What’s going on here?

We are Reut and Antonia, students at Stanford’s Graduate School of Business (“GSB”) with backgrounds in early-stage investing and product management in Israel and Silicon Valley.

Since the release of OpenAI’s ChatGPT last fall, we found ourselves fascinated by the potential of large language models (LLMs) like GPT-3 (and as of this week, GPT-4!) to transform how people interact with technology. At the same time, we were wary of falling into the hype cycle and believing generative AI would solve all problems without taking the time to understand it deeply (we were also at Stanford a year ago when there was a big hype cycle around crypto…which has now largely subsided).

So we decided to talk to the smartest people we could find who are building LLMs at startups or large tech companies, are researching the space, or are investing in it, and learn how they think about this technology’s potential and limitations. We did this as part of an independent research project at Stanford, advised by Amanda Kelly, Stanford lecturer and cofounder of Streamlit, an open-source framework for creating machine learning and data science apps.

We’re creating this blog to capture our perspectives from dozens of conversations as well as our own experience playing around with ChatGPT, Bing, and other generative AI applications. Our goal is to write for a general business audience curious about the applications of large language models: both what use cases they enable and which companies will capture the most value from them.

We see this as an experiment in “learning in public” — sharing what we’re learning even if we don’t always get it 100% right! — so we welcome any feedback or suggestions on future topics to cover. Hit “subscribe” below to hear when we publish, and feel free to drop us a comment below.

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