• Darktrace PREVENT – continuously monitors your attack surface for risks, high-impact vulnerabilities, and external threats.
• Darktrace DETECT – offers instant visibility of threats.
• Darktrace RESPOND – capable of interrupting fast-moving attacks and is customizable to take action only at specific times, on certain devices, or in response to certain events.
• Darktrace HEAL – restore your system back to health after an attack.

For a deeper understanding of cybersecurity and AI, read our guide: Generative AI and Cybersecurity

CrowdStrike: Best for Monitoring User Endpoint Behavior

The CrowdStrike Falcon is an AI-native security solution that leverages machine learning, behavioral AI, and a custom large language model to protect endpoints, detect threats, and respond to security incidents in real-time. It consolidates next-generation antivirus (AV), endpoint detection and response (EDR), and a 24/7 managed hunting service into a single lightweight agent, providing organizations with complete visibility and protection across their endpoints.

The lightweight agent continuously monitors and protects endpoints against various attacks by leveraging real-time indicators of attack and threat intelligence from across the enterprise, thereby providing proactive threat-hunting capabilities.

CrowdStrike uses behavioral AI to detect anomalies in user endpoint behavior, meaning it can monitor current activity as compared with past user actions to protect the perimeter. Its models are trained on trillions of data points daily, allowing it to target threats ahead of time.

Pros and Cons

Pricing

All bundles require a minimum purchase of 5 devices.

• Falcon Go: $299.95 per year.
• Falcon Pro: $499.95 per year.
• Falcon Enterprise: $924.95 per year.
• Falcon Elite: Custom pricing.
• Falcon Complete MDR: Pricing is available upon request.

Features

• Unified attack surface visibility.
• Pre- and post-incident response services.
• Supports importing IOCs.
• Uses an AI-based detection system called user and entity behavior analytics (UEBA).

SentinelOne: Best for Advanced Threat-Hunting and Incident Response Capabilities

SentinelOne’s AI-backed cybersecurity solution, SentinelOne Singularity, is an autonomous security platform that combines endpoint protection platform (EPP), EDR, and extended detection and response (XDR) into a single unified platform.

The platform leverages AI and ML algorithms to provide real-time prevention, detection, response, and threat hunting across user endpoints, containers, cloud workloads, and IoT devices. It protects against a wide array of cyberthreats, including malware, ransomware, exploits, and fileless attacks.

We ranked SentinelOne’s Singularity as one of the best AI security solutions because it aims to simplify and strengthen enterprise security operations by providing comprehensive and automated protection across the entire threat lifecycle, from pre-execution to post-execution.

In sum, its integrated suite of tools works in concert to enable excellent incident response and threat hunting functionality.

Pros and Cons

Pricing

• Singularity Core: $69.99 per endpoint.
• Singularity Control: $79.99 per endpoint.
• Singularity Complete: $159.99 per endpoint.
• Singularity Commercial: $209.99 per endpoint.
• Singularity Enterprise: Pricing is available upon request.

Features

• Ability to identify and triage threats.
• Enables companies to ingest data from various sources.
• Identifying and then very quickly launch threat detection and response.
• Advanced threat-hunting capabilities.

Check Point Software: Best for Network Monitoring and Security

Check Point Software Technologies leverages AI capabilities to enhance its cybersecurity offerings at various levels. Its ThreatCloud AI platform, which drives the actions of the platform’s elements, collects and analyzes threat data from various sources.

This AI intelligence also supports Check Point’s global sensors, research teams, customers, and partner community. This intelligence is then integrated into Check Point’s security solutions to protect against known and unknown threats – the AI enables the response to be proactive.

Check Point’s Quantum also leverages AI and deep learning capabilities to protect your network, cloud, data center, IoT, and remote users against Gen V cyberattacks (also known as “advanced weapon grade” attacks). Its threat prevention solution includes security features such as a firewall, intrusion prevention system (IPS), anti-bot, antivirus, application control, and URL filtering to enable you to combat cyberattacks and threats.

Pros and Cons

Pricing

Check Point doesn’t advertise its rates on its websites. Contact the company for a detailed quote.

Features

• Prevent known and zero-day attacks across networks, endpoints, cloud, and email.
• Uses UEBA to identify anomalous behavior indicative of a potential threat.
• Third-party threat intelligence feeds.
• ThreatCloud AI campaign hunting.
• Anti-phishing AI engine.

Fortinet: Best for Preventing Zero-Day Threats

Fortinet FortiGuard is an AI-powered system incorporating threat intelligence, real-time threat analysis, and global threat protection to identify and block advanced threats and attacks. The services integrate with security solutions across Fortinet’s broad portfolio to provide security capabilities that protect applications, web traffic, content, devices, and users located anywhere.

A core element: the platform is regularly updated with the latest threat intelligence from FortiGuard Labs experts, data from across Fortinet’s broad sensor base, and zero-day intelligence feeds. This ensures that organizations are protected against emerging threats and zero-day vulnerabilities.

Additionally, FortiGuard’s service portfolio includes content security and NOC/SOC security (very important given the core nature of the Security Operations Center). It also offers SOC-as-a-Service functionality and provides consistent cybersecurity assessments and readiness alerts.

Pros and Cons

Pricing

Fortinet doesn’t advertise its rates on its websites. Contact the company for a detailed quote.

Features

• It protects against all OWASP Top-10 threats, DDOS attacks, and bot attacks.
• Indicator of compromise detection.
• AI-based inline malware prevention.
• AI-powered SandBox engine.
• Focused on preventing zero-day threats.

Zscaler: Best for Data Loss Prevention

Zscaler is a cloud-based security platform that provides internet security and web filtering services. It uses proprietary large language models and AI to enhance and improve its security offerings.

The company’s LLMs are integrated with a massive data lake that handles more than 300 billion daily transactions, allowing for continuous learning and improvement of its AI models. This enables Zscaler to provide advanced AI-driven outcomes and capabilities for IT and security teams.

These AI-driven outcomes are particularly notable for data loss prevention; Zscaler’s common DLP use cases includes securing data in motion, securing endpoint data, and the ability to protect against misconfigurations.

Zscaler operates on the principle of zero-trust connectivity, meaning that it assumes everything on the network is potentially malicious and does not automatically trust any user or device. Instead, it authenticates and validates every user and device before granting access to resources, which also supports DLP.

Pros and Cons

Pricing

Zscaler doesn’t advertise its rates on its websites. Contact the company for a detailed quote.

Features

• AI-powered phishing and C2 detection.
• Standard digital experience monitoring.
• Data loss prevention capability.
• AI-powered phishing detection.
• Automated, AI-powered root cause analysis.

Trellix: Best for Complex IT Environments That Require Continuous Monitoring

Trellix is a product of the merger of the security product divisions of McAfee Enterprise and FireEye. The platform excels in continuous monitoring – which enables proactive threat detection – by combining signature-based identification, behavioral analytics, and real-time monitoring.

Trellix XDR leverages advanced machine learning and AI techniques to analyze, correlate and monitor data from various sources, including network traffic, endpoint behavior and threat intelligence feeds. Its continuous monitoring enables it to detect sophisticated and complex threats that traditional security solutions might miss.

Trellix’s AI and security operation is capable of operationalizing threat intelligence, reducing alert noise and automating responses to security incidents, resulting in faster response times and proper incident management.

Notably, its XConsole combines security controls and an advanced research center to provide a unified view of the security landscape and enhanced visibility into network traffic, endpoint activity, and user behavior — allowing analysts to identify and remediate threats before they can cause damage.

Pros and Cons

Pricing

Potential customers must contact an expert at Trellix to receive pricing information.

Features

• Signature-based engine to find and block known malware.
• Behavior-based analytics engine to stop advanced threats.
• Incorporates UEBA capabilities to detect anomalous user behaviors that may indicate insider threats or compromised accounts.
• Real-time monitoring.

Vectra AI: Best for Hybrid Attack Detection, Investigation, and Response

Vectra AI Attack Signal Intelligence platform combines human intelligence, data science, and machine learning to detect cyberattacks in real time. The company’s AI and cybersecurity solution gives organizations constant visibility into their network security posture, helps prioritize potential threats, and enables quick response and mitigation to minimize the impact of hybrid cyberattacks.

Significantly, with the prevalence of “hybrid attacks” (two or more combined attacks to break the perimeter) Vectra offers a tool to prevent these attacks. The tool combats various hybrid attack types, such as account takeovers, data breaches, ransomware, supply chain attacks, and nation state attacks – this last attack tends to be particularly robust.

Vectra AI uses the detect, prioritize, investigate, and respond model to remediate and mitigate cyberthreats and also integrates detections across identity, public cloud, SaaS, and data center networks to provide a holistic view of an organization’s security landscape.

Pros and Cons

Pricing

Though Vectra AI doesn’t display product pricing on its website, publicly available information reveals that Vectra’s Cognito Threat Detection and Response pricing ranges up to $5,000 for month-to-month licenses and up to $50,000 for annual licenses, depending on your selected service. For actual rates, contact Vectra’s sales team for a quote.

Features

• Automatically analyzes attacker behaviors post-compromise and in real time.
• Automatically correlates, scores, and ranks incidents by urgency across all network, identity, cloud, and SaaS environments.
• Threat intelligence integration.
• AI-based threat detection and response geared for hybrid attack defense.
• Machine learning techniques, including deep learning and neural networks.

Cybereason: Best for Defending Against MalOps

Cybereason’s platform uses behavioral analytics and artificial intelligence to detect and respond to threats in real-time, helping organizations recognize and stop attacks before they can cause significant damage.

Among its other defense strategies, Cybereason’s platform combats MalOps, which is the full range of events that take place in coordinated hacking attacks. To accomplish this, the solution uses NGAV-based behavioral and machine learning techniques, with an approach that works to prevent known and unknown MalOps threats for fast response across the network and cloud infrastructure.

Cybereason uses an AI-driven XDR platform – as cybersecurity professionals know, the XDR architecture is considered to be leading-edge in the security sector. Its XDR tools enable forensic analysis to assist security teams as they investigate and remediate security incidents in rapid-response mode.

Pros and Cons

Pricing

Potential customers must contact an expert at Cybereason to receive pricing information.

Features

• Posture and incident management.
• Threat intelligence.
• Mobile threat defense.
• Digital forensic and incident response.

Tessian: Best for Protecting Against Email-Based Threats

Tessian’s platform uses AI behavior-based protection to prevent accidental and intentional loss of data over email – an important goal, given that email is one of the true weak points in the perimeter.

Tessian protects organizations from phishing attacks, accidental data leakage, and unauthorized email activity. It uses AI algorithms to analyze email communication patterns, identify suspicious behavior, and provide real-time warnings and training to employees regarding potential security risks. Significantly, Tessian is capable of protecting companies against compromised business email, account takeover and “misdirected” email. It also offers tools to combat image and QR code attacks, which is an attack type that will likely grow in the years ahead.

Tessian’s goal is to make email communication more secure and prevent data breaches caused by human error or malicious intent. The worst of these threats, like financial fraud and credential theft, do certainly deserve special tools to combat them – they cost businesses large sums annually. 

Pros and Cons

Pricing

Tessian doesn’t advertise its product pricing on its website. However, publicly available data shows that the Tessian Cloud Email Security platform (100 inboxes protected) costs $40,080 per year. Contact the company sales team for a quote to get your actual pricing.

Features

• Protect against QR code phishing, BEC, executive impersonation, and domain spoofing.
• Automate removal of end user reported threats.
• Behavioral analysis.
• Tessian’s machine learning identifies threats in image-based text, QR codes, URLs, subject headings, body text, and inside of email attachments.

Honorable Mentions: Leading AI Security Solutions 

Aside from the AI security solutions we analyzed above, other top-tier platforms worth mentioning are as follows. 

1. Cylance: A cybersecurity solution that leverages AI and ML to detect and prevent malware. Cylance AI offers protection for modern enterprise infrastructure, legacy devices and isolated endpoints.
2. Deep Instinct: The company uses a prevention-first approach to stop ransomware and other malware by using predictive prevention powered by deep learning.
3. LogRhythm: LogRhythm is a security intelligence company that offers various cybersecurity solutions, including SIEM, SOAR, UEBA and NDR to help organizations detect, investigate and respond to cyberattacks.
4. VIPRE: VIPRE offers two threat intelligence solutions (VIPRE ThreatAnalyzer and VIPRE ThreatIQ) designed to detect, analyze and destroy persistent threats 
5. Stellar Cyber: Stellar is an AI-driven open XDR platform that collects and normalizes security alerts, logs and telemetry from products. It also automatically detects and correlates threats using purpose-built Graph ML, allowing you to hunt for, investigate and eliminate threats quickly.
6. Sophos: The company offers detection and response, firewall, cloud and managed service solutions for network security and unified threat management.
7. Dataminr: Dataminr offers real-time event and risk detection to help you discover, prioritize and categorize critical information. They use deep learning-based multi-modal AI fusion methods to improve event detection accuracy. 
8. Cynet: The solution offers an automated XDR platform that allows security teams to detect, prevent, correlate, investigate and respond to threats across endpoints, users, networks and SaaS applications.
9. SparkCognition: SparkCognition offers AI solutions that enable companies to predict future outcomes, optimize processes and prevent cyberattacks.
10. Targeted Attack Analytics (TAA) by Symantec: TAA identifies incidents with AI and advanced machine learning. Symantec EDR uses TAA data to generate new incidents or to add to existing Symantec EDR incidents.

How to Choose the Best AI Security Software for Your Business

There are many factors that determine the best AI security solution for you. These include your security needs, organization size, team, and budget. While most AI security software promises similar capabilities, they are not created equal — some are more powerful than others, with cutting edge XDR capability, while some excel in certain areas like predictive threat response.

For instance, Tessian caters to those shopping for email security, while Check Point is more focused on network security. Vectra includes tools to prevent hybrid attacks.

Review your current security architecture and determine which areas need AI-powered solutions — email security, network security, endpoint protection, data loss prevention, or insider threat detection. Be sure to consider costs, features, complexity, and integrations before settling for a solution. To the extent possible, use a trial version of the AI cybersecurity solution before making a final decision.

Frequently Asked Questions (FAQs)

We answered the most commonly asked questions about the best AI security solutions to help you determine the best option for your business.

What is the best AI security solution?

