roboboffin

5 ms·

31.
by roboboffin 2y ago
Yeah, that's what I thought.
32.
rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking(arxiv.org)
39 points by roboboffin 2y ago|7 comments
33.
by roboboffin 2y ago
The actual quote is that they are easier than IMO; but maybe not directly comparable. https://x.com/littmath/status/1870848783065788644?s=46&t=foR... I think it’s more probable that it would have solve the eas
34.
by roboboffin 2y ago
I think the problems it solved were understood to be well known undergraduate problems. https://xenaproject.wordpress.com/2024/12/22/can-ai-do-maths...
35.
by roboboffin 2y ago
I guess the point I am trying to make, is that paradoxically the more an AI company's products are integrated into the economy, the less value they can extract from the economy. As a large amount of the world's economic output is
36.
by roboboffin 2y ago
One thing I thought recently, is that a large amount of work is currently monitoring and correcting human activity. Corporate law, accounting, HR and services etc. If we have AGI that is forced to be compliant, then all these businesses dis
37.
by roboboffin 2y ago
However, the way it is progressing is that the SOTA is saturating the current benchmarks; then a new one is conceived as people understand the nature of what it means to be intelligent. It seems only natural to concentrate on one benchmark
38.
by roboboffin 2y ago
Interesting that in the video, there is an admission that they have been targeting this benchmark. A comment that was quickly shut down by Sam. A bit puzzling to me. Why does it matter ?
39.
by roboboffin 2y ago
Not an expert, but I think procedurally generated terrain is generally fractal in nature, and is reproducible in that sense from a seed that is used in the generation. It is therefore recursive, as fractals are recursive. A traditional neur
40.
AlphaQubit: AI to identify errors in Quantum Computers(blog.google)
161 points by roboboffin 2y ago|50 comments
41.
The Geometry of Concepts: Sparse Autoencoder Feature Structure(arxiv.org)
2 points by roboboffin 2y ago|0 comments
42.
by roboboffin 2y ago
I understand your point. I apologise, if I am coming across pendantic. My point is computers already follow algorithms, and algorithms contain reasoning; but the computers are not reasoning themselves. At least, not yet!
43.
by roboboffin 2y ago
It’s not reasoning, it retrieval of a pattern, and that pattern may contain reasoning. The prompt engineering is the real reasoning, provided by the human.
44.
by roboboffin 2y ago
For example, papers like this call into question whether or not a LLM can plan: https://arxiv.org/html/2409.13373v1 This is a basic form of reasoning, to plan out the steps needed to execute something.
45.
by roboboffin 2y ago
I'm not sure that's true at all. There are several well known researchers that say LLMs are in fact not doing reasoning.
46.
by roboboffin 2y ago
Hopefully, it won’t cause a plethora of nuisance phone calls. As the cost tends to zero, then it will be much easier to spam people; even more so than now.
47.
by roboboffin 2y ago
Is it that most models are based on the transformer architecture ? And so performance improvements can then we used throughout their different products ?
48.
by roboboffin 2y ago
I think this is similar to this point: https://news.ycombinator.com/item?id=41601738 That the chain-of-thought diverges from accepted truth as an incorrect token pushes it into a line of thinking that is not true. The use o
49.
by roboboffin 2y ago
Is this similar to the effect that I have seen when you have two different LLMs talking to each other, they tend to descend into nonsense ? A single error in one of the LLM's output and that then pushes the other LLM out of distributio
50.
The AI expert who says artificial general intelligence is nonsense(newscientist.com)
6 points by roboboffin 2y ago|0 comments
51.
by roboboffin 2y ago
Does that mean when we reduce the precision of a NN, for example using bfloat16 instead of float32, we reduce the set of computational problems that can be solved. How would that compare with a biological neural network with presumably near