Smash Notes

Back to Beam: The Great American Open Model with ReflectionAI Co-Founder and CEO Misha Laskin, with Misha Laskin.

What Sets a Foundation for Intelligence?

Misha Laskin says code and agentic work set a foundation for intelligence, and the intelligence is jagged. It generalizes in a surprising way: his model reached a fresh, recent level of capability quickly, the kind other labs were discovering not long ago. Results still do not carry cleanly from one harness to another, including between versions of terminal bench.

Once a general agentic capability is working and the right data is available for a new harness, adaptation happens pretty quickly. The practical question is where the economically valuable pools of data sit. Open models are powerful because enterprises and customers can customize them for their own workloads and get the lowest cost for the highest performance. The usual path is a good evaluation rather than training on a customer's own data. A solid evaluation supports synthetic data that approximates the task and still generalizes.

Finance know your customer flows and compliance flows are very valuable. Cyber defense is quite valuable. Legal work and other agentic verticals inside the enterprise follow a similar pattern for getting something working.

Transcript

Beam: The Great American Open Model with ReflectionAI Co-Founder and CEO Misha Laskin ·

No Priors: Artificial Intelligence | Technology | Startups

More from this episode

  1. What Was Hardest About Building Reflection AI?Misha Laskin says the hardest part of building Reflection was everything.
  2. Is Catching the AI Frontier Getting More Expensive?Misha Laskin says catching up to the frontier can be done a lot more capital efficiently, and the price still climbs every year.
  3. How Was the Open Model Beam Trained?Misha Laskin says Beam was trained as a 500-billion-parameter model, with 23 billion of those parameters active. Pre-training ran on 6,000 GB300s.
  4. Have Open Models Overtaken Closed Models?Misha Laskin says the mix of tokens on model gateways has flipped from mostly closed to mostly open, and he thinks the shift will only accelerate.
  5. When Do Enterprises Switch to Open Models?Misha Laskin says enterprises consider open models after they ramp up significant workloads on closed models.
  6. What Do Open Models Do to AI Margins?Misha Laskin says open models compress margins across the whole AI stack.
  7. How Do Chinese Open Models Help Companies in the West?Misha Laskin says companies in the West have built more durable businesses because a great open-model ecosystem came from China, and he calls that a gift.
  8. Why Is Openness Safer for AI?Misha Laskin says openness is safer for AI because openness is already the safety default in software, and a few hundred researchers inside closed labs cannot…
  9. Can a PhD Take a Week With AI?Misha Laskin says a PhD can now take a week. Finding the right question and executing the answer to write a doctorate took a few years.
  10. How Does Beam Choose Its Next Training Bets?Misha Laskin says Beam chooses its next training bets by exhausting the high-impact methods the team already knows work, then expanding into riskier ideas.
  11. How Many Researchers Does a Frontier AI Lab Need?Misha Laskin estimates a steady state around an order of 100 researchers for a large effort like the one he is running.

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