The best AI security tool for you depends on your needs. Our analysis above evaluated several top-rated AI security solutions for different users. The best solution for your business is one that integrates fully into your existing infrastructure.

How do AI security solutions detect and prevent threats?

AI security solutions leverage machine learning algorithms to analyze network traffic, user behavior, and system logs to detect patterns and anomalies associated with known or unknown threats. AI can analyze these threats far faster than human security administrators.

How does AI help in incident response?

AI helps in incident response by automating the analysis of security events, prioritizing alerts based on risk, and providing insights into the root cause of incidents. AI’s strength in incident response is that the system “learns” over time, and so is increasingly effective month after month.

Bottom Line: AI Security Solutions 

When shopping for your company’s best AI security solution, select the one that ticks all or most of your boxes – specifically, the one that truly works with your infrastructure, with its mix of on-premise, network configuration and cloud-based software.

As you consider the features and capabilities of various AI security tools, it is also necessary to consider the product costs. Since most vendors do not advertise their rates on their website, you must contact their sales team for personalized quotes to determine if the tool is within your budget – realize you likely have some bargaining power in these situations. Additionally, ensure you understand the vendor’s reputation, customer support, and implementation process.

For a deeper understanding of the power of artificial intelligence, read our guide, What is Artificial Intelligence? 

The post 20 Best AI Security Software for 2024 appeared first on eWEEK.

An ever-growing number of generative AI chatbots are now entering the market, but not all chatbots are created equal. We analyzed the best generative AI chatbots to help you determine the best conversational AI app for your business.

Here are our picks for the top generative AI chatbot software.

Top 20 Generative AI Chatbot Software: Comparison Chart

We compared the key features of the top generative AI chatbot software to help you determine the best option for your company:

Please note: All ratings are based on a range of 1 to 5, with 5 being the best option.

Bing Chat Enterprise: Best Chatbot for Organizations in the Microsoft Ecosystem

Overall rating: 3.13

• Cost: 3.95
• Feature Set: 3.5
• Ease of Use: 1.75
• Quality of Output: 2.5
• Support: 4

Microsoft generative AI tool Bing Chat Enterprise uses GPT-4 — which includes a top large language model — to generate natural language responses to users’ queries. Bing Chat Enterprise has three conversation styles: creative, balanced, and precise. These styles help users set the tone for the expected response to their query.

Bing Chat Enterprise is available in 160 regions; significantly, users can also access it via the Windows Copilot Sidebar, making this app easily accessible. Indeed, Microsoft is incorporating AI across their product portfolio, so this chat app will likely show up in a number of applications. If your company uses Microsoft, this chap app is a good choice.

The greatest strong point for the Bing Chat tool is that it’s produced by Microsoft – arguably the leader in AI today. The company’s deep resources and dominant technical expertise in AI software should support this chat app very well in the years ahead.

Additionally, Microsoft is skilled at serving both the consumer and the business market, so this chat app can be configured for a variety of levels of performance – it has the depth of features needed to serve the SMB market and large enterprise.

Pros and Cons

Pricing

Bing AI chat is available at no additional cost for customers who are licensed for Microsoft 365 E3, E5, Business Standard, Business Premium, or A3 or A5 for faculty. If you don’t have those licenses, you can purchase Bing AI as a standalone tool for $5 monthly.

Features

• A versatile mix of conversation styles for different enterprise AI use cases.
• Bing’s citation capability allows you to fact-check its output.
• It allows users to upload an image and it can also generate an image for you.

Also see: Top Generative AI Apps and Tools

ChatGPT: Best Chatbot for Versatility and Advanced Generative AI Features

Overall rating: 4.51

• Cost: 4.15
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 3.75
• Support: 5

Developed by OpenAI as part of the GPT (Generative Pre-trained Transformer) series of models, ChatGPT is more than just another natural language processing (NLP) tool designed to engage in human-quality conversations with users. The fact that it was developed by OpenAI means this generative AI app benefits from the pioneering work done by this leading AI company – ChatGPT, after all, was the first generative AI app to come to market, launching in November of 2022.

The OpenAI platform can perform NLP tasks, such as answering questions, providing recommendations, summarizing text, and translating languages. Aside from content generation, developers can also use ChatGPT to assist with coding tasks, including code generation, debugging help, and programming-related question responses.

Also supporting this app: OpenAI has received significant funding from Microsoft (and will almost certainly receive still more) so ChatGPT will likely be a leader in the years ahead, both in terms of advanced functionality (depth and versatility of toolset) and its ability to offer technology that’s ahead of the curve.

Pros and Cons

Pricing

• Free: You can use the free plan at no cost.
• ChatGPT Plus: $20 per month.
• Enterprise plan: Custom quotes.

Features

• Analytics dashboard to understand usage for enterprise users.
• Multilingual features: It can understand and generate text in multiple languages.
• Contextual understanding of extended conversation.

OpenAI Playground: Best Chatbot for Customizability

Overall rating: 3.0

• Cost: 4.15
• Feature Set: 5
• Ease of Use: 0.55
• Quality of Output: 2.5
• Support: 2

OpenAI Playground was designed by the same generative AI company that created ChatGPT (see above). As such, it is well funded and is continuously improved by some of the best developers in the AI industry. Expect it to stay ahead of the curve in terms of feature set.

It is a web-based environment allowing users to experiment with different OpenAI models, including GPT-4, GPT-3.5 Turbo, and others. OpenAI Playground is suitable for advanced users looking for a customizable generative AI chatbot model that they can fine-tune to suit their business needs. This advanced platform enables a vast level of choices and approaches in an AI chatbot.

What OpenAI Playground’s focus on customizability means is that it is ideal for companies that need a very specific focus to their chatbot. For instance, a sophisticated branding effort or an approach that requires a very proprietary large language model, like finance or healthcare. Given that this app needs true developer expertise to be fully customizable, it is not the best choice for small businesses or companies on a tight budget.

Pros and Cons

Pricing

OpenAI Playground is priced per 1,000 tokens (1,000 tokens equals to 750 words). Pricing for this tool varies based on your chosen model. New users can get $5 in free credit to use for their first three months.

GPT-4 models

• 8K context: Input costs $0.03 per 1K tokens, while output costs $0.06 per 1K tokens.
• 32K context: Input costs $0.06 per 1K tokens, while output costs $0.12 per 1K tokens.

GPT-3.5 Turbo

• 4K context: Input costs $0.0015 per 1K tokens, while output costs $0.002 per 1K tokens.
• 16K context: Input costs $0.003  per 1K tokens, while output costs $0.004 per 1K tokens.

Features

• Text and completion summarization capability.
• Multiple options for model selection.
• Language translation capability.
• Sentiment analysis.

Also see: The Benefits of Generative AI

Perplexity AI: Best Chatbot for Finding Information on the Internet

Overall rating: 4.19

• Cost: 4.15
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 5
• Support: 2

Perplexity AI is a generative AI chatbot/search/answer engine that allows users to express queries in natural language​​ and provides answers based on information gathered from various sources on the web. When you ask a question on Perplexity AI, it does more than provide the answer to your query –  it also suggests related follow-up questions. In response, you can either select from the suggested related questions or type yours in the text field.

Perplexity AI’s Copilot feature can guide users through the search process with interactive multiple searches and summarized results – this capability is helpful when exploring complex topics. However, it’s limited to five searches every four hours for free plan users and up to 300 searches for paid users.

Perplexity AI’s strength in searching the Internet means this tool is ideal for advanced researchers, from academic to small business to large enterprise, including companies that want to explore how they’re viewed on the Web. The app’s greatest strength: because AI enables it to understand your search query at a multi-dimensional level, the app can guide you in directions you might not have thought of. Think of this app as a “serious researcher’s best friend.”

Pros and Cons

Pricing

• Free: Available at no cost with limited features.
• Pro: It costs $20 per month or $200 per year.

Features

• Support Claude 2 and GPT-4.
• Support 30 languages, including English, Bengali, Danish and more.
• Text and PDF file upload capability.

YouChat: Best Chatbot for Students

Overall rating: 3.64

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 5
• Quality of Output: 3.75
• Support: 1

Designed by You.com, YouChat is an AI-powered generative chatbot that can summarize text, write code, suggest ideas, compose emails, and answer general questions based on information available on the web.

It also cites its information source, making it easy to fact-check the chatbot’s answers to your queries. YouChat combines various elements in its search results, including images, videos, news, maps, social, code, and search engine results on the subject.

In essence, YouChat is a lighter weight tool with an affordable price plan that performs a wide array of tasks – particularly those needed by students. It certainly would help with most homework assignments. YouChat offers an easy user interface that will appeal to a busy user base that wants to jump right in without undergoing a lot of technical training.

The upside of this kind of easy-to-use app is that, as generative AI advances, today’s fairly lightweight tools will likely offer an enormous level of functionality. So any student or SMB users who starts with it now will probably reap greater benefits in the months and years ahead.

Pros and Cons

Pricing

• Free: Available at no cost for up to 10 AI writing generations.
• YouPro: $14.99 per month.
• YouPro for Education: $6.99 per month.

Features

• Code generator.
• Multimodal search capability.
• Supports social media profiles.

Also see: Generative AI Examples

Chatsonic: Best Chatbot for Individuals in the Creative Industries

Overall rating: 4.03

• Cost: 4.55
• Feature Set: 4.4
• Ease of Use: 5
• Quality of Output: 2.5
• Support: 2

Trained and powered by Google Search to converse with users based on current events, Chatsonic positions itself as a ChatGPT alternative. The AI chatbot is a product of Writesonic, an AI platform geared for content creation. When using Chatsonic, you can toggle on the “Include latest Google data” button to add real-time trending information.

The benefit to this “latest data” approach is that it helps individuals in the creative industries – like advertising and marketing – to stay very up to date on current trends. In contrast, some of the more advanced chatbots use large language models that are updated only so often, so those looking for this week’s information won’t find what they need.

This current events approach makes the Chatsonic app very useful for a company that wants to consistently monitor any comments or concerns about its products based on current news coverage. Indeed, some companies will use this app in combination with other AI chatbot apps; they may use 1-2 other apps as their main chatbots, with the Chatsonic chatbot reserved specifically to perform a broad and deep brand response monitoring function.

Pros and Cons

Pricing

• Free trial: Up to 10,000 words per month.
• Unlimited: $20 per month when billed monthly or $16 per month when billed yearly – limited to one user.
• Business: $19 per month when billed monthly or $12.67 per month when billed annually – for up to 200,000 words for GPT 3.5 or 33,333 words for GPT 4.0 – limited to one user. With this plan, you can increase your word count and number of users at an additional cost.
• Enterprise: Custom quote.

Features

• It has a Sonic Editor (Google Docs-like editor).
• Integration with third-party apps.
• Offers over 100 AI templates.

On a related topic: What is Generative AI?

Google Bard: Best Chatbot for Brainstorming Ideas

Overall rating: 4.28

• Cost: 5
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 1

Google Bard is an AI-powered LLM chatbot built on the PaLM2 (Pathways Language Model, version 2) AI model. You can export your Google Bard conversation to Google Docs or Draft in Gmail. The platform also allows you to create a shareable public link you can send to a third party, so this app is very useful in collaborative workflows for professional work environments.

It’s a major plus for this app that it’s developed and supported by Google. Admittedly, this app had some difficulties when it was first rolled out; Google was apparently scrambling to keep up with the phenomenal success of OpenAI’s ChatGPT, and didn’t iron out all the bugs first. However, Bard is being actively developed and will benefit greatly from Google’s deep resources and legions of top AI developers.

An important benefit of using Google Bard is that its supporting knowledge base is as large as any chatbot’s – it’s created and updated by Google. So if your team is looking to brainstorm ideas or check an existing plan against a huge database, the Bard app can be very useful due to its deep and constantly updated reservoir of data.

Pros and Cons

Pricing

Google Bard is free to use.

Features

• Ability to export conversation.
• Its “Google it” function directs you to a search engine, providing more information on your query.
• It can generate code in at least 20 programming languages.

Also see: ChatGPT vs. Google Bard: Generative AI Comparison

Socrates.ai: Best Chatbot for Internal Knowledge-Base Management

Overall rating: 2.1

• Cost: 0 [no information available]
• Feature Set: 3
• Ease of Use: 3
• Quality of Output: 2.5
• Support: 2

Socrates.ai is an artificial intelligence platform that provides businesses with an array of conversational AI solutions. It enables companies to create and deploy conversational agents that can interact with users naturally, and is part of the wave of chatbots that is playing an ever greater role as a “first responder” to real time, in-bound consumer questions and concerns.

The Socrates app can be integrated into various channels, such as websites, mobile apps, and messaging platforms, to enhance user experience and support automation. Significantly, the app’s large library of pre-built and pre-tested content enables a company to efficiently – and constantly – query its internal knowledge base and use company-specific terminology in chatbot answers. This key feature makes Socrates ideal for organizations that need to frequently update chatbot responses based on fresh internal data.

Additionally, Socrates integrates with third-party enterprise apps, providing a far fuller range of features. It also facilitates bot to bot communication, which also helps this chatbot stay refreshed with more current information.

Pros and Cons

Pricing

Available upon request.

Features

• Integration with third-party enterprise apps.
• It has a database of about 1,000 employee questions.
• Supports natural language processing and understanding.
• Bot-to-bot conversations.

Also see: Generative AI Companies: Top 12 Leaders

HuggingChat: Best Chatbot for Developers

Overall rating: 3.33

• Cost: 5
• Feature Set: 2.9
• Ease of Use: 4.75
• Quality of Output: 1.25
• Support: 1

Developed by Hugging Face, HuggingChat is a chatbot based on the Open Assistant Conversational AI Model. It uses NLP and ML algorithms to interact with users and can generate answers to questions, write essays, write code, translate text, and construct emails. The platform has been trained on a large dataset of diverse conversations and can learn from new interactions.

Most significantly, Hugging Face has a large and enthusiastic following among developers – it’s something of a favorite in the development community. Its platform is set up as an ideal environment to mix and match chatbot elements, including datasets ranging from Berkeley’s Nectar to Wikipedia/Wikimedia. And the AI models available range from Anthropic to Playground AI.

Many of these resources may not mean much to the SMB owner or enterprise manager – but they mean a great deal to developers with the expertise to use a deep resource base to customize an AI chatbot. Given that HuggingChat offers such a rich developer-centric platform, users can expect it to grow rapidly as AI chatbots gain still more adoption.

