Note that you're asking whether it's more impressive that someone managed to analyze and intentionally create an appealing, cross-cultural, and marketable product, rather than creating something appealing completely by accident. Of course the former is far more impressive than the latter, assuming it really was intention as laid out by the OP. It requires intelligence and understanding of the world.
> IMO wherever someone says "the government" we should mentally substitute "we all, collectively".
No, we should substitute "unaccountable bureaucrats". The people who enter and leave power from elections are not the source of the daily frustrations people have with government, it's the rest.
If this is in fact an issue where you life, then you should consider stopping to elect politicians that allow bureaucrats to be unaccountable. Or stop believing politicians who rave on about how bureaucrats are unaccountable while they themselves have the power to shape systems where that would not be the case.
Same way anyone else got their job, but that's beside the point. The point is that accountability in government is significantly lower than in private industry, and this is a big source of the problems.
They are smart, but they are not aware of the environment they're in, or any implicit context that someone whose doing a job carries with them, that's why all of that context has to be explicitly laid out in a prompt. When the context is provided, they are quite smart.
> Why on earth would you go out of your way to do that? If someone wants to try it, why stop them? She just took it for granted that their job was to enshrine the existing state of things in a formal law.
This is exactly the Canadian experience: restrictions without thought.
> You're not really solving problems, you're retrieving the best match of solved problems from compressed corpus.
This is not correct. LLMs interpolate in a high dimensional space, so you're actually composing the best matches in a compressed corpus to find novel points/paths in that space. That is problem solving.
> that the infrastructure being built and compute commitments being made are being done so at a level that demands that generative AI and AI compute generate over $2 trillion in annual revenue by 2030
That seems doable. Next generation architectures and the models they produce are accelerating progress. More capable with less data and compute, which ironically will drive more demand, aka Jevon's paradox.
> If you are someone in the executive team of any major tech company, know that your employees are, for the most part, completely and utterly miserable.
I agree this is a problem. Adopting too eagerly and too early, and not listening to feedback from the people who are using these tools is a recipe for disaster.
> Healthy democracies will still have investigative journalism, public debate, trustworthy institutions, etc.
Boy do I wish that were the case. Investigative journalism is rare now and instead favours activist journalism, public debate is hard (but getting better), and institutional trust is at all time lows, for various reasons.
People will muddle through regardless, we're not as fragile as most assume.
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