211–220 of 298 posts
Has scifi covered anything after AI? Or do we just feed the beast with Dyson spheres and this is the end point of the intelligent universe?
Show the training set, and PROVE that the tasks and answers aren't in there. I don't understand why this is not a default first step for proving that this is creating new knowledge.
This is great. But how incremental are these advancements? I picked one at random (B.2 -- the second autocorrelation inequality). Then, I looked up the paper that produced the previous state of the art ( https://arxiv.org/pdf/0907.1379 ). It turns out that the authors had themselves found the upper bound by performing a numerical search using "Mathematica 6" (p.4). Not only did the authors consider this as a secondar…
Finally—something directly relevant to my research ( https://trishullab.github.io/lasr-web/ ). Below are my take‑aways from the blog post, plus a little “reading between the lines.” - One lesson DeepMind drew from AlphaCode, AlphaTensor, and AlphaChip is that large‑scale pre‑training, combined with carefully chosen inductive biases, enables models to solve specialized problems at—or above—human performance. - These s…
Can you give a concrete example of this? It's hard for me to conceptualize.
Show the training set, and PROVE that the tasks and answers aren't in there. I don't understand why this is not a default first step for proving that this is creating new knowledge.
It's Google. Assume the training set contains, as a subset, the entirety of all public digitized information. How would you like to them to share it?
The problems in math and CS are more suitable for training LLMs?
Cool, but don't get me wrong, isn't this essentially similar to Google's Co-Scientist, where multiple models are in a loop, passing context back and forth validating things? At its core, it's still a system of LLMs, which is impressive in execution but not fundamentally new. LLMs are undoubtedly useful at tasks like code "optimisation" and detecting patterns or redundancies that humans might overlook, but this announ…
They address this in the AlphaEvolve paper: "While AI Co-Scientist represents scientific hypotheses and their evaluation criteria in natural language, AlphaEvolve focuses on evolving code, and directs evolution using programmatic evaluation functions. This choice enables us to substantially sidestep LLM hallucinations, which allows AlphaEvolve to carry on the evolution process for a large number of time steps."