Karpathy’s autoresearch could make scientists of us all episode artwork

EPISODE · Apr 1, 2026 · 21 MIN

Karpathy’s autoresearch could make scientists of us all

from Azeem Azhar's Exponential View · host EPIIPLUS 1 Ltd / Azeem Azhar

Welcome to Exponential View, the show where I explore how exponential technologies such as AI are reshaping our future. I’ve been studying AI and exponential technologies at the frontier for over ten years. Each week, I share some of my analysis or speak with an expert guest to make light of a particular topic. To keep up with the Exponential transition, subscribe to this channel or to my newsletter: https://www.exponentialview.co/ ---- Published in early March 2026, Andrej Karpathy's autoresearch AI tool makes autonomous scientific experimentation cheap and easy — but it was designed to solve machine learning problems. I wanted to see if I could apply its loop architecture to my own work: refining my worldview, testing arguments, solving business problems. In this video, I share how I adapted Karpathy’s autoresearch loops for problems that aren't easy to quantify, how to avoid the local minima trap, and the broader impact of these kinds of methods. I covered: (02:11) The Karpathy Loop: what is it and how does it work (07:54) Extending the loop into business and thinking (09:46) The local minima trap (12:20) The escape harness: getting beyond “good enough” (16:05) What I’ve learned after 30 days (18:47) The loop economy: from doing to judging ---- Where to find me: Exponential View newsletter: https://www.exponentialview.co/ Website: https://www.azeemazhar.com/ LinkedIn: https://www.linkedin.com/in/azeem/ Twitter/X: https://x.com/azeem Production by EPIIPLUS1. Production and research: Baba Films, Chantal Smith, Marija Gavrilov. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

Episode metadata supplied by the publisher feed · Published Apr 1, 2026

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Published in early March 2026, Andrej Karpathy's autoresearch AI tool makes autonomous scientific experimentation cheap and easy — but it was designed to solve machine learning problems. I wanted to see if I could apply its loop architecture to my own work: refining my worldview, testing arguments, solving business problems. In this video, I share how I adapted Karpathy’s autoresearch loops for problems that aren't easy to quantify, how to avoid the local minima trap, and the broader impact of these kinds of methods. I covered:

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Karpathy’s autoresearch could make scientists of us all

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