Pros and Cons

Pricing

HuggingChat is free to use. You can also subscribe to the Pro plan at $9 per month to get early access to new features. They also offer an Enterprise Hub plan at $20 per user per month.

Features

• It has web search functionality that complements its response with web content.
• Multilingual support.
• It can debug and write code and create Excel formulas.

Also see: Generative AI Startups

Jasper: Best Chatbot for Marketing and Sales Teams

Overall rating: 4.23

• Cost: 2.65
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 3

The Jasper generative AI chatbot can be trained on your brand voice to interact with your customers in a personalized manner. Jasper partners with OpenAI and uses GPT-3.5 and GPT-4 language models and their proprietary AI engine. The company also sources from other models such as Neo X, T5, and Bloom.

Clearly, Jasper’s strongest upside is its brand voice functionality, which allows teams and organizations to create highly specific, on-brand content. This capability is invaluable for marketing and sales team that need to ensure that all chatbot communications are created with an accurate brand identity.

Out of the box, Jasper offers more than 50 templates, so the user won’t need to create a chatbot persona from scratch. The wide array of models that Jasper accesses and its focus on customizing for brand identity means this is a choice that marketing teams should at least audition before they make any final selections for an AI chatbot.

Pros and Cons

Pricing

• Creator: It costs $49 per month when billed monthly and $39 per month when billed annually.
• Teams: It costs $125 per month when billed monthly and $99 per month when billed annually.
• Business: Custom quotes.

Features

• Browser extension available.
• Support up to 30 languages.
• Integrates with Zapier, Webflow, Make, Google Sheets, and other tools.
• Collaboration capability.

Tidio: Best for Small and Medium-Sized Businesses

Overall rating: 4.23

• Cost: 4.13
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

SMBs looking for an easy-to-use AI chatbot to scale their support capacity may find Tidio to be a suitable solution. With Tidio Lyro, businesses can automate their customer support processes, reduce response times, and handle tasks such as answering frequently asked questions. You can use Tidio Lyro to answer customer inquiries, provide automated responses, and assist with basic analytics, allowing you to manage customer support efficiently.

Tidio fits the SMB market because it offers solid functionality at a reasonable price. SMBs are under pressure to offer basic customer service at a low cost; to address this, Tidio allows the creation of wide array of pre-written responses for simple questions that customers ask again and again. Most important in terms of tools and affordability, Tidio offers add-ons at no extra cost, including sales templates to save time with setup.

Additionally, the quality of Tidio’s output was ranked highly in our research, so even as the AI chatbot focuses on affordability, it offers a quality toolset.

Pros and Cons

Pricing

• Free: Available at no cost for up to 20 live chat conversations.
• Starter: It costs $29 per month. Includes three seats.
• Communicator: It costs $25 per user per month.
• Chatbots: Starts at $29 per month. Includes three seats.
• Bundle solution — Communicator plus Chatbots: Starts at $54 per seat per month.
• Tidio+: Starts at $394 per month.

Features

• Live chat capability.
• Integration with Messenger, Instagram, WhatsApp, and email services.
• Multi-language support.
• Canned responses.

ChatSpot: Best for HubSpot Customers

Overall rating: 4.40

• Cost: 5
• Feature Set:5
• Ease of Use: 5
• Quality of Output: 5
• Support: 1

ChatSpot combines the capabilities of ChatGPT and HubSpot CRM into one solution. With this tool, you can draft blog posts and tweets and also create AI-generated images. You can feed this app a prompt to enable you to get specific data from your HubSpot CRM.

ChatSpot allows you to perform many functions, including adding contacts and creating tasks and notes. You can also ask it to summarize your CRM data or generate a bar chart of results to understand your company’s performance.

If you’re a HubSpot customer, this chatbot app can be a useful choice, given that Hubspot offers so many ways to connect with third party tools – literally hundreds of business apps. And HubSpot, as its users are well aware, is a platform that offers great functionality for sales reps. This chatbot will likely remain a top candidate for sales and marketing professionals that need improved functionality for customer sales and service.

Pros and Cons

Pricing

ChatSpot is a free tool.

Features

• OpenAI’s GPT-3 and GPT-4.
• Integration with ChatGPT, HubSpot, DALL-E, and Google Docs.
• Prompt templates and library.

Drift: Best for Businesses that Rely on B2B Sales and Marketing

Overall rating: 3.78

• Cost: 1.75
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 2

Drift’s AI is trained on 100M+ B2B sales and marketing conversations, enabling it to understand and respond to B2B customer inquiries in the conversational manner that’s expected in this market sector (including multi-language support).

The Drift AI chatbot is designed to handle different types of conversations, including lead nurturing, customer support, and sales assistance. It can engage with website visitors and provide relevant information or route inquiries to the appropriate human representative.

Drift can be custom-trained for your B2B business in fine detail, allowing it to learn your brand’s voice and respond in a manner similar to your in-house reps. The B2B market is a specific use case for AI chatbots, and Drift’s focus on this market means that a B2B company can set up a highly functional chatbot with far less work – and one that will evolve with the B2B market over time.

Pros and Cons

Pricing

• Premium: $2,500 per month, billed annually.
• Advanced: Available upon request.
• Enterprise: Custom quote.

Features

• User administration with role-based access control.
• Offers live chat, custom chatbots, and AI-powered chatbots.
• Meeting scheduler (Google, Office 365, and Teams integration).
• Conversation and conversion reporting capability.

Ada: Best for Customer Service Automation

Overall rating: 3.75

• Cost: 0.63
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 2.5

Ada is an AI-powered customer service automation platform that uses natural language processing and machine learning algorithms to automate customer service tasks. It is designed to help resolve customer issues, allowing businesses to streamline their customer service operations and enhance the customer experience.

There are two ways to use Ada. You can either connect it to your knowledge base and use generative AI to answer questions grounded in your existing content. Or you can build a hard-coded chatbot using Ada’s natural language understanding and its drag-and-drop platform for a pre-scripted easy and fast setup.

In either case, Ada enables you to monitor and measure your bot KPI metrics across digital and voice channels, such as automated resolution rate, average handle time, containment rate, CSAT, and handoff rate. It also offers predictive suggestions for answers, allowing the app to stay ahead of customer interactions. To its credit, Ada’s user interface is intuitive and easy to use, which creates a faster onboarding process for customer service reps.

Pros and Cons

Pricing

Ada offers two pricing plans: Generative and Scripted. However, the vendor doesn’t advertise its plan rate – interested buyers must contact Ada’s sales team for a quote.

Features

• Integration with third-party apps like Shopify, Marketo, and Clearbit.
• Automated resolution measurement.
• Advanced branding includes additional customizations such as chat widget size, color schemes, font sizes, and dark mode.

LivePerson: Best for Conversation Analytics

Overall rating: 4.13

• Cost: 0.63
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 5

With the LivePerson AI chatbot, you can simulate human-like conversation by interacting with users in a natural, conversational manner. Its goal is to discover customer intent – which is the core of most successful sales interactions – using analytics. To this end, LivePerson offers what it calls a “meaningful automated conversation score,” which is a metric that attempts to quantify whether a given bot-human interaction was successful in terms of company branding and service.

Additionally, the platform enables you to convert webpages, PDFs, and FAQs into interactive AI chatbot experiences that use natural human language to showcase your brand’s expertise. The bot’s entire strategy is based on making as much content as possible available in a conversational format.

LivePerson can be deployed on various digital channels, such as websites and messaging apps, to automate customer interactions, provide instant responses to inquiries, assist with transactions, and offer personalized recommendations. Significantly, LivePerson is also geared to be embedded in social media platforms, so it certainly aims to reach a large consumer base.

Pros and Cons

Pricing

LivePerson offers two plans, which are Conversational Cloud and Conversational Cloud & Generative AI. But both plans are charged on a pay-as-you-go basis. LivePerson says you will only pay for resolutions, not seats, chats, or minutes. The Conversational Cloud is ideal for businesses looking to “automate messages and calls, optimize consumer insights, increase agent productivity with LivePerson AI,” while the Conversational Cloud & Generative AI help organizations “accelerate automation, increase conversion rate, and boost agent productivity with Generative AI.”

Features

• Conversation builder and orchestrator.
• Supports administrative function, which includes the ability to create and manage users and skills.
• It supports 19 messaging channels, including Facebook, Instagram, X (formerly Twitter), and WhatsApp.
• Reporting and analytics.

Replika: Best for Personal Use

Overall rating: 3.16

• Cost: 5
• Feature Set: 0.63
• Ease of Use: 5
• Quality of Output: 5
• Support: 1.5

Replika is an artificial intelligence chatbot designed to have meaningful and empathetic conversations with users. Its focus is based more on entertaining and engaging personal interaction rather than straight forward business purposes.

To support its goal, Replika uses natural language processing and machine learning algorithms to understand and respond to text-based conversations. Replika aims to be a virtual friend or companion that learns from and adapts to the user’s personality and preferences.

To better engage, the platform learns a user’s texting style and mimics it. Of course this means that the longer a user interfaces with the app, the more accurately Replika can mimic a user’s style.

Its motto is “My AI Friend.” The app claims that it can offer dialogue geared for emotional support. To that end, it can engage in a wide variety topics, or even help users learn new things.

Pros and Cons

Pricing

• Free plan available.
• Month-to-month: $19.99 per month.
• Annual plan: $5.83 per month, billed annually.
• Lifetime: $299.99 billed once.

Features

• Role-playing activities.
• Communicate through text, pictures, voice calls, and video calls.
• It can engage in conversations about a wide range of topics, from personal interests to general knowledge.
• Replika can guide users through specific conversation topics, such as mindfulness, stress management, or self-care.

Intercom: Best for Handling Support Queries

Overall rating: 4.33

• Cost: 2.25
• Feature Set: 5
• Ease of Use: 4.5
• Quality of Output: 5
• Support: 5

The Intercom AI chatbot aims to improve customer experience, automate support processes, and enhance user engagement. Its AI-powered chatbot, Fin, is powered by large language models from OpenAI. The fact that OpenAI (with all of its deep funding and vast expertise) provides Intercom’s underlying engine is clearly a plus.

Intercom can engage in realistic conversations with customers, helping to resolve common issues, answer questions, and initiate actions – in sum, it’s an app aimed clearly at the lucrative call center sector. So what distinguishes it? First, it has gained wide adoption in the industry, and is used by companies ranging from Amazon to Microsoft to Meta.

Also, it offers a “plug and play” chatbot architecture to make setup relatively easy. Particularly useful: Intercom’s “Composer AI” feature enables a call center rep to rephrase a message with one click, turning a single phrase into longer, more detailed response. It can easily summarize entire conversations with one click.

Pros and Cons

Pricing

Offers a 14-day free trial.

• Fin AI Chatbot: Fin usage is measured in resolutions at $0.99 per resolution.
• Essential: ​​$39 per seat per month.
• Advanced: $99 per seat per month.
• Expert: $139 per seat per month.

Features

• Support up to 43 languages.
• Integrates with Facebook and Instagram.
• Automatically answers customer questions based on support content.
• Article suggestions.

Kommunicate: Best for E-Commerce Businesses

Overall rating: 4.50

• Cost: 3.25
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 4

Kommunicate is a generative AI-powered chatbot designed to help businesses optimize customer support and improve the customer experience. One of its chief goals is assisting and completing sales for e-commerce vendors, though it also handles support and the full range of customer queries.

The app provides automated conversational capabilities through chatbots, live chat, and omnichannel customer support. Kommunicate can be integrated into websites, mobile apps, and social media platforms, allowing businesses to engage with their customers in real time and provide instant assistance regarding any issue that involves a sale or service.

To assist with this, it is offers a FAQ bot to lessen the load of simple, repetitive customer queries. The app’s feature set is far more robust due to long list of integrations, from OpenAI to IBM Watson, from Zapier to Shopify. It enables easy, seamless hand-off from chatbot to a human operator for those interactions that call for it.

Pros and Cons

Pricing

Offers a 30-day free trial.

• Lite: $100 month-to-month or $1,000 billed annually – up to two teammates. Costs $20 per additional teammate.
• Advanced: $200 month-to-month or $2,000 billed annually – up to five teammates. Costs $30 per additional teammate.
• Enterprise: Custom pricing.

Features

• Omnichannel – Web, mobile, and socials.
• CSAT rating.
• Integrations with third-party services include Agile CRM, Pipedrive, Zapier, and Zendesk.
• Enable you to manage customer conversations through bots, live chat, Facebook, WhatsApp, and Line.

Freshchat: Best for Automating Self-Service

Overall rating: 4.63

• Cost: 5
• Feature Set: 5
• Ease of Use: 5
• Quality of Output: 5
• Support: 2.5

Freshchat is an AI-powered bot and live chat platform powered by Freddy AI. Like many products in this sector, Freshchat enables businesses to automate customer interactions through chatbots and offers live chat capabilities for real-time customer support. It allows companies to manage and streamline customer conversations across various channels, such as websites, and an array of integrated apps.

Freshchat provides features like customizable chat widgets, agent collaboration, customer context, and analytics to track chat performance and customer satisfaction.

What distinguishes Freshchat is that it enables sales and marketing, and even support, to not only reach customers, but to scale those interactions so that the expertise of each live company staffer can be used to converse with many customers. It does this using its unified agent workspace, which holds a full menu of past conversations, as well as responses from sales, marketing and support, which an agent can quickly and easily share with an interested customer.

Pros and Cons

Pricing

• Free: Up to 10 agents.
• Growth: $23 per agent per month, billed monthly or $19 per agent per month billed annually.
• Pro: $59 per agent per month, billed monthly or $49 per agent per month billed annually.
• Enterprise: $95 per agent per month, billed monthly or $79 per agent per month billed annually.

Features

• Chatbot analytics.
• Canned responses.
• CSAT survey and report.
• Analytics and reporting.
• Multi-channel communication.

Crisp Chatbot: Best for Lead Nurturing

Overall rating: 4.55

• Cost: 5
• Feature Set: 3.5
• Ease of Use: 5
• Quality of Output: 5
• Support: 5

Crisp Chatbot uses AI to understand user queries and provide relevant responses. It can handle basic inquiries, provide product information, schedule appointments, and collect customer feedback.

In a growing trend across the AI chatbot sector, the Crisp Chatbot can be customized to match a business’s branding and tone. This is increasingly important in crowded markets where a number of companies are seeking to create a distinct brand to cut through the clutter.

