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At its recent Think 2023 conference, IBM focused on two areas – AI and quantum computing – that it believes will be essential to its enterprise customers. Let’s look at the details.
Why should organizations consider AI or quantum computing? The technologies are not mutually exclusive but deserve separate answers.
In the former case, AI offers companies new tools for analyzing and leveraging existing data resources with the aim of improving processes from IT management to supply chain operations. Consider that a company could use AI models to generate code for developers or to automate complex data center tasks. These and solutions based on other AI modalities are currently available to businesses.
While it is still in relatively early days, quantum computing is maturing quickly and, in fact, is an issue that many government agencies and businesses will need to understand and deploy relatively soon.
For example, last year the U.S. government released new requirements and guidelines for federal agencies to start transitioning to solutions to protect valuable and critically important data against quantum computing-based attacks. In part, that is due to the increasing prevalence of “harvest now, decrypt later” attacks aimed at enduringly valuable government information, like classified and strategic documents.
To achieve that, the National Institute of Standards and Technology (NIST) selected four quantum-resistant algorithms for standardization — three of which were developed by IBM, alongside academic and industry collaborators.
In addition, the National Security Agency (NSA) announced that national security systems will be required to fully transition to quantum-safe algorithms by 2035. They further define that software and firmware signing should begin transitioning immediately.
Finally, the White House ordered federal agencies to submit inventories of systems that could be vulnerable to cryptographically relevant quantum computers.
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IBM WatsonX Foundation Models
AI-enabled business has arrived, and the need for quantum computing is approaching quickly. IBM’s central message at Think 2023 was that it is delivering artificial intelligence business solutions today and is rapidly developing robust quantum safe technology and services for near term deployment.
According to IBM chairman and CEO Arvind Krishna, the new WatsonX AI and data platform was, “Built for the needs of enterprises, so that clients can be more than just users, they can become ‘AI advantaged.’ Foundation models make deploying AI significantly more scalable, affordable and efficient. With IBM WatsonX, clients can quickly train and deploy custom AI capabilities across their entire business, all while retaining full control of their data.”
What are foundation models? According to the company, they are built with large sets of IBM-curated enterprise data backed by a robust filtering and cleansing process and auditable data lineages. IBM is training the models on language, as well as other modalities, including code, time-series data, tabular data, geospatial data and IT events data.
Using WatsonX foundation models alone or in concert with their own proprietary data sets will enable IBM customers to speed and scale AI training processes while reducing potential problems caused by inaccurate or “noisy” data.
As a result, AI-enabled business processes should be more stable and successful out of the block. Plus, IBM believes that the adaptable AI models combined with enterprises’ data and domain expertise will enable customers to derive competitive differentiation and unique business value.
On a related topic: The AI Market: An Overview
The WatsonX platform: A Closer Look
As detailed at Think 2023, the WatsonX platform consists of three product sets:
- IBM watsonx.ai – an enterprise studio for AI builders to train, test, tune and deploy traditional machine learning and new generative AI capabilities. The studio provides a range of IBM-curated and trained foundation models, open-source AI models from IBM partner Hugging Face, tools and cost-effective infrastructure services that span data and AI lifecycles. Examples of foundation models include fm.code for automatically generating code; fm.NLP large language models for industry-specific domains; and fm.geospatial, which leverages climate and remote sensing data to help organizations understand and plan for changes in geophysical processes.
- IBM watsonx.data – a fit-for-purpose data store built on an open lakehouse architecture that is optimized for governed data and AI workloads. The data store can manage workloads on-premises and across multi-cloud environments, providing a single point of entry while applying multiple query engines. It offers built-in governance tools, automation and integrations with customers’ existing databases and tools.
- IBM watsonx.governance – an AI governance toolkit designed to enable trusted AI workflows. The toolkit operationalizes governance to reduce the risk and time requirements of manual processes, and also includes mechanisms to protect customer privacy, detect model bias and drift, and help organizations meet ethics standards.
