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With the introduction of its new Watsonx platform, IBM is rebranding its more than two-decades-old AI system, Watson.
Previewed at the IBM Think 2023 conference on Tuesday, Watsonx is a new AI and data platform for foundation models and generative AI.
The platform includes Watsonx.ai, Watsonx.data and Watsonx.governance.
Watsonx.ai is an enterprise studio that will enable AI builders to train, test and deploy generative AI capabilities powered by foundation models.
Scheduled to be generally available in July, the studio also includes a model library populated with IBM's trained foundation models. Some foundation models available now in beta preview include Fm.code, Fm.NLP and Fm.geospatial.
Fm.code is a set of models that automatically generate code for developers. Fm.NLP is a suite of large language models for specific industries. And Fm.geospatial provides models built on climate and remote sensing data to help organizations know more about natural disaster patterns, biodiversity, land use and geophysical processes.
Watsonx.ai studio will build on open source libraries and offer thousands of open models and data sets from generative AI vendor Hugging Face.
Watsonx.data is a data store built on open lakehouse architecture for governed data and AI workloads that will be available in July, according to IBM. Watsonx.governance is a toolkit aimed at mitigating risk associated with AI and protecting customers' privacy. It is expected to be generally available sometime later this year.
Watsonx enables the 111-year-old tech vendor to enter the burgeoning generative AI market, following the likes of younger tech giants such as Google, Microsoft and AWS, as well as independent AI hardware/software vendors such as Nvidia and SambaNova.
IBM's differentiating factor
While it appears that IBM is late to the fast-growing market, that's not the case, said Daniel Newman, an analyst at Futurum Research.
"This is what I would call the next wave [in generative AI]," Newman said, noting that IBM offers enterprises an AI platform driven by security and data privacy.
"What we've seen mostly launched so far has been tools for users, consumers and social, and a few productivity apps," he said. Watsonx is different because it focuses solely on enterprises, Newman added.
Arun ChandrasekaranAnalyst, Gartner
Moreover, even if the big cloud providers have pushed out enterprise AI products, generative AI adoption is still in its infancy, Gartner analyst Arun Chandrasekaran said.
"More enterprise clients want to customize the generative AI models to align with their use cases," he said. "IBM is betting on the fact that there will be numerous models used, but clients would look for a consistent set of tools to operationalize them."
The vendor is also differentiating itself by focusing on AI and hybrid cloud, Newman said.
He added that by using Red Hat -- the open source software vendor it acquired in 2018 -- IBM is appealing to enterprises that are building data governance systems for compliance on cloud and on-premises hybrid infrastructures.
"We assert that a hybrid cloud choice gives you two and a half times more value than picking a singular answer from one of those underlying landscape choices," IBM CEO Arvind Krishna said during a streamed and live keynote address at the conference on May 9.
IBM and Red Hat also revealed a collaborative effort to make coding easier for developers with Watson Code Assistant. Code Assistant enables developers to generate code with accessible English commands.
Meanwhile, enterprises will find IBM's services and consulting businesses helpful in servicing their foundation models, Newman said. IBM's partnerships with big consulting firms such as Accenture will also help in deploying large-scale AI models, he said.
"Companies have tons of data, and they're going to want to build very specific models on top of these different foundational tools that are being offered as part of Watsonx," Newman said. "And those models are going to become specific to different parts of the business, and they're going to need a lot of help."
Watsonx comes with challenges. The main hurdle is achieving speed to market, Chandrasekaran said.
"IBM needs to boost its mindshare in the generative AI space," he said. "While IBM research is a significant innovator in AI, IBM needs to accelerate the pace at which it is commercializing its research capabilities."
Another key challenge is competition, Newman said. Many vendors, particularly cloud giants Google and Microsoft, are vying to be the dominant provider of what enterprises need with generative AI technology.
IBM's strength in its diverse customer base, strong consulting and deployments in the hybrid cloud world could give it a firm footing, Newman added.
Esther Ajao is a news writer covering artificial intelligence software and systems.