Freshchat can also be integrated with other systems like CRM or ticketing systems to provide a seamless customer experience – and to facilitate later sales. It has an “Escalation Policies” tool that enables greater control for reps to move a challenging call to the right channel.

Most interesting: the app has a “Freddy Insights” tool that provides key trends and insights that can be fed into a conversation at opportune moments to prompt a faster decision.

Pros and Cons

Crisp MagicReply sample view

Pricing

• Offers a 14-day free trial.
• Basic: Free forever. Up to 2 seats included.
• Pro: $25 per month per workspace. Up to 4 seats included.
• Unlimited: $95 per month per workspace. Up to 20 seats included.
• Enterprise: Custom quote.

Features

• Integrations with social apps like Facebook Messenger, WhatsApp, Line, and Instagram.
• Conversation routing capability.
• Capable of sending multilingual messages.
• Its MagicReply feature provides suggested AI-powered chatbot answers on multiple channels and in several languages.

Key Features of Generative AI Chatbots

Natural Language Processing

Natural language processing is an very important feature of a generative AI chatbot. NLP enables the AI chatbot to understand and interpret casual conversational input from users, allowing them to have more human-like conversations. With NLP capabilities, generative AI chatbots can recognize context, intent, and entities within the conversation.

Context Understanding

Context understanding is a chatbot’s ability to comprehend and retain context during conversations – this enables a more seamless and human-like conversation flow. A quality artificial intelligence chatbot can maintain context and remember previous interactions, providing more personalized and relevant responses based on the conversation history. This enables chatbots to provide more coherent and relevant replies.

Personalization

When shopping for generative AI chatbot software, customization and personalization capabilities are important factors to consider, as they enable the tool to tailor responses based on user preferences and history. ChatGPT, for instance, allows businesses to train and fine-tune chatbots to align with their brand, industry-specific terminology, and user preferences.

Multilingual support

An AI chatbot’s ability to communicate in multiple languages makes it appealing to global audiences. This functionality also allows the chatbot to translate text from one language to another.

Also see: Best Artificial Intelligence Software

How to Choose the Best Generative AI Chatbot For Your Business

The best generative AI chatbot for your company serves your business’s needs and balances quality service with moderately expensive – or lower cost – pricing, based on what works with your budget. Additionally, you’ll need to ensure it has all the necessary AI features you need for your operations, and that these features will be supported going forward.

Organizations in the Microsoft ecosystem may find Bing Chat Enterprise beneficial, as it works better on the Edge browser. ChatGPT does not cite its data sources, but it is one of the most versatile and creative AI chatbots. Google Bard cites data sources and provides up-to-date information, but its response time is sometimes slow. Chatsonic can generate AI images as part of the answer to your query.

What seems like positives to you may be negatives to another user and vice versa. The best tool for your business is unique to you – conduct your own research enough to fully understand the chatbot market. Then identify your overall AI goals, and shop for a chatbot tool that offers features and capabilities that meet your requirements.

How We Evaluated the Best Generative AI Chatbots

Cost – 20%

We reviewed each AI chatbot pricing model and available plans, plus the availability of a free trial to test out the platform. Our research found that some platforms are completely free, while some offer both free and paid plans – a tool like Google Bard gives you access to all its features for free, ChatGPT has a free plan with access to GPT 3.5 capabilities, while GPT 4 requires a monthly subscription. On the other hand, Jasper is a paid chatbot offering a seven-day free trial.

Features set – 30%

Features carry the most weight (30%) in our evaluation process. We evaluated various capabilities offered by each generative AI software, including multi-language support, the ability to accept spoken word input, the programmability of the solution, the kind of users it is built for, and customization options.

Ease of use – 25%

We assessed each generative AI software’s user interface and overall user experience. This included evaluating the ease of installation, setup process, and navigation within the platform. A well-designed and intuitive interface with clear documentation, support materials and the AI chatbot response time contributed to a higher score in this category.

Quality of output – 10%

To determine the output quality generated by the AI chatbot software, we analyzed the accuracy of responses, coherence in conversation flow, and ability to understand and respond appropriately to user inputs. We selected our top solutions based on their ability to produce high-quality and contextually relevant responses consistently.

Support – 15%

Our analysis also considered the level of support provided by the AI software provider. We assessed the availability and responsiveness of customer support, including customer service hours, email support, live chat support and knowledge base.

AI Chatbots: Frequently Asked Questions (FAQs)

We answered the most commonly asked questions about AI chatbots below.

What features should businesses look for in AI chatbots?

Key features to look for in AI chatbots include NLP capabilities, contextual understanding, multi-language support, pre-trained knowledge and conversation flow management. It is also important to look for a tool with a high accuracy rating, even if the questions asked are complex or open-ended.

Why are AI chatbots important for businesses?

AI chatbots are important to businesses because they enhance customer experience and provide various operational benefits such as improved customer experience, personalized experiences, cost reduction, and increased productivity. Most important: they provide customer service at a far lower cost.

How can AI chatbots enhance customer support and engagement?

AI chatbots can boost customer support by providing 24/7 support, answering common questions, and personalizing interaction based on customer preferences (for instance, multilingual AI chatbots can communicate in multiple languages, enabling businesses to assist customers from different regions).

Bottom Line: Top AI Chatbots

Determining the “best” generative AI chatbot software can be subjective, as it largely depends on the business’s specific needs and objectives. Chatbot software is continuously evolving, and new chatbot entrants may offer innovative features and improvements over existing solutions. Therefore, the best chatbot for your business will vary based on factors such as industry, use case, budget, and desired features – and your own experience with AI. In short, there is no “one size fits all” chatbot solution.

Read next: 100+ Top AI Companies

The post 20 Best AI Chatbots in 2024 appeared first on eWEEK.

The process of selecting the best generative AI app builder can be daunting and overwhelming – the market is crowded. So we did the hard work for you by reviewing the available tools and curating a list of the best generative AI application builders, including their features, pros and cons, and pricing, to help you determine the best option for your business.

Top Generative AI App Builder: Comparison Chart

Here is a head-to-head comparison table of the best generative AI app builders.

Top 8 Generative AI App Builders

Appy Pie: Best for Ease of Use

Appy Pie is a no-code generative AI app development platform. It enables you to create applications and websites without coding or technical skills. With a simple drag-and-drop interface, you can easily design and customize your app or website.

Appy Pie’s generative AI capabilities allow you to generate images, logos, and artwork for your app or website, as the platform design interface offers numerous generative AI capabilities, such as an artificial intelligence text-to-image generator, an AI text-to-logo generator, an AI photo enhancer, an AI NFT generator.

Additionally, the platform offers an extensive collection of AI-generated templates like posters, cards, and other business graphic design templates to enable you to fast track your app development process. In short, this menu of tools means that Appy Pie clearly earns its “easy to use” reputation.

Appy Pie also offers enterprise features, like tools for creating workflow automation with Salesforce and Slack, and with Slack and Microsoft Teams.

Pros and Cons

Pricing

The company offers a 7-day free trial.

• Basic: $16 per app per month billed monthly or $14 per app per month billed annually.
• Gold: $36 per app per month billed monthly or $30 per app per month billed annually.
• Platinum: $60 per app per month billed monthly or $50 per app per month billed annually.
• Enterprise: Contact the company for pricing details.

Features

• App analytics with Google Analytics.
• Supported platforms include Android and iOS.
• Regulatory-compliant – PCI DSS.
• Integration with third-party apps.
• Support up to 30 languages, including Spanish, Arabic, French, and Hindi.

Also see: Top Generative AI Apps and Tools

Mobincube: Best for Affordability

With Mobincube, you can create and publish your mobile apps without coding knowledge. The platform provides a drag-and-drop interface and a range of templates and design elements to help you build and customize your apps based on your business needs.

Mobincube offers features for adding functionality to existing apps, such as integration with third-party services, push notifications, and in-app purchases. You can publish apps built on this platform on Google Play and the Apple App Store.

The best part – for those with a limited budget – is that Mobincube’s free plan offers extensive app building functionality. However, this AI app builder doesn’t have a reputation for enabling the creation of the most advanced designs; it appears to prioritize affordability over top-level functionality.

Pros and Cons

Pricing

• Free forever plan.
• S: €4.99 per month or €15.96 per quarter or €35.88 per year.
• M: €14.99 per month or €51.96 per quarter or €119.88 per year.
• L: €29.99 per month or €99.96 per quarter or €239.76 per year.
• XL: €69.99 per month or €239.96 per quarter or €599.88 per year.
• XXL: €149.99 per month or €519.96 per quarter or €1,199.88 per year.

Features

• Users can add multimedia, such as videos, images and audio.
• It supports push notifications and in-app purchases.
• Supports monetization via advertisement.
• Online store.
• Navigation bars.
• Ability to add Google Maps to your app.

Also see: Best Artificial Intelligence Software

Google AppSheet: Best for Advanced Features

AppSheet has enabled the creation of over 4.5 million apps by users worldwide. It uses AI technology to generate app features automatically, based on user requirements and customizations.

While AppSheet offers some automation and machine learning features, it is primarily focused on providing a no-code development environment that enables you to create apps that can understand and respond intelligently to user inputs. This ability to interact intelligently allows the platform to create many advanced features, like those that include interoperability.

Indeed, this AI app platform is very strong when it comes to interoperability: AppSheet apps can connect to hosted Excel files, Google Sheets, Google Drive, Cloud SQL, Apigee, Azure SQL, AWS, Salesforce objects, Smartsheet, and OData.

AppSheet naturally benefits from being owned by Google. The company’s extensive expertise in AI and vast resources should keep this AI app building platform well supported going forward.

Pros and Cons

Pricing

Unlimited-time free trial for up to 10 users.

• Starter: $5 per user per month.
• Core: $10 per user per month.
• Enterprise Standard: Custom quote.
• Enterprise Plus: Custom quote.

Features

• Duet AI for app creation.
• Manage users with role-based security, authentication, and usage reports.
• Capture rich data using forms, barcodes, locations, signatures, and photos.
• Send and automate email, SMS, and push notifications.
• Add machine learning models like intelligent document processing and OCR to your app.

Also see: Best AI Writing Tools

Zoho Creator: Best for Creating Business Intelligence and Analytics Apps

With Zoho Creator, users can create applications for various business purposes, such as data collection, workflow management, customer relationship management, and project management.

Zoho’s overall business strategy is based on an integrated suite of apps, in which every app is part of a connected ecosystem. Consequently, the AI app builder offers features like forms, reports, dashboards, workflows, and integrations with other Zoho apps and third-party services. Zoho Creator enables app deployment to various platforms, including web, mobile (iOS and Android), and tablets.

Ultimately, Zoho is geared for a business audience, and so its AI app building functionality includes the ability to create BI and data analytics apps. While this offers major potential, it also means that getting the most out of this AI app builder will require some training in data discovery and data analytics.

Pros and Cons

Pricing

Offers a 15-day free trial.

• Standard: $12 per user per month, billed month-to-month or $8 per user per month, billed annually.
• Professional: $30 per user per month, billed month-to-month or $20 per user per month, billed annually.
• Enterprise: $37 per user per month, billed month-to-month or $25 per user per month, billed annually.
• Flex: Custom quote.

Features

• AI-assisted migration tools.
• Data visualization using cross-functional analytics.
• Integration with 600+ third-party apps.
• Auto language translation.

Also see: Generative AI Companies: Top 12 Leaders

Mendix: Best for Building Complex Business Apps

If you want to create a simple mobile app or a complex enterprise-level application, Mendix positions itself as a one-stop solution that combines the power of low-code development with agile methodologies that can be used by the enterprise.

Mendix excels at enabling citizen and professional developers to collaborate and build applications quickly. It offers a full suite of low-code tools that enable fast and relatively easy assembly of AI apps with minimal coding skills.

Additionally, the platform offers upper level functionality. The platform stands out for its collaboration capability – each app lives in its own central project space with a wide variety of tools. The menu includes sophisticated tools for building collaboration, agile project management, backlog management, feedback management, and DevOps. Mendix use cases include applications for process automation and legacy modernization.

Pros and Cons

Pricing

• Free: Limited functionality, as your app will only run for a few hours before shutting down.
• Basic: Starts at €50 per month. 5 users included plus €10 per user per app per month.
• Standard: Starts at €800 per month. 5 users included plus €10 per user per app per month.
• Premium: Custom quote.

Features

• Enables you to collaborate with other developers using Git-based version control.
• Deploy to any cloud, on-premise environment, or edge device.
• Supports integrations with your existing data sources and services through various industry-standard protocols  — REST, SOAP, MQTT, JDBC, ODBC, BAPI, OPC, and OData.

On a related topic: ChatGPT: Understanding the ChatGPT ChatBot

Pico: Best for Small Business Owners

Pico is a GPT4-powered “text-to-app” platform developed by WhimsyWorks. It allows you to convert natural language into code, enabling the creation of web applications using just plain English text – so it’s the ultimate in ease of use.

The engine underneath Pico is ChatGPT-4, so this app builder is fully equipped to generate content based on a large language model. Plus the resulting apps can be built into any web site.

Pico excels in understanding and interpreting user input. This AI app builder aims to democratize web development and empower non-technical users to create their own applications. To support that goal, it offers enough functionality for a small business owner – you can build tools to streamline business operations or develop lead generation use cases. Yet the AI app builder’s simplicity means it can function well on a small business budget.

Pros and Cons

Pricing

• Try: Up to 4 apps (or 4 iterations total).
• Pro: $29 per month or $240 per year.
• Premium: $49 per month or $390 per year. Limited to 2,000 image generations per month.
• Business: $129 per month or $990 per year. 5,000 image generations per month.

For the Premium and Business tiers, additional images are billed at $0.80 per 100 images.

Features

• Private apps – you can add password protection to any app, so it’s only accessible to people you give access to.
• Pico supports the full app lifecycle, from prototyping, creation, iteration to launch and usage tracking.
• Offers up to 10 custom domains.

Softr: Best for Extensive Customization

Like many tools in the AI sector, Softr allows you to enter text prompts to generate an app – so you don’t need advanced technical skills to create relatively advanced apps. For instance, you can enter a prompt and it will generate the website copy as well as images for you.

You can customize your app in the Softr Studio – a visual interface and a drag-and-drop builder that allows you to create and design your applications easily by selecting elements, adding content, and customizing features.

