The Nonlinear Library LW - Possible OpenAI's Q* breakthrough and DeepMind's AlphaGo-type systems plus LLMs by Burny
Nov 23, 2023
05:32
Welcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Possible OpenAI's Q* breakthrough and DeepMind's AlphaGo-type systems plus LLMs, published by Burny on November 23, 2023 on LessWrong.
tl;dr: OpenAI leaked AI breakthrough called Q*, acing grade-school math. It is hypothesized combination of Q-learning and A*. It was then refuted. DeepMind is working on something similar with Gemini, AlphaGo-style Monte Carlo Tree Search. Scaling these might be crux of planning for increasingly abstract goals and agentic behavior. Academic community has been circling around these ideas for a while.
https://www.reuters.com/technology/sam-altmans-ouster-openai-was-precipitated-by-letter-board-about-ai-breakthrough-2023-11-22/
https://twitter.com/MichaelTrazzi/status/1727473723597353386
"Ahead of OpenAI CEO Sam Altman's four days in exile, several staff researchers sent the board of directors a letter warning of a powerful artificial intelligence discovery that they said could threaten humanity
Mira Murati told employees on Wednesday that a letter about the AI breakthrough called Q* (pronounced Q-Star), precipitated the board's actions.
Given vast computing resources, the new model was able to solve certain mathematical problems. Though only performing math on the level of grade-school students, acing such tests made researchers very optimistic about Q*'s future success."
https://twitter.com/SilasAlberti/status/1727486985336660347
"What could OpenAI's breakthrough Q* be about?
It sounds like it's related to Q-learning. (For example, Q* denotes the optimal solution of the Bellman equation.) Alternatively, referring to a combination of the A* algorithm and Q learning.
One natural guess is that it is AlphaGo-style Monte Carlo Tree Search of the token trajectory. It seems like a natural next step: Previously, papers like AlphaCode showed that even very naive brute force sampling in an LLM can get you huge improvements in competitive programming. The next logical step is to search the token tree in a more principled way. This particularly makes sense in settings like coding and math where there is an easy way to determine correctness.
https://twitter.com/mark_riedl/status/1727476666329411975
"Anyone want to speculate on OpenAI's secret Q* project?
Something similar to tree-of-thought with intermediate evaluation (like A*)?
Monte-Carlo Tree Search like forward roll-outs with LLM decoder and q-learning (like AlphaGo)?
Maybe they meant Q-Bert, which combines LLMs and deep Q-learning
Before we get too excited, the academic community has been circling around these ideas for a while. There are a ton of papers in the last 6 months that could be said to combine some sort of tree-of-thought and graph search. Also some work on state-space RL and LLMs."
https://www.theverge.com/2023/11/22/23973354/a-recent-openai-breakthrough-on-the-path-to-agi-has-caused-a-stir
OpenAI spokesperson Lindsey Held Bolton refuted it:
"refuted that notion in a statement shared with The Verge: "Mira told employees what the media reports were about but she did not comment on the accuracy of the information.""
https://www.wired.com/story/google-deepmind-demis-hassabis-chatgpt/
Google DeepMind's Gemini, that is currently the biggest rival with GPT4, which was delayed to the start of 2024, is also trying similar things: AlphaZero-based MCTS through chains of thought, according to Hassabis.
Demis Hassabis: "At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models. We also have some new innovations that are going to be pretty interesting."
https://twitter.com/abacaj/status/1727494917356703829
Aligns with DeepMind Chief AGI scientist Shane Legg saying: "To do really creative problem solving you need to start searching."
https://twitter.com/iamgingertrash/status/1727482695356494132
"...
tl;dr: OpenAI leaked AI breakthrough called Q*, acing grade-school math. It is hypothesized combination of Q-learning and A*. It was then refuted. DeepMind is working on something similar with Gemini, AlphaGo-style Monte Carlo Tree Search. Scaling these might be crux of planning for increasingly abstract goals and agentic behavior. Academic community has been circling around these ideas for a while.
https://www.reuters.com/technology/sam-altmans-ouster-openai-was-precipitated-by-letter-board-about-ai-breakthrough-2023-11-22/
https://twitter.com/MichaelTrazzi/status/1727473723597353386
"Ahead of OpenAI CEO Sam Altman's four days in exile, several staff researchers sent the board of directors a letter warning of a powerful artificial intelligence discovery that they said could threaten humanity
Mira Murati told employees on Wednesday that a letter about the AI breakthrough called Q* (pronounced Q-Star), precipitated the board's actions.
Given vast computing resources, the new model was able to solve certain mathematical problems. Though only performing math on the level of grade-school students, acing such tests made researchers very optimistic about Q*'s future success."
https://twitter.com/SilasAlberti/status/1727486985336660347
"What could OpenAI's breakthrough Q* be about?
It sounds like it's related to Q-learning. (For example, Q* denotes the optimal solution of the Bellman equation.) Alternatively, referring to a combination of the A* algorithm and Q learning.
One natural guess is that it is AlphaGo-style Monte Carlo Tree Search of the token trajectory. It seems like a natural next step: Previously, papers like AlphaCode showed that even very naive brute force sampling in an LLM can get you huge improvements in competitive programming. The next logical step is to search the token tree in a more principled way. This particularly makes sense in settings like coding and math where there is an easy way to determine correctness.
https://twitter.com/mark_riedl/status/1727476666329411975
"Anyone want to speculate on OpenAI's secret Q* project?
Something similar to tree-of-thought with intermediate evaluation (like A*)?
Monte-Carlo Tree Search like forward roll-outs with LLM decoder and q-learning (like AlphaGo)?
Maybe they meant Q-Bert, which combines LLMs and deep Q-learning
Before we get too excited, the academic community has been circling around these ideas for a while. There are a ton of papers in the last 6 months that could be said to combine some sort of tree-of-thought and graph search. Also some work on state-space RL and LLMs."
https://www.theverge.com/2023/11/22/23973354/a-recent-openai-breakthrough-on-the-path-to-agi-has-caused-a-stir
OpenAI spokesperson Lindsey Held Bolton refuted it:
"refuted that notion in a statement shared with The Verge: "Mira told employees what the media reports were about but she did not comment on the accuracy of the information.""
https://www.wired.com/story/google-deepmind-demis-hassabis-chatgpt/
Google DeepMind's Gemini, that is currently the biggest rival with GPT4, which was delayed to the start of 2024, is also trying similar things: AlphaZero-based MCTS through chains of thought, according to Hassabis.
Demis Hassabis: "At a high level you can think of Gemini as combining some of the strengths of AlphaGo-type systems with the amazing language capabilities of the large models. We also have some new innovations that are going to be pretty interesting."
https://twitter.com/abacaj/status/1727494917356703829
Aligns with DeepMind Chief AGI scientist Shane Legg saying: "To do really creative problem solving you need to start searching."
https://twitter.com/iamgingertrash/status/1727482695356494132
"...