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Machine Learning Street Talk
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MLST is by Dr. Tim Scarfe @ecsquendor w/ cameos from @DoctorDuggar youtube.com/c/MachineLearn… (early access/priv.discord) - Sponsor us!
- Coding using @cursor_ai 0.45 with the @GoogleDeepMind (new) gemini-2.0-flash-thinking-exp model seems like the biggest step up in genai coding since Claude Sonnet 3.5 came out last June. This is unreal... forget about R1 folks - check out this new Gemini model! 🤯
- Devin just got debunked, no LLMs won't be replacing software engineers news.ycombinator.com/item?id=400081…
- The legendary @rao2z explains the difference between reasoning and memorisation using the example of the famous "why are manhole covers round?" interview question. Which do you think LLMs do?
00:00 - This is @fchollet discussing deep learning guided program synthesis, reasoning, o-series models and the ARC challenge. We will drop the full video hopefully later today!
00:00 - "o3 is the alexnet moment for program synthesis" - today is a pretty big day folks. We need to update our priors. o3 is zero-shotting extremely high scores on ARC-AGI which is a step towards the spirit of "developer aware generalisation" which Chollet originally envisioned.o3 is really special and everyone will need to update their intuition about what AI can/cannot do. while these are still early days, this system shows a genuine increase in intelligence, canaried by ARC-AGI semiprivate v1 scores: * GPT-2 (2019): 0% * GPT-3 (2020): 0% * GPT-4
- Terence Tao said that the new OpenAI models "could not generate conceptual ideas of their own"
- Today @GoogleDeepMind released AlphaEvolve: a Gemini coding agent for algorithm discovery. It beat the famous Strassen algorithm for matrix multiplication set 56 years ago. @Google has been killing it recently. We had early access to the paper and interviewed the researchers.
00:00 - Iman Mirzadeh from Apple @i_mirzadeh wrote the famous GSM-Symbolic paper a couple of months back which argued that LLMs are learning surface statistics and not genuinely reasoning due to their sensitivity to distractors and out of distribution examples.
00:00 - My dream came true today - an epic day of filming with the original gangster of AI - @SchmidhuberAI
- We just released our interview with the father of Generative AI - @SchmidhuberAI! The G, P, and T in "ChatGPT" (GPT means "Generative Pre-Trained Transformer") go back to Juergen's work of 1990-91 when he published what's now called "Unnormalised Linear Transformers,"
00:00 - Neural Networks are not Turing Machines/Turing Complete (in any practical sense). Probably the most pervasive thing which (apparently!) nearly everyone misunderstands about neural networks. This means that the space of expressible programs in a NN, is a tiny fraction of that of a
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00:00- Hot-take on Gemini 1) Surprised that Google managed to produce something roughly on GPT-4 level. They might be the only company other than OpenAI who will though. 2) The technology is SATURATING hard, scaling laws != competence 3) The elephant in the room is the AUTONOMY GAP -