Softr also offers various templates and integrations with other popular tools and services, making it a versatile platform for creating different types of applications, such as membership sites, directories, marketplaces, and job portals. Indeed, with the menu of options available, Softr enables a remarkable array of variation and customization.

Pros and Cons

Pricing

• Free: No cost for up to 5 internal and 100 external app users.
• Basic: $59 per month or $49 per month billed yearly. Support up to 5 collaborators.
• Professional: $167 per month or $139 per month billed yearly. Support up to 10 collaborators.
• Business: $323 per month or $269 per month billed yearly. Support up to 15 collaborators.
• Enterprise: Custom quote.

Features

• Supported data sources include Airtable, Google Sheets, and SmartSuite.
• Several data visualization options – Charts, Calendar, Inbox, Kanban, Calendar, and Org chart.
• Image, logo, favicon uploading, plus video embedding (Youtube, Vimeo).
• 100+ pre-built blocks.
• Custom form builder.

Bubble: Best for Creating Full-Stack Data-Driven Web Applications

Like many tools in this sector, Bubble enables you to create interactive, multi-user apps for desktop and mobile web browsers without coding. It offers a drag-and-drop interface and a wide range of pre-built templates and plugins, making it easy to build and customize your app.

In contrast with lighter weight AI app builders, Bubble also offers powerful backend capabilities, allowing you to store and retrieve data, send emails and integrate with external APIs. With Bubble, you can create anything from simple landing pages to complex web applications that include features like user authentication, payment processing, and automatic app text translation functionality.

In sum, Bubble offers a powerful combination of low code development with full-stack capability. While the casual user could enjoy building with Bubble, this AI app builder has the robust qualities of a true enterprise tool.

Pros and Cons

Pricing

• Free: Limited functionalities.
• Starter: $32 per month billed month-to-month or $29 per month billed annually.
• Growth: $134 per month billed month-to-month or $119 per month billed annually.
• Team: $399 per month billed month-to-month or $349 per month billed annually.
• Enterprise: Custom quote.

Features

• Apps come with a ready-made user management system.
• Bubble supports 80+ international languages.
• Version control and backups.
• Allows you to manage SEO by setting meta tags, customizing URL text and titles, and generating sitemaps.

How to Choose the Best Generative AI App Builder Software for Your Business

While many generative AI application builders on the market advertise themselves as the best app builder, the popular saying “not all that glitters is gold” holds true here: the market for AI app builders offers exceptionally wide variation in approach and capacity. That is why we carefully curated the list of top-tier tools for various user types and use cases.

Our analysis found that Zoho Creator and Mendix are the best options for creating complex business apps, while Softr and Pico are solid options for non-technical people, as they allow them to use natural language inputs to build AI-powered apps. Bubble is a top AI app builder for low code and full-stack development.

The best generative AI app builder for your business will depend on your specific requirements, target audience, and required features and capabilities – and the apps change rapidly, so be aware of that.

Frequently Asked Questions (FAQs)

We answered the most commonly asked questions to help you determine the best generative AI app builder for your company.

What is the best generative AI app builder?

There is no single best generative AI app builder, as the best option for you depends on your needs. Our list analyzed the top-rated generative AI application builders for different business categories. Ultimately, you may want to use (or at least try) several tools over a variety of work sessions to learn the sector and find your way to the best option.

Can a generative AI app builder replace human developers?

No, a generative AI app builder is not intended to replace human developers. It is designed to help non-technical and business users create apps without coding experience. In fact, a developer can create more advanced applications with these tools.

Are generative AI app builders suitable for all types of applications?

Generative AI app builders can be used for various applications, but their effectiveness may vary depending on the complexity and requirements of the specific app. As you’ve seen in the list above, some AI app builders are far more capable than others.

Bottom Line: Generative AI App Builders

Generative AI app builders are still emerging, and their capabilities and maturity vary enormously. Some app builders have advanced features and produce high-quality results, while others are still in the early stages and may have limitations. Researching and evaluating different tools is essential to find the AI app builder that aligns with your specific app development needs.

To gain a deeper understanding of the AI app sector, read our guide to Best AI Apps for Mobile

The post 8 Best Generative AI App Builders 2024 appeared first on eWEEK.

While there are hundreds of neural network software applications (free and paid), it can get overwhelming when shopping for the best option for your organization. We did the heavy lifting for you by selecting the best neural network software.

Here are our 10 top picks for the best neural network software — plus an additional 10 honorable mentions down below.

Top Neural Network Software: Comparison Chart

Here is a head-to-head summary of the best neural network software features and pricing.

Top Neural Network Software

Keras: Best for Rapid Prototyping

Keras is a high-level, open-source neural network library written in Python. It can run on top of other deep learning frameworks, such as TensorFlow, Theano or CNTK, giving you a simplified and intuitive API to define and run neural networks. ​​It supports various types of neural networks, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their combinations.

Pros and Cons

Pricing

Keras is a free, open-source tool.

Features

• Keras models can be deployed to run directly in the browser or TF Lite to enable it to run on iOS, Android and embedded devices.
• High-performance backend engines.
• Pre-trained models.
• Built-in data preprocessing utilities.

TensorFlow: Best for Production Deployment

Released in 2015, TensorFlow is an end-to-end framework for machine learning developed by Google to enable you to prepare data, build, and deploy ML models and implement MLOps. TensorFlow allows users to develop and deploy neural networks, perform numerical computations, and train models across different platforms. It is widely used for various applications, such as image recognition, natural language processing, computer vision, and reinforcement learning. The software is deployable on the web, mobile, edge, and servers.

Pros and Cons

Pricing

TensorFlow is free and open-source software.

Features

• While TensorFlow is primarily implemented in Python, it provides bindings for other languages, such as C++, Java, JavaScript, and Go.
• TensorFlow has a large and active community of researchers, developers, and data scientists.
• TensorFlow includes TensorBoard, a visualization tool that helps users understand, debug, and optimize the performance of their machine-learning models.
• Contains pre-trained models and datasets.

PyTorch: Best for Modularity and Quick Experimentation

Developed by Facebook’s AI Research (FAIR) group – now META AI – PyTorch is another popular open-source machine learning library for developing and training neural network-based deep learning models. Unlike frameworks like TensorFlow, which uses static computation graphs, it provides a dynamic computational framework, allowing artificial intelligence developers to define and run computational graphs on the fly, which makes it highly flexible and efficient for deep learning tasks.

Pros and Cons

Pricing

PyTorch is free to install and use.

Features

• PyTorch is compatible with major cloud services such as AWS, GCP, Alibaba Cloud, and Azure.
• It offers a rich set of libraries and tools, such as Captum, PyTorch Geometric, and skorch, to support your development process in NLP and computer vision.
• Dynamic computational graph.
• It’s well supported by major cloud platforms.

Apache MXNet: Best for Flexible Research Prototyping

​​Apache MXNet is an open-source project that provides a deep learning framework for training and deploying deep neural networks on various devices, from cloud infrastructure to mobile devices. One of the key features of MXNet is its dynamic computational graph, which allows for efficient memory usage and flexible model architectures. It also provides a wealth of pre-built neural network layers and algorithms, as well as support for popular deep learning frameworks such as Gluon, Keras, and TensorFlow.

Pros and Cons

Pricing

MXNet is a free, open-source tool.

Features

• Deep integration into Python and support for Scala, Julia, Clojure, Java, C++, R, and Perl.
• Supports various use cases, including computer vision, NLP, and time series.
• MXNet supports imperative programming using NDArray, making it useful for storing and transforming data, much like NumPy’s ndarray.
• Key-value store interface for efficient parameter synchronization.

Torch: Best for Researchers and Developers in the Academic and Research Community

Built on Lua is a lightweight and embeddable scripting language offering support for multiple programming methods, including procedural, object-oriented, functional, and data-driven programming. Torch is known for its speed and high-performance capabilities, making it popular among researchers and practitioners in the field of deep learning. It has a large community of developers contributing to its development and use.

Pros and Cons

Pricing

Torch is a free, open-source tool.

Features

• Numeric optimization routines.
• Embeddable, with ports to iOS and Android backends.
• Neural network and energy-based models.
• Offers routines for indexing, slicing, and transposing.

Weka: Best for Developing New Machine Learning Schemes

Weka (an acronym for Waikato Environment for Knowledge Analysis) is open-source software issued under the GNU General Public License. It provides a collection of algorithms, tools, and libraries for predictive modeling, data preprocessing, classification, regression, clustering, and visualization. The Weka software provides several neural network algorithms for training and testing neural network models, such as multilayer perceptron, radial basis function network, and RProp, among others.

Pros and Cons

Pricing

Weka is freely available under the GNU General Public License.

Features

• Integration capabilities.
• Data preprocessing capabilities.
• Visualization.
• Comprehensive algorithms.

Neural Designer: Best for GUI-Based Development

Neural Designer is commercial neural network software that uses artificial neural networks for data modeling and predictive analytics. It allows users to create, train, and deploy neural network models without the need for extensive knowledge of coding or machine learning algorithms.

Pros and Cons

Pricing

Neural Designer offers standard license and academic license.

Standard licenses

• Free trial: 15 days.
• Small: $2.495 per user per year or $6.245 per user for lifetime access.
• Medium: $4.995 per user per year or $12.495 per user for lifetime access.
• Large: $7.495 per user per year or $18.745 per user for lifetime access.

Academic licenses

• Research: $2.495 per user per year or $6.245 per user for lifetime access.
• Teaching: $4.995 per user per year or $12.495 per user for lifetime access.
• Campus: Quote available upon request.

Features

• GPU acceleration (NVIDIA CUDA).
• Multi-core parallelization (Intel MKL).
• Desktop (Windows, macOS, Linux).
• Cloud (AWS BYOL).

Chainer: Best for Small to Medium-Sized Projects

Chainer is a fully featured neural network software that allows for easy and intuitive definition of complex neural network models. Chainer is written in Python and can be used with popular libraries such as NumPy for numerical computations. It is designed to be efficient and scalable, making it suitable for both research and production environments.

Pros and Cons

Pricing

Available upon request.

Features

• It supports several network architectures, including recursive nets, convnets, feed-forward nets, and recurrent nets.
• Support NVIDIA cuTENSOR and CUB for better performance.
• Chainer has four extension libraries, including ChainerMN, ChainerRL, ChainerCV, and ChainerUI.

Caffe: Best for Image Classification and Computer Vision Tasks

Caffe was created by Yangqing Jia during his PhD at UC Berkeley. It’s a “deep learning framework made with expression, speed, and modularity in mind.” It allows researchers and developers to define, train, and deploy various types of deep learning models. Caffe gained popularity for its efficiency, scalability, and modularity, making it a popular choice in the field of computer vision.

Pros and Cons

Pricing

Caffe is released under the BSD 2-Clause license.

Features

• Caffe can process over 60M images per day with a single NVIDIA K40 GPU.
• Backed by a strong and active community of developers and researchers.
• Supports CPU and GPU computation.

Knet: Best for Dynamic Computation

Knet (pronounced “kay-net”) is a deep learning framework implemented in the Julia programming language. It provides a high-level interface for building and training deep neural networks. It aims to provide both flexibility and performance, allowing users to build and train neural networks on CPUs or GPUs efficiently.

Pros and Cons

Pricing

Knet is free, open-source software.

Features

• Integration with Julia.
• Knet machine images are available for AWS, Singularity, and Docker.
• Uses dynamic computational graphs.

Honourable Mentions

Aside from the neural network software mentioned above, below are other top neural network software worth mentioning.

• Merlin – Best for neural network-based speech synthesis.
• Clarifai – Ideal for computer vision-related tasks.
• TFLearn – Well-suited for quick TensorFlow model building.
• DeepPy – Good for Pythonic programming based on NumPy’s ndarray.
• Bitnami Pytorch – Best for GPU acceleration.
• ConvNetJS – Good for training deep learning models like neural networks in web browsers.
• Scikit-learn – Good for predictive data analysis.
• Neuroph – Best for training neural networks in Java programs.
• NeuroSolutions – Good for cluster analysis.
• Darknet – Best for deep computation and image classification.

Key Features of Neural Network Software

Integration with Hardware Accelerators

Compatibility with hardware accelerators (e.g., GPUs, TPUs) to speed up the training and inference processes. This is particularly important for large-scale neural network applications.

Comprehensive Documentation

Neural network software are highly technical and may require you to invest time and effort in understanding the concepts and functionalities.

Here are some documentation checklists to use:

• Installation guide.
• User guide.
• API documentation.
• Examples and tutorials.
• Troubleshooting guide.
• Support and community resources.

Data Handling and Preprocessing

Neural network software should have capabilities for pre-processing and engineering features from raw data. This includes tasks such as data normalization, outlier removal, and feature scaling.

Integration with Other Libraries and Frameworks

Neural network software should have the ability to integrate with other popular libraries and frameworks. This allows users to leverage the functionalities and resources provided by these libraries for tasks such as data manipulation, visualization, and parallel computing.

How to Choose the Best Neural Network Software for Your Business

When shopping for the best neural network software for your business, you must first evaluate your organization to assess your specific needs and the tasks you want to carry out with neural network software. Keep in mind that not all neural network software functions the same way; some may be easy to use but lack advanced features, while others may offer advanced features but have a steeper learning curve.

Our analysis found that Caffe is ideal for computer vision related tasks, while Keras is well-suited for prototyping. Those with limited computer programming knowledge may find Neural Designer beneficial. On the other hand, Chainer is a good option for running small to medium-sized projects.

Be sure to research available software and consider factors such as ease of use, flexibility, scalability, available resources (documentation, community support, tutorials), and compatibility with your existing technology stack before settling for a particular neural network tool. Though neural network software usually supports multiple programming languages such as Python, R, and C++, consider the programming language native to your organization and choose software that offers strong support for that language.

Frequently Asked Questions (FAQs)

We answered the most commonly asked questions about neural network software.

What is the best neural network software?

The best neural network for your business is the one that offers the features, capabilities, and functionalities you need. Our top picks offer extensive community support, active development, and good performance across various tasks.

What are the common applications of neural network software?

Neural network software has a wide range of applications, including:

• Image and speech recognition.
• Natural language processing.
• Sentiment analysis.
• Financial analysis.
• Fraud detection.
• Recommendation systems.

Can neural network software run on a regular computer?

Yes, neural network software can run on regular computers, but the performance may vary depending on the network’s complexity and the size of the dataset.

