It’s not just vision. It’s familiarity with the physical world. We think with our hands and LLMs simply haven’t had that data. Most of the problems require thinking in terms of physical object manipulation… that’s not necessarily reasoning.
Intuition for program search is mostly about observing and using similarity then? I'm using tiny SLMs trained on the DSL/solvers. The first program it generates is run and the failed output grid given, then the SLM updates the code and tries again. You can see it evolve its approach. It's not all memory; it's a cut-and-try approach like a human programmer's debugging/reasoning trace. I think we are ignoring a clear fact -- there is no good neural visual circuit for the data array as it can't read x,y coords once it gets up to, say, 10x10. AND -- 7B is too big for the available GPU types 🙂
what bothers me about program search is that i dont think it is related to reasoning at all. reasoning, in humans, happens over concepts that are already formed through continuous, similarity-based methods. so reasoning happens at a "higher level". but program search seems too "low level"
How is this channel still so unsubscribed! This is the coolest thing in AI right now. I tried using morphological image analysis, and it did pretty well on the easy stuff in the training set, but then I looked more into it and there's so much logical components, that it just wasn't going to work.
Yeah I have to keep reminding people in the chat room of this. Everyone wants to either use LLMs or brute force, but the point is to come up with really brand new ideas.
@@b.k.officiel873 I would say anything that is guess and check rather than trying to understand the examples. So the guy that generates 20,000 python programs per question, I would label as brute force. But that doesn't apply to training. You can do anything you want in training. If it took 20,000 python programs per example in training to learn how to reason about the questions, then that is ok because the final solution isn't brute force. You can also custom program solutions to every example. If you see a square with a missing corner, fill it in. Etc. That is brute force. It will automatically solve all training data, but fail on the test set.
![The moment we stopped understanding AI [AlexNet]](http://i.ytimg.com/vi/UZDiGooFs54/mqdefault.jpg)
![The moment we stopped understanding AI [AlexNet]](/img/tr.png)
Thanks.
i think the perception to solid building blocks and then useing those for programm synthesis is really powerful
It’s not just vision. It’s familiarity with the physical world. We think with our hands and LLMs simply haven’t had that data. Most of the problems require thinking in terms of physical object manipulation… that’s not necessarily reasoning.
Thank you for sharing
Intuition for program search is mostly about observing and using similarity then? I'm using tiny SLMs trained on the DSL/solvers. The first program it generates is run and the failed output grid given, then the SLM updates the code and tries again. You can see it evolve its approach. It's not all memory; it's a cut-and-try approach like a human programmer's debugging/reasoning trace. I think we are ignoring a clear fact -- there is no good neural visual circuit for the data array as it can't read x,y coords once it gets up to, say, 10x10. AND -- 7B is too big for the available GPU types 🙂
what bothers me about program search is that i dont think it is related to reasoning at all. reasoning, in humans, happens over concepts that are already formed through continuous, similarity-based methods. so reasoning happens at a "higher level". but program search seems too "low level"
Agree
Yeah, it’s more of a traditional optimization technique in a new medium… not reasoning
yes abstraction is the key to the solution i am building
Any chance you can post the generated code dataset before the competition ends?
How is this channel still so unsubscribed! This is the coolest thing in AI right now. I tried using morphological image analysis, and it did pretty well on the easy stuff in the training set, but then I looked more into it and there's so much logical components, that it just wasn't going to work.
Thanking you from Wisconsin. I'm trying NOT to use any brute force techniques... seems antithetical to the competition.
Yeah I have to keep reminding people in the chat room of this. Everyone wants to either use LLMs or brute force, but the point is to come up with really brand new ideas.
@@InfiniteQuest86 What do you mean by brute force in practice ?
@@b.k.officiel873 I would say anything that is guess and check rather than trying to understand the examples. So the guy that generates 20,000 python programs per question, I would label as brute force. But that doesn't apply to training. You can do anything you want in training. If it took 20,000 python programs per example in training to learn how to reason about the questions, then that is ok because the final solution isn't brute force. You can also custom program solutions to every example. If you see a square with a missing corner, fill it in. Etc. That is brute force. It will automatically solve all training data, but fail on the test set.