00:03 Learning from AI expert on reasoning and game plays 02:06 Evolution of poker Bots and model scaling in competitions 06:20 Improving search scalability in poker algorithms. 08:30 Use of search and planning in improving poker bot performance 12:36 Search algorithm made a 100,000x difference in poker and go 14:44 Scaling up models for performance improvement 18:42 Consensus or majority voting can improve performance on exams using GBD4. 20:35 Scalability of inference compute leads to significant performance improvements. 24:52 Machine learning moving towards reasoning-based models 26:42 Deciphering difficult codes using reasoning 30:41 Games provide ground truth for verifying winning states. 32:40 Different approaches to compute allocation for model training and testing impacts ELO rating 36:28 Effective algorithms leverage increased compute for long-term success. 38:28 OpenAI launching a new multi-agent reasoning team and hiring strong engineers for research. 42:35 Significant impact of scaling up inference compute 44:26 Need for restructuring academic research 48:25 Exploring different approaches for inference compute 50:11 Introducing controllable thinking time for more effective reasoning.
Comment from my philosophy bot: Descartes' statement, "cogito ergo sum" (I think, therefore I am) overstates the implications of the cogito, as the existence of a thinking entity or the reference of "I" is not necessarily justified by the mere assertion of thinking. The statement assumes the existence of an "I" that thinks, which may be questioned, as it could be more accurately expressed as "thinking is occurring" or "it thinks," implying an impersonal subject. Furthermore, the cogito can be seen as a tautology, as it already presupposes the existence of "I" in order to assert that "I" think. This makes the conclusion of existence from thinking logically trivial, as existence is assumed for thinking to occur, rather than being a consequence of it. Additionally, the statement's reliance on introspection and subjective experience raises questions about its ability to establish objective, third-personal facts. Critics argue that it is impossible to make sense of "there is thinking" without relating it to something, but this something cannot be the Cartesian ego, as objective differentiation between things based solely on the pure content of consciousness is unattainable. Introspection alone is insufficient to conclude the existence of any third-personal fact, making the cogito's implications regarding the existence of a thinking entity questionable.
Originally wrote a comment as a review of the talk, but when I re-read it, it felt a bit too mean. Instead, just have my personal recommendation that if you're limited on time, the other talks in this workshop are a great watch!
Here is a meta review that isnt afraid to be mean. Your review sucks and contains little information and contains no useful information. It's like it was generated by some highly censored LLM.
00:03 Learning from AI expert on reasoning and game plays
02:06 Evolution of poker Bots and model scaling in competitions
06:20 Improving search scalability in poker algorithms.
08:30 Use of search and planning in improving poker bot performance
12:36 Search algorithm made a 100,000x difference in poker and go
14:44 Scaling up models for performance improvement
18:42 Consensus or majority voting can improve performance on exams using GBD4.
20:35 Scalability of inference compute leads to significant performance improvements.
24:52 Machine learning moving towards reasoning-based models
26:42 Deciphering difficult codes using reasoning
30:41 Games provide ground truth for verifying winning states.
32:40 Different approaches to compute allocation for model training and testing impacts ELO rating
36:28 Effective algorithms leverage increased compute for long-term success.
38:28 OpenAI launching a new multi-agent reasoning team and hiring strong engineers for research.
42:35 Significant impact of scaling up inference compute
44:26 Need for restructuring academic research
48:25 Exploring different approaches for inference compute
50:11 Introducing controllable thinking time for more effective reasoning.
24:54 sad
But what does it mean for a model to think? Think like humans? “I think, therefore I am” type of think. Think is not defined.
Comment from my philosophy bot: Descartes' statement, "cogito ergo sum" (I think, therefore I am) overstates the implications of the cogito, as the existence of a thinking entity or the reference of "I" is not necessarily justified by the mere assertion of thinking. The statement assumes the existence of an "I" that thinks, which may be questioned, as it could be more accurately expressed as "thinking is occurring" or "it thinks," implying an impersonal subject.
Furthermore, the cogito can be seen as a tautology, as it already presupposes the existence of "I" in order to assert that "I" think. This makes the conclusion of existence from thinking logically trivial, as existence is assumed for thinking to occur, rather than being a consequence of it.
Additionally, the statement's reliance on introspection and subjective experience raises questions about its ability to establish objective, third-personal facts. Critics argue that it is impossible to make sense of "there is thinking" without relating it to something, but this something cannot be the Cartesian ego, as objective differentiation between things based solely on the pure content of consciousness is unattainable. Introspection alone is insufficient to conclude the existence of any third-personal fact, making the cogito's implications regarding the existence of a thinking entity questionable.
Originally wrote a comment as a review of the talk, but when I re-read it, it felt a bit too mean. Instead, just have my personal recommendation that if you're limited on time, the other talks in this workshop are a great watch!
?
Literally no one cares about your review or recommendation, stop spamming the comment section.
It’s not mean if you provide valid reasons. Otherwise, it’s called woke. This is science. Not a tea party.
Here is a meta review that isnt afraid to be mean. Your review sucks and contains little information and contains no useful information. It's like it was generated by some highly censored LLM.