Navigating the Efficacy of Large Language Models in Classification Tasks

AI is going to change science forever. Small scale studies will give way to large scale open data gathering efforts. We’ll shift from seeking broad general theories to making contextual predictions in individual cases. The traditional research paper will change fundamentally. That’s why I had Alice Albrecht on the show. Few people straddle the worlds of science and AI like she does: She holds a Ph.D. in cognitive neuroscience from Yale and is a machine learning researcher with almost a decade of experience. Her startup re:collect built an app to augment human intelligence with AI and was acqui-hired by SmartNews earlier this year. She now heads up AI product there. We get into the contours of this new paradigm in science: - Whether research papers are still the best format to “release” science in - The increasing importance of data in scientific discovery - Why AI is making N-of-1 studies imperative—when they’re normally seen as unscientific - The case for big tech to open-source their data for scientific research - The power of unbundling data and interpretations, in science and media This is a must-watch for anyone interested in how AI is changing the future of scientific research. If you found this episode interesting, please like, subscribe, comment, and share! Want even more? Sign up for Every to unlock our ultimate guide to prompting ChatGPT here: https://every.ck.page/ultimate-guide-to-prompting-chatgpt. It’s usually only for paying subscribers, but you can get it here for free. To hear more from Dan Shipper: Subscribe to Every: https://every.to/subscribe Follow him on X: https://twitter.com/danshipper

Timestamps:

1. Introduction: (00:00:59)

2. Everything Alice learned about growing an AI startup: (00:04:50)

3. Alice’s thesis about how AI can augment human intelligence: (00:09:08)

4. Whether chat is the best way for humans to interface with AI: (00:12:47)

5. Ideas to build an AI model that predicts OCD symptoms: (00:23:55)

6. Why Alice thinks LLMs aren’t the right models to do predictive work: (00:37:12)

7. How AI is broadening the horizons of science: (00:38:39)

8. The new format in which science will be released: (00:40:14)

9. Why AI makes N-of-1 studies more relevant: (00:45:39)

10. The power of separating data from interpretations: (00:50:42)

Links to resources mentioned in the episode:  

• Alice Albrecht: @AliceAlbrecht

• The company that recently acquired Alice’s startup: SmartNews

• The piece Alice wrote for Every about how AI can augment human intelligence: The Case for Cyborgs 
  Every’s product incubations that we discuss in the context of how AI is changing media: Extendable Articles, TLDR