The quest for knowledge at work can feel like searching for a needle in a haystack. But what if the haystack itself could reveal where the needle is?
That’s the promise of large language models, or LLMs, the subject of this week’s episode of the NVIDIA AI Podcast featuring DeeDee Das and Eddie Zhou, founding engineers at Silicon Valley-based startup Glean, in conversation with our host, Noah Kravitz.
With LLMs, the haystack can become a source of intelligence, helping guide knowledge workers on what they need to know.
Glean is focused on providing better tools for enterprise search by indexing everything employees have access to in the company, including Slack, Confluence, GSuite and much more. The company raised a series C financing round last year, valuing the company at $1 billion.
Large language models can provide a comprehensive view of the enterprise and its data, which makes finding the information needed to get work done easier.
In the podcast, Das and Zhou discuss the challenges and opportunities of bringing LLMs into the enterprise, and how this technology can help people spend less time searching and more time working.
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