@devagrawal09 "large scale distillation attack" is still a dog whistle AI companies use now to blame scary asians (that don't exist) and not their terrible (non existent?) security hygiene. They've created a reality in AI where you can just blame things on Chinese and not take responsibilty.
@devagrawal09 "large scale distillation attack" is still a dog whistle AI companies use now to blame scary asians (that don't exist) and not their terrible (non existent?) security hygiene. They've created a reality in AI where you can just blame things on Chinese and not take responsibilty.
@BrianMRey You're not supposed to focus on that, you're supposed to focus on the fact that it was a "distillation attack" and think about scary asians.
@jsuarez I agree, I can see the usefulness as a sorting mechanism for people who will push through the discomfort of working on hard problems they might not enjoy. It might be gatekeeping but its also a quality you want in your staff.
@i2cjak What was so sophisticated about the lrand48 lib? This is just further proof that they mostly brute force on loop until they arrive at a solution. Much like they do with lean, "they" try a bunch of random approaches until it works. Literal infinite monkey theorem
@dotpem Sounds like more useless meta-agentic workflows. Its very similar to how everyone used to work on their .nvim cfg all day, thinking they're being productive but doing nothing. It would be lossy and you'd be saving yourself a few buck a month, after spending hrs to implement.
AMD ended up sending us the boxes and giving us a $2M contract. Their stock went from $97.10 to $608.10 and the software is quite usable now.
Are you a chip maker who wants to turn your life around? Who is hungry to win? @intel@Qualcomm@tenstorrent
@AnushElangovan If this isn't worth 200k to AMD to send us a few boxes, I don't know what to tell you. Cultural test to see if AMD can invest in software, if not why should I waste my development time on MI300X?
@MatthewChang I would also argue that token prices have so bar been deflationary, and I don't see how that would go the other way. More Machines + More Users = more margin = cheaper + jevons paradox. I agree Anthropic is over valued, but I do not think your analysis here is accurate.
@MatthewChang I'm with you here, but there is an issue, GPU inference leverages batch processing. The cost to serve 1k requests is similar to serving 5 (but the 5 just have a little better latency). Anthropic isn't giving out 20k for a 1k, they amortize the cost across many request .
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