Built in collaboration with and exclusively for OpenAI - an artificial intelligence (AI) research laboratory consisting of the for-profit corporation OpenAI LP and its parent organization, the non-profit OpenAI Inc. - the supercomputer hosted in Azure was designed specifically to train that company’s AI models. The supercomputer, says the company, represents a first step toward making the next generation of very large AI models and the infrastructure needed to train them available as a platform for other organizations and developers to build upon.
"The exciting thing about these models is the breadth of things they’re going to enable," says Microsoft Chief Technical Officer Kevin Scott. "This is about being able to do a hundred exciting things in natural language processing at once and a hundred exciting things in computer vision, and when you start to see combinations of these perceptual domains, you’re going to have new applications that are hard to even imagine right now."
Traditionally, says the company, machine learning experts have built separate, smaller AI models that use many labeled examples to learn a single task such as translating between languages, recognizing objects, reading text to identify key points in an email, or recognizing speech well enough to deliver today’s weather report when asked. A new class of models developed by the AI research community has proven that some of those tasks can be performed better by a single massive model — one that learns from examining billions of pages of publicly available text, for example.
This type of model can so deeply absorb the nuances of language, grammar, knowledge, concepts, and context, says the company, that it can excel at multiple tasks: summarizing a lengthy speech, moderating content in live gaming chats, finding relevant passages across thousands of legal files, or even generating code from scouring GitHub. As part of its AI at Scale initiative, Microsoft has developed its own family of large AI models - the