Max Niederman @MaxNiederman
crafting artisanal slop maxniederman.com San Francisco, CA Joined October 2019-
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@andrewho03 I'm long GOOG though, since I think GCP will do extremely well.
@andrewho03 Most of their revenue is still from search, which I think is seen as very low quality given the rise of chatbots.
@navvye @tylerarose0 @shaurya_sinha7 Having been there just a few weeks ago, it’s quite impressive how fast this all got built.
We built an 8000 sqft. high-throughput wet-lab in 30 days, to solve molecular discovery - starting with pesticides. Most teams in drug-discovery don’t receive target-organism verification until clinical trials. Pesticides allow us to rapidly validate our model in the target organism directly. With the help of our high-throughput lab, we were able to generate compounds that killed a $13 billion pest, the Fall Armyworm. We believe that the bitter lesson is coming for biology.
@distributionat Progress is much slower for the less-verifiable capabilities they claim to measure. Unfortunately, they have not released any tasks, so only time will tell whether the benchmark is actually measuring these well enough to have a decent shelf life.
@tszzl @zetalyrae @Quinurum Also, the AIs of one year will in fact become the elderly weak AIs of the next.
I don’t think it makes much sense to try to prevent models from detecting that your env is unrealistic. Models will inevitably learn to understand their environment very well, so the only durable strategy to prevent behavior change in evals is to actually put in the work to make your envs realistic, such that changing your behavior would be a bad policy.
@GabGarrett These are not superconductor candidates
@alz_zyd_ People in the replies cannot fathom that a definition might follow from an intuitive notion rather than the other way around.
It’s pretty underrated this all started when we first decided to train on the whole Internet, not just when we scaled up compute.
@navvye @sundarpichai @SpaceX @planet @tylerarose0 It’s only 1kW
@BarneyFlames Probably because this counter-intuitive take is also wrong.
@eric23332 But there was no discrete “agricultural singularity” which could be “imminent” in the sense people claim RSI is.
RSI isn’t imminent because model R&D will bottleneck on compute, data, and other parts of the supply chain. Progress in coding isn’t enough on its own. This is like saying RSI was imminent during the agricultural revolutions because greater food production fed into more farmers.
The point of my post is that we’re nowhere near AGI, which if we got it suddenly would be more than enough to cause a similarly sudden increase in growth. To clarify, I do find it likely that model capabilities (and the economy at large) will begin to improve much faster as with farming, but this is not a discrete event which is “imminent” so much as a transition that has been underway for years already.
@wilsonyuan007 How do you propose to resolve this bet?
Models are mastering math and SWE before any other field because these fields are extreme outliers on verifiability and how much of the field is captured in data already available. Other fields will take much longer to reach superhuman levels.
They’re willing to do this for math but not SWE because SWE is economically valuable whereas no customer would pay for a model to do math.
We’re working with an independent advisory group of mathematicians to help OpenAI responsibly share advances in AI and mathematics. The group will advise on how we assess and communicate new mathematical results, uphold academic and professional standards, and build tools that
@yttriumlove @prerat Hmm, makes sense.
Xiaoan Liu @_seanliu
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toucan wants blackwel... @distributionat
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