ML practitioners usually choose a particular type of FM based on their needs and then either use it out of the box or … See more

Foundation models raise new issues in defining, measuring, and mitigating responsible AI concerns across the development cycle including accuracy, fairness, intellectual property consideratio… See more

LLMs can sufer from hallucination (i.e., they make up inaccurate responses that are not consistent with the training data). They are typically a byproduct of the way these FMs represent their inputs, often causing them not to distin… See more

Today, most of the time and money spent on FMs goes into training them. This is because many customers are only just starting to deploy FMs into production. However, in the future, when FMs are deployed a… See more

Customers have asked us how they can take advantage of what is out there today (and what is likely coming tomorrow) and quickly begin using FMs and generative AI within their business or organization to drive new l… See more