IBM Watsonx – Scaling GenAI Responsibly
IBM recently announced the general availability of WatsonX. Below is our thoughts on what is significant and a recap of the main announcements.
With GenAI being a significant driver on enterprise interest, businesses still have more questions than answers in terms of how they will deploy, manage, and secure their company’s proprietary data. According to the most recent CIO Survey from Morgan Stanley, 66% of CIO’s surveyed indicate GenAI as an increasing budget priority in 2023 but only 5% indicate these initiatives are significant. From that same report, 33% of CIOs surveyed indicated that within the scope of the GenAI projects they are testing, they expect some form of the technology to be deployed in late 2024, with most CIOs stating 2025 as a reasobale expecation. This confirms the cautious approach most businesses are taking given they are hyper focused on scaling Gen AI responsibly and securely. This is why initiaties like IBM’s Watsonx are relevant to potentially help accellerate the adoption of GenAI within organizations large and small.
There are a few significant aspects that stand out in IBM’s announcement regarding the watsonx Granite model series and client protections:
Business-focused AI models – The watsonx Granite models have been specifically customized for enterprise use cases and optimized for precision and accuracy. This highlights IBM’s commitment to providing AI solutions tailored to business needs rather than general consumer applications.
Responsible and ethical AI – IBM has invested heavily in curating training data, implementing governance practices, and developing tools like watsonx.governance to ensure ethical and responsible AI development. This underscores their leadership in trustworthy AI.
Client protections for data – By providing standard contractual protections and IP indemnity, IBM enables clients to confidently leverage AI while safeguarding their valuable data assets. This reassurance facilitates wider business adoption of AI.
Scalable and flexible AI solutions – The Granite models are available in different sizes to meet diverse business requirements. The integration with third-party models also provides flexibility. This demonstrates IBM’s focus on scalable and adaptable AI.
Driving innovation in enterprise AI – The release of the Granite series marks an important milestone in making enterprise-ready AI accessible for businesses. IBM is spearheading innovation in this space.
What Was Announced
- IBM announced the availability of first models in watsonx Granite series, a new collection of generative AI models designed to advance the integration of generative AI into business applications and workflows
- Granite models are being developed in different sizes to fit the unique needs of various business use cases like customer service, document summarization, etc.
- Models can enable specific capabilities like retrieval augmented generation to search knowledge bases, summarization to condense long documents, and insight extraction for sentiment analysis
- IBM enables businesses to be AI creators by bringing proprietary data to IBM’s base models to build customized models
- IBM invested over the years in developing custom foundation models optimized for precision and accuracy required in business use cases
- Internal benchmarking shows specialized models deliver better accuracy with lower infrastructure requirements compared to generalized models
- IBM provides flexibility to integrate third-party models like Meta’s Llama chatbot and Hugging Face models based on business needs
- Granite models trained on curated, business-relevant datasets from 5 domains – internet, academic, legal, finance, code – and filtered for objectionable content
- IBM applying rigorous governance process and releasing watsonx.governance toolkit to enable trusted AI workflows for clients
- IBM extending standard IP protections, like those for hardware/software products, to watsonx models
- IP indemnity enables clients to confidently develop AI solutions using their data with IBM’s trusted foundation models