AlphaGo, every mention
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every year anyone Noam Brown 5Misha Laskin 4William Beauchamp 3Alessio Fanelli 3Shawn Wang 2Alex Duffy 2Will Brown 1Thomas Scialom 1Soumith Chintala 1RJ Haneke 1
Verbatim, from the transcripts: the passages where AlphaGo comes up
Cooking with OpenAI’s Research Chief: AGI, o1, Evals, and Scaling Laws — Mark Chen
🔬How GPT‑5 derived new results in theoretical physics and quantum gravity — Alex Lupsasca, OpenAI
Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay
- ▶ 15:08 unnamed speaker Oh, it's a very alpha goal.
Information Theory for Language Models: Jack Morris
- ▶ 2:09 Jack Morris I mean, I think AlphaGo, I thought AlphaGo was really good.
Scaling Test Time Compute to Multi-Agent Civilizations — Noam Brown, OpenAI
- ▶ 54:46 Noam Brown And I think if you're following, you know, you look at something like AlphaGo and AlphaZero, we seem to be following a very similar trend, right? 5 times in the scene
The Shape of Compute (Chris Lattner of Modular)
- ▶ 1:01:17 Chris Lattner Well, and so, uh, so my, my experience with RL systems were like at scale, DeepMind style, AlphaGo and things like this, right?
⚡️Launching AI Diplomacy: the hardest LLM Game Benchmark yet - Alex Duffy
- ▶ 9:58 Alex Duffy I mean, I, I think a lot of the examples that you gave, I think it's so cool that, you know, education being a big part, part of my life that AlphaGo, right? 2 times in the scene
⚡️Multi-Turn RL for Multi-Hour Agents — with Will Brown, Prime Intellect
- ▶ 25:50 Will Brown But, like, towards the end of the 20 tens, like, we had, like, AlphaGo and DeepMind doing all this multi-agent RL stuff that was, like, really cool.
Solve coding, solve AGI [Reflection.ai launch w/ CEO Misha Laskin]
- ▶ 2:06 Misha Laskin And the first one was reinforcement learning, in which a lot of members of our team pioneered some of the largest advances in that, including deep Q networks, AlphaGo, AlphaZero, and so forth. 2 times in the scene
- ▶ 4:10 Alessio Fanelli So you mentioned AlphaGo. 3 times in the scene
- ▶ 8:38 Misha Laskin I think that, I mean, so, for, to me, it just means, it's just a system that will be able to do most of the work that we wanted to on a computer, and not just kind of do it, but do it more creatively than we could, right, that it'll… 2 times in the scene
Outlasting Noam Shazeer, Crowdsourcing Chai AI w/ 1.4m DAU — with William Beauchamp, Chai Research
- ▶ 10:16 William Beauchamp There was almost nothing that went superhuman except for something like AlphaGo. 2 times in the scene
- ▶ 1:10:30 William Beauchamp Why was AlphaGo able to be superhuman, right?
Training Llama 2, 3 & 4: The Path to Open Source AGI — with Thomas Scialom of Meta AI
- ▶ 1:05 Thomas Scialom No, it's exactly that, but basically I think it's at the AlphaGo moment where I was doing some training.
- ▶ 35:39 Shawn Wang And, uh, so we mentioned at the start of the conversation about the AlphaGo moment. 2 times in the scene
Open Source AI is AI we can Trust — with Soumith Chintala of Meta AI
- ▶ 32:19 Soumith Chintala I, I think, ah, like the whole AlphaGo style model is one example, and then I think we're attempting to do it for LLMs as well, with like various reward models and then search.