IBM Starts Rollout of 'watsonx' for Enterprise AI

IBM, once the face of "advanced" AI, might have fallen behind in the generative AI space but is seeking to catch up with an enterprise offering called watsonx.

It builds upon the company's Watson AI platform, a name familiar to those who watched an IBM supercomputer with that name beat humans in the TV game show "Jeopardy!" in 2011. The company also produced Deep Blue, which became a chess champion as a supercomputer using specialized machine learning algorithms.

And while IBM appears to be now lagging in the new generative machine language wars sparked by ChatGPT, it has recently made inroads to catch up.

The IBM watsonx site indicates the AI/data platform consists of three parts:

  • This is a new studio for foundation models, generative AI and machine learning. IBM says it can help organizations train, validate, tune and deploy foundation and machine learning models with ease.
    [Click on image for larger view.] Foundation Models (source: IBM).
  • This is for scaling AI workloads, for all data, anywhere with a fit-for-purpose data store built on an open lakehouse architecture.
    [Click on image for larger view.] Infrastructure Manager (source: IBM).
  • watsonx.governance: This enables responsibility, transparency and explainability in data and AI workflows, helping organizations to direct, manage and monitor its AI activities.
    [Click on image for larger view.] Governance (source: IBM).

While the first two are now available, general availability of watsonx.governance is expected in November.

IBM in May announced watsonx and today (July 11) revealed that it has been shaped by more than 150 users across industries participating in its beta and tech preview programs.

"Today in, AI builders can leverage models from IBM and from the Hugging Face community for a range of AI development tasks," IBM said. "The models are pre-trained to support a range of Natural Language Processing (NLP) type tasks including question answering, content generation and summarization, text classification and extraction. Future releases will provide access to a greater variety of IBM-trained proprietary foundation models for efficient domain and task specialization."

Along with foundation models, also features a Prompt Lab for prompt engineering to query large language models (LLMs), with a Tuning Studio coming soon to help organizations tune their foundation models with labeled data for better performance and accuracy.

"Over the next year, watsonx will continue to evolve and we expect to make significant releases," IBM said. "We will be focused on expanding enterprise foundation model use cases beyond NLP and operationalizing 100B+ parameter models for bespoke, targeted use cases -- opening the door to broader enterprise adoption.

"We will also bring to bear the strength of our AI governance capabilities -- helping organizations to implement end-to-end lifecycle governance, mitigate risk and manage compliance to the growing AI and industry regulations. AI governance should never be an afterthought, so we encourage our customers begin governance of their ML models and foundation models at the outset."

The new offering is available in a free trial before pricing kicks in.

About the Author

David Ramel is an editor and writer for Converge360.


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