This notion of a hard takeoff, or singularity, based on self-improving AI, is based on the implicit assumption that what's holding AI progress back is lack of AI researchers/developers, which is false.

Ideas are a penny a dozen - the bottleneck is the money/compute to test them at scale.

What exactly is the scenario you are imagining where more developers at a company like OpenAI (or maybe Meta, which has just laid off 600 of them) would accelerate progress?

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xeckr 3 hours ago | parent [-]

It's not hard to believe that adding AI researchers to an AI company marginally increases the rate of progress, otherwise why would the companies be clamouring for talent with eye-watering salaries? In any case, I'm not just talking about AI researchers—AGI will not only help with algorithmic efficiency improvements, but will probably make spinning up chip fabs that much easier.

	▲	HarHarVeryFunny 2 hours ago \| parent [-]
		The eye-watering salary you probably have in mind is for a manager at Meta, same company that just laid of 600 actual developers. Why just Meta, not other companies - because they are blaming poor LLama performance on the manager, it seems. Algorithmic efficiency improvements are being made all the time, and will only serve to reduce inference cost, which is already happening. This isn't going to accelerate AI advance. It just makes ChatGPT more profitable. Why would human level AGI help spin up chip fabs faster, when we already have actual humans who know how to spin them up, and the bottleneck is raising the billions of dollars to build them? All of these hard take-off fantasies seem to come down to: We get human-level AGI, then magic happens, and we get hard take-off. Why isn't the magic happening when we already have real live humans on the job?