Bottom Line: Best Neural Network Software

As stated earlier in this article, the best neural network software for your enterprise depends on your specific requirements and tasks. Some software may specialize in image recognition, while others may be more suitable for natural language processing or time series analysis. Hence, choosing a tool that aligns with your business objectives is important.

Read next: Best Artificial Intelligence Software

The post 20 Best Neural Network Software for 2024 appeared first on eWEEK.

Generative AI can support staffers in managing their existing task loads and, in some cases, these models can be trained to take on entirely new tasks and types of work. In all of these cases, generative AI is helping businesses streamline and automate their processes in repeatable and scalable ways that contribute to business growth goals.

Depending on your business priorities and requirements, generative AI can support your operations in a variety of ways. Read on to learn some of the most common ways generative AI is used to improve businesses today. Also important, learn about generative AI usage best practices that will help you achieve new levels of business success.

Table of Contents: How Generative AI Can Support Business Operations

• Top 7 Ways to Use Generative AI in Your Company
• 5 Benefits of Leveraging Generative AI in Your Business
• 5 Challenges of Using Generative AI
• What Are Generative AI Best Practices for Business Usage?
• Learning About Generative AI
• Bottom Line: How to Use Generative AI in Your Business

Top 7 Ways to Use Generative AI in Your Company

Generative AI models are being used for a variety of industry-specific enterprise use cases that range from simple customer service support and coaching to more complex tasks like medical imaging and drug discovery.

But generative AI can also be trained to handle more generic business tasks that are relevant to all businesses, regardless of industry or size. Below are seven of the most useful ways business leaders can incorporate generative AI into their business today:

1) Smart, Secure Data Analytics

Generative-AI-powered data analytics solutions make data analysis smarter, speedier, more scalable, and more secure. Depending on the model type and size you select, you can use generative AI to generate synthetic data for more secure and compliant data analysis and QA testing practices.

You can also use generative AI to democratize data analytics in two important ways:

• Generative AI models allow users to create narrative explanations of their data, making it easier for non-data scientists to understand the data they have in front of them.
• Generative AI assistants are being embedded and used in common data tools like Power BI, which enables less technical users to comprehend complex datasets and create accurate data visualizations and reports.

Example solutions: SparkBeyond Discovery, Dremio, Narrative BI, Power BI Copilot

2) Customer Service and User Experience

Most businesses have a customer service component that could be improved with more consistent training and customer-first communication and designs.

A variety of generative AI tools are springing up to mentor your existing customer service agents and, in some cases, replace them with chatbot, voice generation technology, and AI-powered search engines that are designed with customer queries and natural language requirements in mind.

In more specialized industries, like insurance, generative AI can also be used to better assess risk and achieve optimal outcomes for customers’ plan rates and claims.

Example solutions: Gridspace, IBM Watson Assistant, UltimateGPT, Zendesk Advanced AI, Forethought SupportGPT

3) Assistive Coding and Product Design

Regardless of your tech teams’ levels of expertise, generative AI can be incorporated to support coding and quality assurance tests for digital product design. Generative AI models like ChatGPT can fix bugs, generate test code, and write documentation for programs.

Perhaps most significant, generative AI models can help developers of all skill levels solve problems; even non-technical team players can generate code through natural language queries.

Example solutions: Code Snippets AI, ChatGPT, Google Bard, Tabnine, MOSTLY AI, Stability AI

4) Content Creation

Generative AI models have already proven their ability to quickly generate natural language content affordably and at scale, which has made these models particularly enticing for organizations that want to outsource content writing.

Several generative AI tools are able to write blog and social media content based on simple prompts. Others are designed to create more specific content, like legal documents or marketing materials. However, the area of generative AI content generation that is growing most quickly is multimedia content, with AI models used to create content like marketing videos with AI-generated voices and avatars.

Example solutions: Jasper, Notion AI, Phrasee, HubSpot Content Assistant

5) Document Summarization

A simple but effective way to use generative AI in your business is to summarize long and complex documents.

This can be a quick and easy way to identify the most important points in a long contract, legal document, conversation transcript, or other long-form content type. While some generative AI tools are standalone content summarization tools, others are embedded in everyday business operations and project management tools.

For example, Notion AI is a feature that enables Notion users to quickly summarize project notes and sales call transcripts.

Example solutions: Cohere Summarize, Anthropic Claude, PatentPal, AI21 Studio

6) Project and Workflow Management

Several of the most popular project management platforms have or are currently adding generative AI assistive capabilities to their features lists. These assistants can help with administrative tasks like note-taking during meetings, email writing, and document summarization, freeing up time for your employees to focus on more strategic tasks.

At a more technical level, these AI assistants can also automate and optimize workflow builds, make task suggestions, and support data integration efforts.

Example solutions: Process Street, Wrike, Notion AI, ClickUp, Asana

7) Cybersecurity Management

Although generative AI can pose major risks to cybersecurity postures, these AI tools are also valuable for automating business cybersecurity management workflows and handling data security requirements.

Some of the most common ways businesses are taking advantage of generative AI in cybersecurity include through smarter threat intelligence and hunting, contextualized security environment recommendations, and attack simulations. Some of these new generative AI security tools are freestanding products, but many of them are either new features or add-on products for existing cybersecurity platforms.

Example solutions: Google Cloud Security AI Workbench, Microsoft Security Copilot, CrowdStrike Charlotte AI, Airgap Networks ThreatGPT

Also see: Top Generative AI Apps and Tools

5 Benefits of Leveraging Generative AI in Your Business

Depending on how (and how much) you choose to leverage AI capabilities in your organization, expect the following generative AI benefits from your efforts:

• Quicker delivery times on projects: Generative AI models can quickly generate responses, new content, useful data, and other value your organization may need at scale. This leads to more efficient production and allows your team to complete projects on tighter timelines, which is ultimately more cost-effective.
• Fewer hands-on employee requirements: Whether you lack the in-house staff expertise to complete a certain task or find that certain tasks are too tedious to hold employee attention, generative AI tools can pick up the slack and deliver consistent, accurate, and repeatable results.
• Support and QA for employee-driven tasks: Particularly with coding and product development tasks, but also with data analytics and other content forms, generative AI tools can act as quality assurance analysts, checking employee work for errors and sometimes correcting those errors without human intervention.
• Enhanced user experiences: Many generative AI tools are embedded in software that your employees or customers already use. With the help of generative AI, search engines, enterprise knowledge bases, project management platforms, and other user-facing tools are optimized for natural language inputs and an overall better user experience.
• Industry-specific solutions: Several generative AI models have been fine-tuned to address industry- and function-specific requirements across sectors like healthcare and pharmaceuticals, insurance, manufacturing, and more. If you’re operating in a specialized industry — even with strict compliance requirements — there’s more than likely a generative AI model that will address your needs and simplify your workflow.

Also see: Best Artificial Intelligence Software

5 Challenges of Using Generative AI

Many risks come with using generative AI, and especially because this technology is still so new, not all ethical use dilemmas have been worked out. If you choose to use generative AI in your business, be on the lookout for these possible challenges you’ll face:

• Limited regulatory requirements and guidance: Generative AI is not currently regulated on a larger scale, and at this time, there are few comprehensive usage frameworks that cover how your organization can use generative AI compliantly and effectively.
• Lack of data and training transparency: Although many generative AI vendors are beginning to improve in this area, most are still not transparent with the types and sources of the training data they use, which leads to additional compliance and usage concerns.
• Cybersecurity concerns: In the wrong hands or in the hands of an ill-trained employee, sensitive data may be exposed to generative models and become part of the training set. Bad-faith actors can also train these models to work around their rules to complete unauthorized tasks.
• Identifying inaccurate outputs: Generative AI models use natural language so well that it’s sometimes difficult to determine if a model has generated an inaccurate response. Users will need to have the skills and nuanced knowledge to check their own work when using this type of technology.
• Employee usage errors: It’s difficult to regulate and control how employees use generative AI in their work. Coming up with an AI use policy is a good step toward mitigating these errors, but there’s still no consistent way to enforce usage rules, control what data employees use as inputs, or monitor multiple employees’ actions at once.

Also read: Generative AI’s Drawbacks: IP to Ethics

What Are Generative AI Best Practices for Business Usage?

Establishing best practices and procedures for generative AI use is the best way to manage internal business use of these models. Follow these best practices for better generative AI outcomes in your business:

• Use data from verified, credible, and approved sources as inputs.
• Develop an AI use policy and training plan that clearly outlines how and when employees can use generative AI tools.
• Partner with a generative AI vendor building models that can scale or be fine-tuned as your business requirements evolve; it’s also beneficial to identify vendors with products that integrate with your existing tool stack.
• Do your due diligence and research generative AI vendors’ policies, terms, and reputations before committing.
• Consider your budget and what tools fit into that budget; many foundation models are not that expensive but can quickly go up in price depending on your usage volume.
• Consider any generative AI models you use as part of your cybersecurity threat landscape and protect accordingly.

For more on this topic, read these comprehensive guides:

• Risks of Generative AI: 6 Risk Management Tips
• Generative AI Ethics: Concerns and Solutions
• Generative AI and Data Analytics: Best Practices

Learning About Generative AI

Generative AI is revolutionizing industries like art, gaming, music, and even healthcare — acquiring knowledge about this technology can therefore be very valuable. The importance of learning about generative AI stems from its transformative impact on fields such as computer vision, natural language processing, and creative arts.

For instance, in the domain of image synthesis, generative adversarial networks (GANs) have enabled the creation of realistic images, transforming industries like graphic design, gaming, and even medical imaging. In natural language processing, large language models using generative techniques have pushed the boundaries of what AI can achieve in tasks like text completion, translation, and summarization.

Taking classes and pursuing education on generative AI is an effective way to understand these technologies comprehensively. Many reputable massive open online courses (MOOCs) platforms offer courses taught by experts in the field, allowing you to learn at your own pace. These courses often provide hands-on projects, real-world applications, and opportunities to interact with a global community of learners, fostering a dynamic and collaborative learning environment.

As industries continue to adopt generative AI solutions, professionals well-versed in this technology will be in high demand. Whether you’re a software developer, data scientist, designer, or business professional, incorporating generative AI knowledge into your skill set can open up new career opportunities and make you a valuable asset to your organization.

Bottom Line: Generative AI in Your Business

Generative AI technology is a powerful resource that can be leveraged in businesses of all sizes and backgrounds, especially since so many models come in affordable limited versions that still have extensive capabilities.

The most important thing to remember when using generative AI in your business is that these tools are only as effective as the users, inputs, and procedures that surround them. Make sure all employees are trained and given the resources they need to use generative AI in their work effectively, and you’ll achieve new levels of automation, smart assistance, and productivity in your organization.

Read next: ChatGPT Enterprise: AI for Business

The post Generative AI for Business: Top 7 Productivity Boosts appeared first on eWEEK.

• Text-to-3D models: The AI text-to-3D model allows you to generate 3D models from text descriptions. This is useful in fields like architecture, design, or gaming.
• Image-to-3D models: This technique allows the AI system to convert a 2D image into a fully realized 3D model. Professionals in industries like computer vision, virtual reality, and entertainment favor this method.
• Video-to-3D models: Commonly used in areas such as robotics, autonomous vehicles, and augmented reality — the video-to-3D generators can create a 3D model from the video you upload into the system.

We reviewed the best AI 3D generators across various categories, including texts, images and videos. We analyzed each tool’s pricing, key features and capabilities, as well as their pros and cons, to help you determine the best solution for your needs.

• Meshcapade: Best for e-commerce ready models
• Masterpiece X: Best for ease of use
• NeROIC: Best for capturing high-quality geometry and appearance properties
• DPT Depth: Best for 3D scene reconstruction in real-time
• Ponzu: Best for developers and designers
• Spline: Best for collaboration and team projects
• 3DFY AI: Best for gaming and architecture
• Sloyd: Best for customization
• DeepMotion: Best for full-body marker tracking
• Rokoko Vision: Best for real-time full-body motion capture

Best AI 3D generators: Comparison chart

Here is a feature summary of the top-tier AI 3D generators.

Please note: all rating are based on a scale of 1 to 5, with 5 being the best. 

Meshcapade: Best for generating e-commerce ready models

Overall rating: 2.80

• Cost: 2.0
• Feature set: 4.5
• Ease of use: 2.0
• Quality of output: 2.5
• Support: 2.0

Meshcapade is a 3D generator tool that uses advanced algorithms to generate 3D models based on user inputs and preferences. Meshcapade uses a skinned multi-person linear model (SMPL) to power its creation tool, allowing you to recreate the human body in detail. The platform can create realistic 3D avatars of humans from various data sources, including photos, videos, body measurements, 3D scans, motion capture and text.

The generated 3D models – which use artificial intelligence – can be used for various purposes like virtual reality, video games, 3D printing, and architectural visualization.

Pros and cons

Pricing

Pricing for this tool varied based on the package and features chosen. A free 30-day trial license is also available for some models. To give you an idea of how much this product costs, we will list some of its pricing offerings.

Meshcapade Body Models (SMPL)

The Meshcapade avatar tech product line starts at €600 per year for the R&D plans, while the commercial use plans start at €2,000 per year. Keep in mind that your actual price may vary based on your needs.

Features

• Compatible with game engines and graphics applications.
• SMPL is compatible with deep learning architectures.
• Ability to generate e-commerce ready models.

Also see: Top Generative AI Apps and Tools

Masterpiece X: Best for ease of use

Overall rating: 4.3

• Cost: 5.0
• Feature set: 4.5
• Ease of use: 5.0
• Quality of output: 2.5
• Support: 3.0

Masterpiece X is an AI text-to-3D generator that enables you to create assets with mesh, textures, and animations. Masterpiece is a straightforward and user-friendly tool designed to make 3D asset creation accessible to everyone, regardless of their level of expertise. With Masterpiece, you can simply describe the object or scene you have in mind using natural language, and the AI will generate a 3D model based on your description. You can specify details such as the shape, size, colors, textures, and even the desired animations.

Masterpiece assets are compatible with industry-standard game engines and popular apps like: Unity, Unreal Engine and Blender.

To use this tool, select a model type (object, animal or human), add shape details, as well as color details, choose your animation details and click on generate 3D models.

