> These things are so hideously inefficient.

Quite the opposite, really. I did some napkin math for energy and water consumption, and compared to humans these things are very resource efficient.

If LLMs improve productivity by even 5% (studies actually peg productivity gains across various professions at 15 - 30%, and these are from 2024!) the resource savings by accelerating all knowledge workers are significant.

Simplistically, during 8 hours of work a human would consume 10 kWH of electricity + 27 gallons of water. Sped up by 5%, that drops by 0.5kWH and 1.35 gallons. Even assuming a higher end of resources used by LLMs, a 100 large prompts (~1 every 5 minutes) would only consume 0.25 kWH + 0.3 gallons. So we're still saving ~0.25 kWH + 1 gallon overall per day!

That is, humans + LLMs are way more efficient than humans alone. As such, the more knowledge workers adopt LLMs, the more efficiently they can achieve the same work output!

If we assume a conservative 10% productivity speed up, adoption across all ~100M knowledge work in the US will recoup the resource cost of a full training run in a few business days, even after accounting for the inference costs!

Additional reading with more useful numbers (independent of my napkin math):

https://www.nature.com/articles/s41598-024-76682-6

https://cacm.acm.org/blogcacm/the-energy-footprint-of-humans...

Adding new electricity demand to the grid should not be viewed as breaking windows and robbing others. When I bought an EV, I increased my electricity demand a huge amount, but it's not like I'm stealing from my neighbors. No rules were broken. We just need to make sure that I pay enough for my additional demand.

> AI sector will need at least 50 gigawatts of capacity over the next several years.

The error bars on this prediction are extremely large. It would represent a 5% increase in capacity in "the next several years" which is only a percent or two per year, but it could also only be 5GW over the next several years. 50GW represents about 1 year of actual grid additions.

> All of you building these things for these people should be embarrassed and ashamed.

I'm not building these things, and I think there should be AI critique, but this is far over the top. There's great value for all of humanity in these tools. The actual energy use of a typical user is not much more than a typical home appliance, because so many requests are batched together and processed in parallel.

We should be ashamed of getting into our cars every day, that's a true harm to the environment. We should have built something better, allowed more transit. A daily commute of 30 miles is disastrous for the environment compared other any AI use that's really possible at the moment.

Let's be cautious of AI but keep our critiques grounded in reality, so that we have enough powder left to fight the rest of things we need to change in society.

Are you against inefficiency or just LLMs? If it's the former, I assure you LLMs are nowhere near the top of the list lol

You should start from beef industry.

How are you measuring efficiency? They're better than most humans, which is what I would need more of as a substitute.

Every piece of progress looks like this to begin with.

> "Committing to buying the glass to replace the window I broke in your shop to rob the place, you're welcome."

Buying electricity isn't inherently destructive. That's a very bad analogy.

> These things are so hideously inefficient. All of you building these things for these people should be embarrassed and ashamed.

I'm not arguing that they are efficient right now, but how would you measure that? What kind of output does it have to make per kWh of input to be acceptable? Keep in mind that the baseline of US power use is around 500GW and that currently AI is maybe 10.

The numbers must go up, there is no other way.