| ▲ | ben_w 20 hours ago | |
> I want to push back on this argument, as it seems suspect given that none of these tools are creating profit, and so require funds / resources that are essentially coming from the combined efforts of much of the economy. I.e. the energy externalities here are monstrous and never factored into these things, even though these models could never have gotten off the ground if not for the massive energy expenditures that were (and continue to be) needed to sustain the funding for these things. While it is absolutely possible, even plausible, that the economics of these models and providers is the next economic crash in waiting, somewhere between Enron (at worst, if they're knowingly cooking books) or Global Financial Crisis (if they're self-delusional rather than actively dishonest), we do have open-weights models that get hosted for money, that people play with locally if they're rich enough for the beefy machines, and that are not too far behind the SOTA as to suggest a difference in kind. This all strongly suggests that the resource consumption per token by e.g. Claude Code would be reasonably close to the list price if they weren't all doing a Red Queen race[0], running as hard as they can just to retain relevant against each other's progress, in an all-pay auction[1] where only the best can ever hope to cash anything out and even that may never be enough to cover the spend. Thing is, automation has basically always done this. It's more of a question of "what tasks can automation actually do well enough to bother with?" rather than "when it can, is it more energy efficient than a human?" A Raspberry Pi Zero can do basic arithmetic faster than the sum total performance of all 8 billion living humans, even if all the humans had trained hard and reached the level of the current world record holder, for a tenth of the power consumption of just one of those human's brains, or 2% of their whole body. But that's just arithmetic. Stable Diffusion 1.5 had a similar thing, when it came out the energy cost to make a picture on my laptop was comparable with the calories consumed while typing in a prompt for it… but who cares, SD 1.5 had all that Cronenberg anatomy, what matters is when the AI is "good enough" for the tasks against which it is set. To the extent that Claude Code can replace a human, and the speed at which it operates… Well, my experiments just before Christmas (which are limited, and IMO flawed in a way likely to overstate the current quality of the AI) say the speed of the $20 plan is about 10 sprints per calendar month, while the quality is now at the level of a junior with 1-3 years experience who is just about to stop being a junior. This means the energy cost per unit of work done is comparable with the energy cost needed to have that developer keep a computer and monitor switched on long enough to do the same unit of work. The developer's own body adds another 100-120 watts to that from biology, even if they're a free-range hippie communist who doesn't believe in money, cooked food, lightbulbs, nor having a computer or refrigerator at home, and who commutes by foot from a yurt with neither AC nor heating, ditto the office. Where the AI isn't good enough to replace a human, (playing Pokemon and managing businesses?) it's essentially infinitely more expensive (kWh or $) to use the AI. Still, this does leave a similar argument as with aircraft: really efficient per passenger-kilometre, but they enable so many more passenger-kilometres than before as to still sum to a relevant problem. | ||