IBM launches watsonx studio to make deploying generative AI easier

IBM launches watsonx studio to make deploying generative AI easier

The watsonx platform announcement also marks IBM’s plan to add generative AI to other services, incorporating code writing and NASA weather data.

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AI is the hottest commodity at the moment according to the tech innovation market. Today, IBM announced watsonx, which is made up of three different product sets. In total, they serve as a studio, data store and governance toolkit for generative AI and foundation models. A waitlist is now open for watsonx products, with general availability of the first product set derived from it,, expected in July.

The three product sets under the watsonx umbrella are, the studio itself and a foundation model library:, a data store; and watsonx.governance, a governance toolkit.

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What is IBM watsonx?

IBM watsonx is a platform on which to train, tune and deploy AI models. It can train foundation models and machine learning models for cloud environments. IBM-curated and -trained AI models will form the backbone of the service.

These foundation models and open-source AI models will handle the gathering and neatening of training data and then pass that data up to the business that needs it. There’s also a toolkit for ongoing AI governance. IBM wants to provide an end-to-end AI workflow that will let businesses go from not having any AI in play at all to customizing and running it for themselves.

SEE: Microsoft predicts AI will work alongside, not replace, employees.

“We built IBM watsonx for the needs of enterprises, so that clients can be more than just users, they can become AI advantaged,” said Arvind Krishna, IBM chairman and chief executive officer, in a press release.

Following the end-to-end workflow model, clients can build their own models from the ground up or adapt existing AI models.

The watsonx studio also includes tools for writing code among those existing models. For example, fm.code in the foundation model library will use a natural language interface to automatically generate code for developers. Another library, fm.NLP, is a collection of large language models tailored to specific or industry-specific domains. Lastly, fm.geospatial is a model that uses NASA satellite data to analyze weather patterns and climate change.

IBM teams up with Hugging Face

One of the existing AI models IBM encourages users to easily add to their watsonx workflow is Hugging Face’s open-source libraries. Thousands of Hugging Face open models and datasets will be available through watsonx.

Watsonx AI coming to other IBM software products

With this AI at IBM’s fingertips, the company is following industry trends and putting it in as many products as possible. Customers will start to see watsonx services pop up in all of IBM’s major software products. Those services include:

  • Watson Code Assistant for writing code.
  • AIOps Insights for greater visibility in IT operations.
  • Watson Assistant and Watson Orchestrate for labor and customer service solutions.
  • Environmental Intelligence Suite for EIS Builder Edition, which helps measure and respond to environmental risks.

At the Think 2023 conference, the company also announced the opening of the IBM Consulting Center of Excellence for Generative AI, which brings together 1,000 generative AI experts who will work in consulting for businesses who want help building and deploying watsonx.

SEE: Does AI really make sense when organizations look at the costs and benefits?

What are IBM watsonx’s competitors?

Although watsonx is positioned as a way to make it easier for organizations to deploy AI, it’s also a way to keep that deployment within IBM’s ecosystem. Microsoft’s Azure AI platform does something similar, as do Amazon’s SageMaker Studio, Google’s Vertex AI and some more specifically AI-focused businesses such as Cohere and Anthropic.

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