Watsonx.ai and watsonx.data are expected to be generally available in July 2023. Watsonx.governance is expected to be generally available later this year. In addition, IBM plans to infuse WatsonX foundation models throughout its advanced software portfolio.
Finally, the company also announced other upcoming offerings designed to help drive AI adoption. Those include:
- A new GPU service on IBM Cloud.
- A Consulting Center of Excellence for Generative AI.
- The IBM Cloud Carbon Calculator, an AI-informed dashboard designed to help clients measure, track, manage and report carbon emissions associated with hybrid cloud usage.
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End-to-End Quantum Safe Solution
IBM’s new Quantum Safe technology is an end-to-end solution designed to help clients remain secure now and throughout their “quantum-safe journey towards the post-quantum era.” Sounds good, but what exactly does this mean?
While some quantum computing and quantum-like solutions are available, the market is still in very early days. However, potential dangers lie ahead as quantum technologies mature and become increasingly available to valid business and government agencies, as well as to bad actors, including rogue states and organized cybercriminals.
The question, then, is how organizations can best protect themselves against quantum-based cyberattacks during this transition. These attacks include “harvest now, decrypt later” schemes designed to steal highly encrypted data in the hopes that quantum-based tools can eventually be used to decode it.
In essence, IBM Quantum Safe is designed to thwart such efforts with various tools, including:
- IBM Quantum Safe Explorer enables organizations to scan source and object code to locate cryptographic assets, dependencies and vulnerabilities. Further, they can build a Cryptography Bill of Materials (CBOM) that enables teams to view potential risks and aggregate them in a central location.
- IBM Quantum Safe Advisor allows the creation of dynamic or operational views of cryptographic assets to analyze cryptographic posture and compliance to prioritize risks and to guide remediation efforts.
- IBM Quantum Safe Remediator helps organizations deploy and test best practice-based quantum-safe remediation patterns to understand their potential impacts on systems and assets prior to deploying quantum safe cryptography solutions.
IBM also announced its Quantum Safe Roadmap, which is designed to help clients understand new threats and solutions and support them through this security transition.
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Final Analysis
So, what are we to make of IBM’s new WatsonX solutions and Quantum Safe offerings? In the former case, WatsonX is hardly IBM’s first foray into AI. In fact, the company has been at the forefront of AI R&D since the 1950s with Arthur Samuels’ checkers-playing computer. IBM efforts continued through the Deep Blue system that beat chess grand master Gerry Kasparov in 1997 and the Watson system that triumphed over two Jeopardy grand champions in 2011.
While IBM’s commercial Watson efforts haven’t all succeeded as the company hoped, the platform remains one of the world’s most advanced generative AI solutions. Moreover, IBM’s focus on using Watson for simplifying operations and amplifying business benefits continues to find willing customers. In the weeks leading up to Think 2023, SAP announced that it will embed IBM Watson AI in SAP Start, the digital assistant that runs across all SAP instances.
With those points in mind, IBM’s plans and goals for WatsonX appear eminently sensible and achievable, and the company’s approach is spot-on. Leveraging its own substantial resources – curated foundation models, machine learning expertise, hybrid cloud assets and data management and governance tools – should make the WatsonX platform powerfully attractive to IBM clients.
Similar to its experience in AI, IBM was an early adopter and promoter of quantum computing and is actively working to bring quantum solutions to market. It also clearly recognizes the potential dangers that government agencies and enterprises face during the quantum computing transition. Along with its work on three of the four quantum-resistant algorithms adopted for standardization by the NIST, IBM also embedded quantum safe features in the z16 mainframes and LinuxONE 4 systems it launched last year.
In other words, just as it has done with WatsonX, the company is using its quantum computing investments and expertise to deliver Quantum Safe solutions to keep government and enterprise clients secure now and against future threats.
For more information, also see: What is Data Governance