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themafia a day ago

5 decades.

You have one decade to clean up your power use problem. If you don't you will find yourself in the next AI winter.

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shdh a day ago | parent [-]

Power use is less important than model capability

AGI is either more scale or differing systems, or both

They can always optimize for power consumption after AGI has been reached

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ben_w 16 hours ago | parent | next [-]

Disagree. AI that displaces workers is worth spending anything up to that worker's salary on, and this can have a devastating impact on energy prices for everyone.

Worked example, but this is a massive oversimplification in several different ways all at once:

Global electricity supply was around 31,153 TWh in 2024. The world's economy is about $117e12/year. Any AI* that is economically useful enough to handle 33% that, $38.6e12/year, is economically worthwhile to spend anything up to $38.6e12/year to keep that AI running.

If you spend $38.6e12 (per year) to buy all of those 31,153 TWh of electricity (per year), the global average electricity market price is now $1.239/kWh, and a lot of people start to wonder what the point of automating everything was if nobody can afford to keep their heating/AC (delete as appropriate) switched on. Or even the fridge/freezer, for a lot of people.

* I don't care what definition you're using for AGI, this is just about "economically useful"

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themafia a day ago | parent | prev [-]

> AGI is either more scale

So you plan to scale without increasing power usage. How's that?

> They can always optimize for power consumption after AGI has been reached

If you don't optimize power consumption you're going to increase surface area required to build it. There are hard physical limits having to do with signal propagation times.

You're ignoring the engineering entirely. The software is not hardly interesting or even evolving.

	▲	ben_w 16 hours ago \| parent [-]
		> If you don't optimize power consumption you're going to increase surface area required to build it. There are hard physical limits having to do with signal propagation times. While true, that probably stopped being an important constraint around the time we switched from thermionic valves to transistors as the fundamental unit of computation. To be deliberately extreme: if we built cubic-kilometre scale compute hardware where each such structure only modelled a single cortical column from a human's brain, and then spread multiple of these out evenly around the full volume within Earth's geosynchronous orbital altitude until we had enough to represent a full human brain, that would still be on par with human synapses. Synapses just aren't very fast.