Zachary Charles @MatharyCharles
distributed machine learning @ google | sometimes mathematician zachcharles.com Seattle Joined September 2012-
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Reading "Factoring Rational Polynomials over the Complexes" and this part jumped out at me. Is this "random Monte-Carlo NC" computational complexity class something well studied?
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Big news - someone made duck/structural typing into a philosophy. Will wonders never cease?
It will take me years to unravel the linguistic rapture of this tweet. It'll be 2030 and I'll still be talking about chubby cubby appetizers.
It will take me years to unravel the linguistic rapture of this tweet. It'll be 2030 and I'll still be talking about chubby cubby appetizers.
I'm beginning to think the JAX api docs aren't rendering correctly on my phone. Just a vague suspicion.
I've seen people (e.g. Goedel v2 report) use model averaging to mitigate this issue - but cannot personally vouch for how well this works!
Evergreen synopsis from @_katieeverett on scaling exponents - optimizers just often seem not to change them (though there are some recent theoretical works that purport to change this) x.com/_katieeverett/…
Evergreen synopsis from @_katieeverett on scaling exponents - optimizers just often seem not to change them (though there are some recent theoretical works that purport to change this) x.com/_katieeverett/…
I would love to see this done, but with the kind of evaluation methodology from the Algo Perf work. Though I guess one of the key takeaways from these two new works is that doing this in a "scaling aware" way requires new methodology.
I would love to see this done, but with the kind of evaluation methodology from the Algo Perf work. Though I guess one of the key takeaways from these two new works is that doing this in a "scaling aware" way requires new methodology. https://t.co/KOVeOjUiiY
I thought the fundamental insight from the model soup work was that you can bootstrap your own model collection just by changing training hparams - why isn't this used anywhere? E.g. From the (very cool) Goedel-Prover-V2 paper - no actual model soups, just model averaging.
Zachary Charles retweeted
They are not wrong.
I read the whole book a few years back. Graeber's explanations for why businesses would tolerate bullshit jobs was unconvincing - he basically invokes a nebulous "corporate feudalism" concept. More interesting were the insights on how a person feeling that their job was bs would…
I read the whole book a few years back. Graeber's explanations for why businesses would tolerate bullshit jobs was unconvincing - he basically invokes a nebulous "corporate feudalism" concept. More interesting were the insights on how a person feeling that their job was bs would…
Great read. Theoretical physics is so hard right now in part because the standard model is so good at fitting current data. The tough balance between "generating useful hypotheses" and "fitting past data" is also something I struggle with in AI!
Great read. Theoretical physics is so hard right now in part because the standard model is so good at fitting current data. The tough balance between "generating useful hypotheses" and "fitting past data" is also something I struggle with in AI!
Zachary Charles retweeted
Getting small batch sizes to work in bfloat16 precision can be challenging. In our recent paper on batch size, we ran all experiments in float32, but memory-constrained settings demand lower precision. Here are two tricks that we used to enable bf16 training at small batch sizes:
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