Nukes are a far more primitive technology (i.e., enrichment requires only more basic industrial capabilities) than AI hardware, yet they are probably the best example of tech limitations via international agreements.
But the algorithms are mostly public knowledge, datacenters are no secret, and the chips aren't even made in the US. I don't see what leverage California has to regulate AI broadly.
So it seems like the only thing such a bill would achieve is to incentivize AI research to avoid California.
> Nukes are a far more primitive technology (i.e., enrichment requires only more basic industrial capabilities) than AI hardware, yet they are probably the best example of tech limitations via international agreements.
>So it seems like the only thing such a bill would achieve is to incentivize AI research to avoid California.
Which, incidentally, would be pretty bad from a climate change perspective since many of the alternative locations for datacenters have a worse mix of renewables/nuclear to fossil fuels in their electricity generation. ~60% of VA's electricity is generated from burning fossil fuels (of which 1/12th is still coal) while natural gas makes up less than 40% of electricity generation in California, for example
Electric power crosses state lines, very little loss.
It's looking like cooling water may be more of a limiting factor. Yet, even this can be greatly reduced when electric power is cheap enough.
Solar power is already "cheaper than free" in many places and times. If the initial winner-take-all training race ever slows down, perhaps training can be scheduled for energy cost-optimal times and places.
Transmission losses aren't negligible without investment in costly infrastructure like HVDC connections. It's always more efficient to site electricity generation as close to generation as feasibly possible.
That's the average. It's bought and sold on a spot market. If you try to sell CA power in AZ and the losses are 10% then SRP or TEP or whoever can undercut your price with local power/lower losses.
I just don't see 10% remaining a big deal while solar continues its exponential cost reduction. Solar does not consume fuel, so when local supply exceeds local demand the cost of incremental production drops to approximately zero. Nobody's undercutting zero, even with 10% losses.
The cost of solar as a 24hr power supply must include the cost of storage for the 16+ hours that it's not at peak power. It also needs to overproduce by 3x to meet that demand.
Solar provides cheap power only when it's producing.
this is interesting but missing some scale aspects.. capital and concentrated power are mutual attractors in some sense.. these AI datacenters in their current incarnations are massive.. so the number and size of solar panels needed, changes the situation. Common electrical power interchange (grid) is carefully regulated and monitored in all jurisdictions. In other words, there is little chance of an ad-hoc local network of small or mid-size solar systems making enough power unto themselves, without passing through regulated transmission facilities IMHO.
Nukes are a far more primitive technology (i.e., enrichment requires only more basic industrial capabilities) than AI hardware, yet they are probably the best example of tech limitations via international agreements.
But the algorithms are mostly public knowledge, datacenters are no secret, and the chips aren't even made in the US. I don't see what leverage California has to regulate AI broadly.
So it seems like the only thing such a bill would achieve is to incentivize AI research to avoid California.