Stanford is trying to understand the ways in which these models, what it means for kind of models to interact with humans. Should we be building our models differently if we know that humans are going to be in the picture as opposed to full automation? And that's kind of an interesting thing because maybe in some cases, the model, you want a model not to just be accurate, but you want it to be more interpretable or more reliable or kind of understandable.
A re-broadcast of Greylock general partner Saam Motamedi's interview with Adept CEO and co-founder David Luan and Stanford computer science and statistics professor Percy Liang. In this conversation (recorded in mid-2022), David and Percy discuss how large language models are paving the way for the next wave of AI. Adept is developing an AI "teammate" tool that is trained to use every software tool and API for knowledge workers. The company just raised $350 million in Series B funding to further its mission. Greylock has been partnered with Adept since co-leading the Series A in 2022.
You can watch the video from this interview on our YouTube channel here:
https://youtu.be/_ydBm3tADvA
You can read a transcript of the conversation on our website here: https://greylock.com/greymatter/ai-language-words-into-action/
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