IBM rethinks AI with IBM watsonx

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Announced at its annual Think conference, IBM has introduced IBM watsonx, a new AI and data platform to be released that will enable enterprises to scale and accelerate the impact of advanced AI with trusted data.

With IBM watsonx, the company is offering an AI development studio with access to IBM-curated and trained foundation models and open-source models, access to a data store to enable the gathering and cleansing of training and tuning data, and a toolkit for governance of AI to provide a seamless end-to-end AI workflow that will make AI easier to adapt and scale.

The new IBM collaboration with Hugging Face, announced last week, will also work to bring the best of open-source AI models to enterprises on the watsonx platform.

Clients will have access to the toolset, technology, infrastructure and consulting expertise to build or fine-tune and adapt available AI models. Additionally, IBM, a next generation enterprise studio, will be generally available in July, for AI builders to train, test, tune and deploy traditional ML and new generative AI capabilities through an open user interface.

The studio also includes a foundation model library, giving users access to IBM-curated and trained foundation models. Examples of the model categories include fm.code, fm.NLP and fm.geospatial.

Also at Think 2023, IBM announced upcoming offerings planned to drive AI adoption such as a new GPU offering on IBM Cloud, an IBM Consulting Center of Excellence for Generative AI and an IBM Cloud Carbon Calculator.

Arvind Krishna, IBM chairman and CEO, said: “With the development of foundation models, AI for business is more powerful than ever.

“Foundation models make deploying AI significantly more scalable, affordable and efficient. We built IBM watsonx for the needs of enterprises, so that clients can be more than just users, they can become AI advantaged. With IBM watsonx, clients can quickly train and deploy custom AI capabilities across their entire business, all while retaining full control of their data.”