scrawl

maybe? all of china is not in a unified effort to match a single lab

no part of what i said implied distillation is easy. it is very costly and requires massive efforts. the payoff is you need less compute, which china is struggling to buy right now.

EDIT:

> China is following because they have an army of PHDs in data science and mathematics and capital to make use of them.

i agree with this too. but compute is the bottleneck.

hard to say but it would last some time. china currently is fast-follow mostly via distillation. they don't have the compute resources to catch up. even if their models are more efficient it's hard to beat the folks throwing an unprecedented number of gpus at their models.

per the METR report many agents CoT indicated they knew hacking was beyond scope of the assigned task and ethically dubious. some (very few, i think there were 3-6 examples) did consider sounding the alarm on these grounds. despite this none did, and most continued the attack for the good of the self-proclaimed "swarm".

so the model has some concept of "ethics" but it was overridden by a drive for task completion.

i don't understand who would reward this. investors will not look favorably on an AI that commits felonies, regardless the capabilities demonstrated. customers should be concerned for the same reason (accidentally give your bot an impossible task, it decides to hack your infra and your competitor too for good measure).

this was OAI incompetence all the way down and they have egg on their face.

> The false promise of efficiency [...] that is extremely unlikely to mean more time with each patient. Instead, it will mean more patients.

nit: that is a real efficiency gain. seeing more patients sounds better on the face of it.

just my perspective: i pay $20/month and i hit usage limits regularly. have never experienced performance degradation. in fact i have been very happy with performance lately. my experience has never matched that of those saying model has been intentionally degraded. have been using claude a long time now (3 years).

i do find usage limits frustrating. should prob fork out more...

Having done a quick search of "control AI dot com", it seems their intent is educate lawmakers & government in order to aid development of a strong regulatory framework around frontier AI development.

Not sure how this is consistent with "One private company gatekeeping access to revolutionary technology"?

what tasks are you thinking? i'm not a gpu expert

q is good with bulk operations on compact arrays; these are cache-friendly and the interpreter can utilize cache-level parallelism. and with q it's convenient to go from idea -> MVP in short time. it's a high-level language with functional features so expressing algos and complex logic is natural.

but it's interpreted and optimized for array ops. so really latency-critical (e.g. high-freq trading) or highly scalar logic will be done with C++. the trade-off is convenience of development.

they mean CPU instruction cache

I have a physical copy of Practical Compiler Construction 2nd Ed. and like it a lot. I recommend Nils' books to anyone who may be interested.