Pros and cons

Pricing

When you sign up to use Masterpiece, they give you 250 credits for free. If you need more credits, subscribe to their paid plan. Masterpiece offers on-demand credit packs as well as month-to-month plans. The on-demand credit packs start at $14.99 for 750 credits. The monthly plans are as follows.

• 750 credits: $10.99 per month.
• 1500 credits: $19.99 per month.
• 3000 credits: $36.99 per month.

Features

• Functional 3-D models and animation generation.
• Natural language processing technology.
• Export your creation to .GLB format.
• Its storage capability allows you to upload and store files to your private assets.
• Supported file types include FBX, OBJ, STL, GLB and GLTF.

NeROIC: Best for capturing high-quality geometry and appearance properties

Overall rating: 3.25

• Cost: 5.0
• Feature set: 3.25
• Ease of use: 3.5
• Quality of output: 2.5
• Support: 1.0

NeROIC (Neural Rendering of Objects from Online Image Collections) is an AI-based technology that can generate 3D models from 2D images. It can also create a 3D scene from a video. NeROIC’s model uses images of objects taken under different conditions and improves the accuracy of these images by optimizing the geometry of scanned objects and adjusting the camera angles.

Pros and cons

Pricing

Free to use.

Features

• Image-to-3D and video-to-3D.
• It solves the material properties (including Albedo, Specularity and Roughness maps) and surface normal of the captured object.

Also see: Generative AI Companies: Top 12 Leaders 

DPT Depth Estimation: Best for 3D scene reconstruction in real-time

Overall rating: 2.15

• Cost: 5.0
• Feature set: 1.75
• Ease of use: 2.0
• Quality of output: 1.25
• Support: 0

DPT Depth Estimation is an image-to-3D generator that uses deep convolutional network architecture to estimate the depth map of an input image. It captures the depth of an image and then uses 3D Point Cloud to create a 3D object with high accuracy, allowing you to perform tasks such as 3D mesh reconstruction.

Pros and cons

Pricing

You can upload an input image for free and receive predicted depth and 3D mesh reconstruction results. Though Hugging Face allows you to demo the DPT Depth Estimation model for free, they also have a pricing plan that gives you access to a wide range of AI models and features.

• HF Hub: Free forever.
• Pro Account: $9 per month.
• Enterprise Hub: $20 per user per month.
• Spaces Hardware: $0.05 per hour.
• Inference Endpoints: $0.06 per hour

Features

• Uses a deep convolutional network.
• 3D Point Cloud generation.
• Support real-time 3D scene reconstruction.

Ponzu: Best for developers and designers

Overall rating: 3.25

• Cost: 5.0
• Feature set: 2.4
• Ease of use: 2.0
• Quality of output: 2.0
• Support: 4.0

Ponzu is an easy-to-use AI texture generator that creates high-quality 3D models for various applications. Ponzu has an intuitive user interface; the first thing you will see when you launch the website is a text box where you can input your prompt for the texture you want to generate.

Below the text box is a drop-down with 10 texture options, including photorealistic, art nouveau, toon and cyberpunk. Ponzu is particularly useful for game developers, visual effects artists, architects, and designers who need realistic and diverse textures for their projects.

Pros and cons

Pricing

Ponzu is free to use.

Features

• AI texture generation.
• Users can further customize the generated textures by adjusting parameters like ambient and directional light, metalness, reflectivity and roughness.
• It allows you to adjust the specular and diffuse lighting based on your needs.

Also see: Generative AI Examples

Spline: Best for collaboration and team projects

Image: Spline

Overall rating: 3.93

• Cost: 1.0
• Feature set: 3.75
• Ease of use: 5.0
• Quality of output: 2.5
• Support: 2.0

Spline is a web-based 3D AI art generator that allows you to create 3D text, interactive 3D experience, 3D mockups, game controls and physics, as well as 3D character design. Spine enables you to create 3D objects and provides features to edit the materials of these objects, add interactivity, such as animations, and export them in various formats.

Spline is big on collaboration, allowing you to work with your team in real time and set individual permissions.

Pros and cons

Pricing

• Basic: Free for one team project, up to two team files and two editors per team and personal file.
• Super: $7 per month, billed annually, or $9 per month, billed per month.
• Super team: $9 per editor per month, billed annually, or $12 per month, billed monthly.

Features

• Generate textures with AI.
• Import videos and create video layers and video events.
• Image, Video, and 3D Exports.
• Export your design as an image (JPG/PNG), video file (MP4/GIF), or 3D export (GLTF/USDZ).
• 3D modeling and animation.

And: ChatGPT vs. Google Bard

3DFY AI: Best for gaming and architecture

Overall rating: 3.60

• Cost: 3.0
• Feature set: 4.5
• Ease of use: 5.0
• Quality of output: 2.5
• Support: 1.0

The main objective of 3DFY AI is to eliminate the need for human labor in developing 3D content through automation, allowing you to generate high-quality 3D models faster and more efficiently. 3DFY AI has eight categories, including lamps, sofas, tables, ottomans, cutlery, swords, shields, and axes. To create a 3D model, select a category and enter your prompt in the text box; 3DFY AI will generate a 3D model based on your input.

Pros and cons

Pricing

3DFY.ai pricing uses a credit system and has two types of credits: Generation credits and download credits.

• Generation credits allow you to generate one 3D model per prompt.
• Download credits enable you to download one 3D model.

When you sign up on 3DFY.ai, you will receive 10 free credits to generate 3D models, but you’ll have to buy credits to download a model.

With 3DFY.ai, you can either choose to buy models and only pay for the number of credits you need one time or subscribe to a month-to-month or annual model.

The pay-per-need basis model has a $5 flat rate per model download. This means that one download, 10 generations, will cost you $5, while two downloads, 20 generations, will cost you $20.

For the subscription plan:

• 5 downloads and 30 generations cost $15 per month when billed annually or $20 per month when billed monthly.
• 40 downloads and 400 generations cost $80 per month when billed annually or $110 per month when billed monthly. For the month-to-month plan, your generation credits will be reduced to 250 per month, not 400.
• 100 downloads and 700 generations cost $175 per month when billed annually or $225 per month when billed monthly.

Features

• Supported file formats include .glb, .fbx, or .blend format.
• AI-powered text-to-3D generation.
• Adjustable texture and mesh quality.

Sloyd: Best for customization

Overall rating: 3.66

• Cost: 5.0
• Feature set: 2.4
• Ease of use: 5.0
• Quality of output: 2.5
• Support: 3.0

Sloyd is a 3D modeling platform that allows you to create props, weapons, collectibles, and architectural assets. To use this tool, select from the available category or enter a prompt in the text box. Currently, Sloyd doesn’t support creating people, animals, cars, and scenes 3D models. Sloyd is primarily focused on creating objects rather than complex scenes or living creatures and is favored by game developers, architects, and artists.

Pros and cons

Pricing

Sloyd is a free tool.

Features

• Extensive library of generators.
• The models are UV-deployed and optimized for real-time use.
• Sloyd also has an SDK for real-time generation within game engines.

DeepMotion: Best for full-body marker tracking

Image: DeepMotion

Overall rating: 3.43

• Cost: 5.0
• Feature set: 3.0
• Ease of use: 5.0
• Quality of output: 1.25
• Support: 1.0

DeepMotion is a video-to-3D generator that allows you to create dynamic and realistic physics-based animations. The platform enables you to make and simulate lifelike and interactive character animations, including full-body motion capture and simulation of physical interactions.

Pros and cons

Pricing

• Free: No charge for up to 60 credits per month.
• Starter: $9 per month, paid annually or $15 month-to-month. Up to 180 credits per month.
• Innovator: $17 per month, paid annually or $48 month-to-month. Up to 480 credits per month.
• Professional: $39 per month, paid annually or $117 month-to-month. Up to 1500 credits per month.
• Studio: $83 per month, paid annually or $300 month-to-month. Unlimited credits per month.

Features

• Support multiple output formats, including fbx, bvh, glb, dmpe, mp4, jpg, png and gif.
• Track basic facial expressions and hand gestures.
• Full body marker tracking, which includes face tracking, hand tracking and multi-person tracking.
• Foot locking capability.

Rokoko Vision: Best for real-time full-body motion capture

Overall rating: 3.80

• Cost: 5.0
• Feature set: 4.5
• Ease of use: 2.0
• Quality of output: 5.0
• Support: 3.0

Rokoko Vision is a video-to-3D AI generator. Rokoko is a technology company that specializes in motion capture technology. They have developed a range of products and software solutions for motion capture, including the SmartSuit Pro II, a full-body motion capture suit that captures your body’s motion and streams the data over WiFi in real-time to your digital characters.

Rokoko has a free version – Rokoko Vision – that allows beginner creators and enthusiasts to record and preview their motion capture data, as well as manage and export the captured animations.

Pros and cons

Pricing

Rokoko Vision is available in free (Single-cam) and paid (Dual-cam) versions. The Single-cam is completely free to use, while the Dual-cam offers a 14-day free trial, then $240 per year afterward.

Rokoko pricing plans:

• Starter: Free forever for indie creators.
• Plus: For small studios. The annual commitment costs $20 per month, while the month-to-month commitment costs $25.
• Pro: For medium sized teams. The annual commitment costs $50 per month, while the month-to-month commitment costs $60.
• Pro: For large enterprises. Custom quote.

Features

• Users can export files to .FBX or .BVH.
• Integration with popular animation software such as Unity, Unreal Engine, Autodesk Maya, and Blender.
• Full-body motion capture.
• You can import and retarget custom characters.

Key features of best AI 3D generators

Compatibility with various file formats

Integration with industry-standard file formats (such as OBJ, FBX, or GLTF) is important for seamless collaboration with other 3D modeling and rendering tools. This ensures that generated models can be easily imported and used in various workflows.

Speed and efficiency

Generating 3D models can be a computationally intensive task. Therefore, the AI 3D generator you choose should have optimized algorithms and efficient processing capabilities to produce results quickly.

Realistic rendering

When shopping for AI 3D generator for your organization, look for a tool that can produce highly realistic and detailed 3D models. This includes accurate lighting, shadows, textures, and overall visual appearance. This is essential for creating lifelike and visually appealing virtual environments.

Customizability

The ability to customize and fine-tune generated 3D models is a valuable feature. You should be able to adjust various parameters and properties to achieve the desired output.

How to choose the best AI 3D generator for your business

Realize that all AI 3D generators do not function the same way, and the best option for you and your business depends on your needs and preferences. Some companies may need a text-to-3D generator, while image-to-3D or video-to-3D generators may be more relevant for others.

Even when you know the type of 3D generator you need, you must ensure that the tool you choose offers your desired features and capabilities. For instance, Meshcapade and Sloyd are both text-to-3D generators. However, Meshcapade can generate human assets while Sloyd is incapable of doing that; Sloyd’s strengths lie in generating objects like weapons, collectibles and architectural assets.

To select the best AI 3D generator for your organization, you must first define business needs — compare your needs with the offerings of various AI 3D software providers and determine which aligns most with your requirements.

How we evaluated the best AI 3D generators

To write this review, we analyzed the best AI 3D generators based on five key day points, including cost, feature set, ease of use, quality of output and support. We collected primary product data from the vendors’ websites, including information on pricing, features and customer support. Where possible, we conducted hands-on testing of each generator to evaluate their performance.

Cost – 20%

We evaluated each AI 3D generator pricing structure. We checked for the availability of a free trial or free forever plan to enable us to test the platform. We ranked each vendor based on their availability of free trial, low cost subscription and pricing visibility.

Feature set – 30%

The feature set carried the most weight – 30%. We assessed the range of features offered by each AI 3D generator. We considered who the solution caters to, whether for professional users or beginners. We also checked for the availability of real time collaboration feature, access to library/database of digital content and motion capture technology. We ranked each vendor based on the comprehensiveness of their feature set.

Ease of use – 25%

We assessed the user interface and user experience of each AI 3D generator. We considered how easy it was to navigate and understand the platform.

We also analyzed users’ feedback on reputable review sites to learn about current and past users’ experiences with the tools. This information enabled us to gauge each tool’s strengths and weaknesses, quality of support and the overall usability of the product.

Quality of output – 10%

We also assessed the quality of the output generated by each AI 3D generator. In addition to our evaluation of the level of detail, accuracy and precision in the 3D models produced, we looked at factors such as the ability to generate fully functional 3D models and also checked if the tool renders a live video stream.

Support – 15%

We looked at the level of customer support provided by each AI 3D generator vendor. We considered factors such as the availability of customer support channels (e.g., live chat, email, phone), response times, and overall customer satisfaction with the support received. The availability of tutorials or documentation to help users navigate and utilize the software was also a major point of consideration.

Frequently Asked Questions (FAQs)

Is the AI generator free?

Most AI generator offer a free plan. Nine out of the ten tools we reviewed offers a free plan.

What is the best AI 3D generator available?

There is no one size-fits-all in when it comes to selecting the best AI 3D generator. The best one for you will depend on factors unique to you such as your organization size, and the type of file you want to create a 3D model for. That said, the above list include the best AI 3D generator for various users and use cases.

How to make 3D design with AI?

You can create your 3D designing by typing a text prompt or uploading and image or video to the AI 3D generator.

Bottom Line: Best AI 3D Generators

Before AI 3D generators became commonplace, those looking to create 3D designs had to use 3D software like Autodesk Maya, Blender or Adobe Substance 3D Designer to create the 3D models. Unlike AI 3D generators, not everyone can use traditional 3D software, as it requires specialized knowledge. AI 3D generators are revolutionizing and democratizing access to 3D designs by allowing anyone, regardless of their technical skills, to create stunning 3D designs with ease.

Whether you are a business professional, tech enthusiast, game developer, graphic designer, or just an interested party, AI 3D generators can help you create 3D designs in a fraction of the time and effort compared to traditional methods.

Read next: The Benefits of Generative AI

The post 10 Best AI 3D Generators 2023 appeared first on eWEEK.

We analyzed the best AI meeting assistant tools to help you determine the best virtual assistant for your business. We evaluated their features, pricing, pros and cons, as well as what user persona each of these various AI assistant apps are best suited.

Best AI Meeting Assistants: Comparison chart

Here is a head-to-head comparison of the best AI meeting assistants.

Top 10 AI Meeting Assistants

Fireflies.ai: Best for advanced features

The Fireflies.ai AI-powered meeting assistant helps you to transcribe, summarize, search, analyze, and complete actions during virtual meetings.

