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EPISODE · Jun 24, 2026 · 40 MIN

Building Self-Accelerating AI with Mirendil

from AI + a16z · host Matt Bornstein, Harsh Mehta, Behnam Neyshabur

Matt Bornstein speaks with Mirendil cofounders Behnam Neyshabur and Harsh Mehta about their vision for building self-accelerating AI. After leading research efforts at Google and Anthropic, the founders started Mirendil around a simple question: what happens when AI systems can meaningfully contribute to their own development? Rather than focusing solely on AI as a tool for productivity, they argue that the most important application may be accelerating scientific and technological progress itself. The conversation explores AI research, scaling laws, automated engineering, scientific discovery, and the challenges of building systems that can improve over time. They discuss the future of AI-assisted research, why they believe scientific progress remains bottlenecked by intelligence, and how more capable AI systems could help unlock advances across medicine, engineering, and the natural sciences. Resources: Follow Behnam Neyshabur on X: https://x.com/bneyshabur?lang=en Follow Harsh Mehta on X: https://x.com/HarshMeh1a Follow Matt Bornstein on X: https://x.com/BornsteinMatt Check out everything a16z is doing with artificial intelligence here, including articles, projects, and more podcasts. 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 Jun 24, 2026

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Matt Bornstein speaks with Mirendil cofounders Behnam Neyshabur and Harsh Mehta about their vision for building self-accelerating AI. After leading research efforts at Google and Anthropic, the founders started Mirendil around a simple question: what happens when AI systems can meaningfully contribute to their own development? Rather than focusing solely on AI as a tool for productivity, they argue that the most important application may be accelerating scientific and technological progress itself. The conversation explores AI research, scaling laws, automated engineering, scientific discovery, and the challenges of building systems that can improve over time. They discuss the future of AI-assisted research, why they believe scientific progress remains bottlenecked by intelligence, and how more capable AI systems could help unlock advances across medicine, engineering, and the natural sciences.

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Building Self-Accelerating AI with Mirendil

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