The News: On September 7, IBM announced several AI-focused rollouts and enhancements to watsonx. Here are the key details:
- New AI models are coming to watsonx.
- The Granite series are IBM-built AI foundation models (FMs) that the press release says are designed to support enterprise natural language processing (NLP) tasks such as summarization, content generation, and insight extraction. It is important to note that IBM plans to “provide a list of the sources of data as well as a description of the data processing and filtering steps that were performed to produce the training data for the Granite series of models.” Granite models will be available later in September.
- Meta’s Llama 2 chat (70 billion parameter) and StarCoder LLM are now available in watsonx.ai on IBM Cloud.
- Watsonx.ai introduces a synthetic data generator “to assist users in creating artificial tabular data sets from custom data schemas or internal data sets. This will allow users to extract insights for AI model training with reduced risk, thereby augmenting decision making and accelerating time to market. (Available now).”
- Watsonx.governance begins a tech preview of previously announced capabilities “for automated collection and documentation of foundation model details and model risk governance capabilities that allow stakeholders to view relevant metrics in dashboards of their enterprise-wide AI workflows with approvals so humans are engaged at the right times.”
Read the full press release on the Granite AI models and watsonx enhancements on the IBM website.
IBM Rolls New Granite AI Models, Continues watsonx Platform Momentum
Analyst Take: IBM has significant AI street cred. The company has been a longtime investor and innovator in AI, producing some of the earliest and most successful AI-fueled products and platforms, most notably Watson. In the dawn of the generative AI era, IBM is well-positioned to help enterprises operationalize AI through the watsonx platform, and the company will vie with other major players to capture market share. How does the launch of the Granite AI models affect the market?
Granite Is a Market Statement
Although there are not many details regarding IBM’s Granite AI models, the impending launch is a market statement for IBM. Why? With the addition of IBM large language models (LLMs), the watsonx platform, combined with IBM Cloud computing options, is now a comprehensive, end-to-end platform that gives enterprises a one-stop shop/tech stack for leveraging AI in their organizations. It was pretty comprehensive without Granite, but AI foundation models have become the rockstar elements of AI, and in the Granite models, there is the potential for a seamless integration between IBM’s AI models and the rest of the IBM AI stack for customers. To this integrated approach, add AI chip development, in which IBM is heavily invested. Only IBM, Google, AWS, and Microsoft (with AMD) offer such a comprehensive stack.
Granite Reflects Responsible AI Principles
As previously noted, there are not a lot of details about the Granite series yet, but IBM made a point to mention its plans to provide a list of source data and a description of the steps the company used to produce Granite model training data. There is growing momentum for this approach to transparency in AI models. Many proprietary LLM vendors refuse to divulge their training data sources, for various reasons, though most commonly because the LLM vendor sees that data source as competitive IP. IBM is positioning its AI models less as “secret sauce;” instead, the proprietary value in the IBM stack is in watsonx and the value of the complete chain. This approach frees IBM to offer AI models that can meet transparency best practices.
Conclusion
A full-stack AI approach fits to a player such as IBM, which positions itself as a premium option. A full-stack approach will not be for every enterprise, but it will certainly appeal to many, including IBM’s already substantial customer base. It will be interesting to see the details of the Granite models and how they perform when launched. In theory, the responsible AI approach with transparency is a savvy strategy and fits well with the thread of responsible AI best practices IBM has committed to.
Disclosure: The Futurum Group is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of The Futurum Group as a whole.
Other insights from The Futurum Group:
IBM watsonx.governance Tackles AI Risk Management
watson.ai Leverages Foundation Models to Accelerate AI Application Development
IBM watsonx.data is Now Generally Available as Part of Major watsonx Announcement
Author Information
Mark comes to The Futurum Group from Omdia’s Artificial Intelligence practice, where his focus was on natural language and AI use cases.
Previously, Mark worked as a consultant and analyst providing custom and syndicated qualitative market analysis with an emphasis on mobile technology and identifying trends and opportunities for companies like Syniverse and ABI Research. He has been cited by international media outlets including CNBC, The Wall Street Journal, Bloomberg Businessweek, and CNET. Based in Tampa, Florida, Mark is a veteran market research analyst with 25 years of experience interpreting technology business and holds a Bachelor of Science from the University of Florida.
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