Fireflies joins your virtual meeting and takes note of the entire meeting, allowing you to read or listen to your meeting’s discussion anytime. The tool benefits sales and marketing teams, and recruiters can use it to communicate and collaborate for better candidate screening. You can also use Fireflies.ai to generate transcripts and subtitles for your podcast, video and audio.

Pricing

• Free: Available at no charge for up to 800 mins of storage per seat.
• Pro: $10 per user per month billed annually, while the month-to-month plan costs $18 per user.
• Business: $19 per user per month billed annually, while the month-to-month plan costs $29 per user.
• Enterprise: Custom quote.

Features

• It integrates with over 40 tools across 10 categories, including video conferencing, audio recording, CRM, project management and note-taking.
• Meeting audio playback speed (1x, 1.25x, 1.5x, 1.75x, 2x).
• Video screen capture capability.
• Collaboration capabilities.

Pros

• Unlimited storage for business and enterprise plan users.
• You can record using the Chrome extension without the Fireflies bot.
• Analytics and insights capabilities.

Cons

• Priority support is limited to enterprise plan users.
• The free plan cannot download transcripts and recordings.

Also see: Best AI Writing Tools

Fathom: Best free AI meeting assistant

Fathom advertises itself as a free AI meeting assistant tool. The tool allows you to record, transcribe, highlight, and summarize your meetings with no usage limitations at no cost, allowing you to record as many calls as you like.

Fathom works with Zoom, Microsoft Teams and Google Meet. The company also offers team editions that are paid plans.

Pricing

Both standard and pro require a minimum of three users. Fathom also offers a 14-day free trial for the paid plans.

• Free edition: Ideal for personal use.
• Standard: $24 per user per month, billed annually or $32 per user per month, billed monthly.
• Pro: $29 per user per month, billed annually or $39 per user per month, billed monthly.

Features

• CRM Sync (HubSpot, Salesforce and Close).
• Okta SSO / SCIM Integration
• Searchable repository for calls.
• Offers a unified view of all conversations with a customer or prospect.
• Keyword alerts.

Pros

• Generous free plan.
• Automatic summaries.
• Transcription and note-taking.
• Supports up to 7 languages, including English, Spanish and French.

Cons

• The note-taking app capability can be improved.
• The integration with Zoom can be improved.

Also see: Top Generative AI Apps and Tools

Avoma: Best for conversation analysis and insights

Avoma is an end-to-end AI meeting assistant, conversation intelligence and revenue intelligence tool that allows individuals and teams to capture, transcribe, analyze, and collaborate on meetings and sales calls.

Avoma automatically transcribes audio and video recordings of meetings and generates searchable meeting notes. It provides meeting participants with transcripts and AI notes to help them focus on the conversation and helps business leaders learn critical insights to enable them to make data-driven decisions.

Pricing

Paid plans offer a 14-day free trial, except Enterprise.

• Basic: Free for up to five meetings per month.
• Starter: $19 per user per month, billed annually or $24 per user per month, billed monthly. Includes 20 meetings per month.
• Plus: $49 per user per month, billed annually or $59 per user per month, billed monthly. Includes unlimited meetings per month.
• Business: $79 per user per month, billed annually.
• Enterprise: $149 per user per month, billed annually.

Features

• Scheduling capabilities, including access scheduling, group scheduling and more.
• Meeting recording.
• Upload pre-recorded audio or video files.
• Transcription and AI notes.
• Integrations with CRM, video conferencing and dialer tools.

Pros

• Collaboration capability.
• Keyword search alerts.
• AI scorecards and auto scoring.
• Speaker identification.

Cons

• Business and Enterprise plans lack month-to-month pricing.
• According to Avoma users, playback speed over 1x can sometimes skip words.

Also see: AI Detector Tools

Sembly: Best for creating comprehensive meeting summaries and minutes

Sembly is an end-to-end meeting assistant that transcribes, takes meeting notes, and generates insights for your professional meetings. By syncing Sembly with your Outlook or Google calendar, you permit it to automatically join all your calls without downloading or installing any software.

Sembly’s AI identifies key items in the discussion, such as actions, decisions, issues, risks, events and requirements. This helps you easily review the critical points discussed during the meeting.

Pricing

Sembly allows you to try the paid plans for free for 7 days.

• Personal: Free for a 4-hour record limit and 1-hour monthly upload limit. It’s limited to 1 member.
• Professional: $10 per user per month, billed annually or $15 per user per month, billed monthly and is limited to 1 member.
• Team: $20 per user per month, billed annually or $29 per user per month, billed monthly and limited to 40 members.
• Enterprise: Custom quotes. Unlimited member.

Features

• Integrations with task management and CRM tools such as HubSpot, Pipedrive and Zapier.
• Record and transcribe capabilities.
• Voice identification capability.

Pros

• Multi-language meeting notes (40+ languages).
• Proxy meeting attendance.
• Offers meeting notes with AI summary.

Cons

• The professional plan is limited to one workspace member.
• Live demos and webinars are only available to team and enterprise plan users.

Also see: Best Artificial Intelligence Software 2023

OtterPilot: Best for transcription

OtterPilot is an AI-powered meeting assistant that provides transcription and collaboration features. The service can be used for various purposes, including transcribing interviews, meetings, lectures, and podcasts.

When you connect OtterPilot to your Google or Outlook calendars, it will automatically join your Zoom, Microsoft Teams, and Google Meet meetings. Otter.ai is widely used by individuals, teams, businesses, and educational institutions.

Pricing

• Basic: Free for up to 300 monthly transcription minutes.
• Pro: $10 per user per month, billed annually or $16.99 per user per month, billed monthly.
• Business: $20 per user per month, billed annually or $35 per user per month, billed monthly.
• Enterprise: Available upon request.

Features

• Automatic transcription.
• Automatic sync of audio/video files from Dropbox.
• Recording and playback capabilities.
• AES-256 encryption for real-time content.
• Search and keyword analysis.

Pros

• Playback speed of 0.5x, 0.75x, 1x, 1.25x, 1.5x, 1.75x, 2x and 3x.
• Exportable audio, text, and captions.
• Supported file formats include mp3, txt, pdf, docx and srt; bulk export.
• Automatically send a summary to meeting participants.

Cons

• Otters sales tool is only available to enterprise plan users.
• Limited language support.

Also see: The Benefits of Generative AI

Krisp: Best for high-quality meeting audio

If you have kids running around and making noise during virtual meeting calls or you work from home with a lot of background noise, Krisp may benefit you. Krisp describes itself as an “AI-powered voice clarity and meeting assistant” tool. It removes the background voices of other people talking in the same room and keeps only your voice in the call.

Krisp meeting assistant capabilities include meeting transcription and meeting notes, while its AI voice clarity technology offers background voice cancellation, noise cancellation, echo cancellation and accent localization.

Pricing

• Free: 60 Minutes/day of noise, background voice, and echo cancellation plus unlimited transcriptions and two meeting notes per day.
• Pro: $8 per user per month, billed annually or $12 per user per month, billed monthly.
• Enterprise: Custom quotes.

Features

• Automatic summarization.
• Outbound and inbound noise cancellation.
• Real-time meeting transcriptions.
• User management option.

Pros

• Unlimited meeting transcription for the free plan.
• Talk Time indicator.
• High-quality audio

Cons

• The free and pro plan lacks an analytics dashboard.
• The free plan lacks 24/7 support.

On a related topic: What is Generative AI?

tl;dv: Best for UX and product teams

tl;dv’s AI meeting assistant enables you to catch up on meeting updates without attending the meeting yourself.  It is beneficial for busy professionals who may not have the time to participate in every meeting but still need to stay informed.

tl;dv generates meeting summaries, highlights important points, and identifies action items that must be followed up on.

Pricing

• Free forever: Available at no cost for small teams and individuals.
• Pro: $20 per recording user per month, billed annually or $25 per recording user per month, billed annually.
• Enterprise: Custom quotes.

Features

• Transcribe and summarize in 20+ languages.
• Combine clips into reels.
• Embed recordings and clips to WordPress and Notion.
• Automatic speaker recognition

Pros

• Generous free plan.
• Automatically transcribe meetings in 30+ languages, including German, English, French, Spanish, Japanese, Korean, and Portuguese.
• Lightweight.

Cons

• There is no free trial for the pro plan.
• Limited features.

MeetJamie: Best for automatic meeting summary

Unlike most artificial intelligence meeting assistant tools that automatically sync with your calendar and join your call when it’s meeting time, MeetJamie doesn’t send a bot to your meeting; it records your meeting audio and generates transcripts and summaries. It’s also capable of extracting tasks and detecting decisions in a meeting.

Pricing

Offers a 7-day free trial.

• Free: 5 monthly meeting credits and meetings can be as long as 30 minutes.
• Standard plan: $25 per month per user.
• Pro plan: $49 per month per user.
• Executive plan: $105 per month per user.

Features

• Automatic generation of summary, transcript and action items.
• Custom note templates.
• Meeting highlight.

Pros

• Multi-language support.
• Language detection.
• Automatic speaker recognition.

Cons

• No video recording.
• Requires installation

Airgram: Best for small teams and businesses

Airgram syncs your calendar availability, automatically joins your meeting and takes notes in real-time, providing a written summary of the discussion and action items after the meeting.

Airgram offers several meeting agenda templates and options, making it easy to set up meetings with a pre-defined structure.

Pricing

• Free: 30 minutes maximum call duration.
• Plus: $18 per user per month.

Features

• Share meeting snippets and links with internal and external contacts.
• Transcribe imported audio and video files.
• Associate notes from recurring meetings.

Pros

• Integration with Calendar (Google/Outlook), Slack, Google Docs, Notion, Zapier and Hubspot.
• Playback speed adjustment capability.
• Create video snippets.

Cons

• Speaker differentiation capability can be improved.
• The free plan only integrates with Calendar (Google/Outlook) and Slack.

MeetGeek: Best for highlights and keyword detection

MeetGeek integrates with your video conferencing tool to record, transcribe, and distribute meeting highlights to meeting participants.

Sales team, HR professionals and marketing teams can particularly benefit from MeetGeek features. The sales team can use it to automatically capture notes and insights from customer calls, thereby pushing tasks and highlights into their CRM tools such as HubSpot, Pipedrive or Salesforce. HR teams can automatically sync meeting notes and recordings with their ATS to create rich candidate profiles that can be analyzed later. Additionally, marketing teams can use it to make a repository of customers’ insights, allowing them to turn feedback into case studies.

Pricing

• Basic: Free plan.
• Pro: $15 per user per month, billed annually or $19 per user per month, billed monthly.
• Business: $29 per user per month, billed annually or $39 per user per month, billed monthly.
• Enterprise: Starts at $59 per month.

Features

• User management capability.
• Integrations with third-party services, including HubSpot, Trello, Slack and Asana.
• Automatic sharing for participants.
• Download the transcript in Google Docs, Word and XLS.

Pros

• Playback Speeds (1x, 1.5x, 2x, 3x).
• Team collaboration.
• Custom branding.
• Integrates with project management tools.

Cons

• Limited support for the low-tier plans.
• Lacks instant meeting capability; it requires you to schedule meetings 5 minutes in advance.

Key features of AI meeting assistant software

Meeting notes and transcript

Meeting notes are a critical component of AI meeting assistant software, as they help you remember the important details from your meeting and any action items that you or other team members need to complete before the next meeting. The transcription capability helps you capture every word spoken and creates a searchable record to refer to later.

Action item tracking

AI meeting assistants can track action items assigned during meetings and remind participants to complete them. Some software may even integrate with project management tools or task trackers to streamline this process. For example, Sembly and MeetGeek integrate with task and project management tools.

Integration with third-party services

Another important feature to consider is integration with third-party apps. Syncing your AI meeting assistant tool with Calender apps like Google and Outlook and video conferencing software like Zoom, Google Meet and Microsoft Teams will allow it to join your meetings and take notes for you automatically. Just be aware that not all AI meeting assistant integrates with all video conferencing tools. You need to verify that your selected tool can connect with your company’s existing software and tools.

​​Intelligent meeting search

AI-powered intelligent meeting tools allow you to use keywords to search through your AI meeting assistant’s past meeting notes, documents, and recordings to retrieve relevant information, eliminating the need for manual searching and saving time.

Also see: 100+ Top AI Companies

How to choose the right AI meeting assistant tool for your business

The best AI meeting assistant for you and your business depends on your needs and preferences – there is no one-size fits all AI meeting app. For instance, if you need a non-intrusive AI meeting assistant to record and transcribe meeting audio without joining your calls, MeetJamie may work for you. The Fireflies tool is ideal for businesses looking for a meeting assistant tool that balances affordability, service and features.

Those working from a noisy neighborhood will find Krisp’s noise cancellation capability beneficial, while busy professionals who are usually unable to join in-person meetings may prefer an AI meeting assistant like tl;dv.

To choose the right AI meeting assistant for your business, consider the following:

• Company needs: Specific pain points and challenges you hope to address with an AI meeting assistant.
• Organization size: The size of your organization and the number of employees using the AI meeting assistant.
• Budget: Some options may be more affordable than others, while some may offer more advanced features but come at a higher cost.
• Integration with existing tools: Can it connect with your current tech stack?
• Features: Look for features that are beneficial to your organization – and worth the cost that the AI meeting tool charges.

Review methodology

To write the review, we analyzed over 30 AI meeting assistant tools and scored them based on five key data points: Core features, customer service and support, cost, integrations and ease of use. We assigned a score to each AI meeting assistant tool based on these factors to determine their overall ranking.

We selected the top 10 AI meeting assistant tools based on their scores and further evaluated them. We conducted in-depth research on each AI meeting assistant tool, including reading customer reviews, analyzing case studies and testimonials, and studying their website and product documentation. We signed up for a free trial or free plan where possible to gain hands-on experience.

Bottom line: Best AI meeting assistants

The best AI meeting assistant tools enhance productivity and efficiency in meetings. However, be aware that AI meeting assistant software varies considerably from app to app. Though it may look like they offer the same value proposition and capabilities on the surface, accuracy can vary greatly between different providers.

Therefore, you must conduct extensive research on the tools you are considering before making a purchase decision. All the tools we reviewed offer free plans, which is a good starting point. Sign-up for a free plan and use it for some weeks or months if it serves you well — buy the premium plan to unlock its advanced features. Otherwise, consider other options for your AI meeting assistant.

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