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Comment by dr_dshiv | Hacker News Reader

Solving climate change will take a lot of energy.

I found this article to be a little too one sided. For instance, it didn’t talk about the 10x reductions in power achieved this past year — essentially how gpt4 can now run on a laptop.

Viz, via sama “The cost to use a given level of AI falls about 10x every 12 months, and lower prices lead to much more use. You can see this in the token cost from GPT-4 in early 2023 to GPT-4o in mid-2024, where the price per token dropped about 150x in that time period. Moore’s law changed the world at 2x every 18 months; this is unbelievably stronger.” https://blog.samaltman.com/three-observations

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The current AI-boom has been aroung for ~3 years. Implying that effeciency gains in AI will be like Moore's law (ie they will accrue at around the same high rate for decades) based on data from that time frame is pretty unresponsible in my opinion. Also, Altman is not in any way an expert in any of this and has an obvious financial interest in making this technology palatable. There's no good reason to cite his writing in these kinds of discussions.

Distillation seems like a pretty robust approach. There is no good reason to think that GPT5 or 6 won’t have massive rapid efficiency gains.

He’s one of the most knowledgeable persons in the world on the topic. It’s like saying that the ceo of BMW isn’t citable on conversations about expected cost decreases in electric cars.

Any environmental topic is susceptible to a huge amount of groupthink. The world isn’t so binary as people make it out to be. It is far from truth that LLMs=bad for environment, any more than computers=bad for the environment.

I think its more like saying that the ceo of Tesla isn't citable on conversations about the expected advancement in electric car technology.

What I mean is that I have a healthy level of skepticism with Altman. He has to constantly battle for funding. Surely, he must be knowledgeable about LLMs, but he's the CEO of the largest AI company in the world, his PR needs to give "most knowledgeable person in the world on the topic" but I think that title should go to all of the engineers and developers working on these technologies and not a capital founder.

All that said, I agree that LLM's being bad for the environment is a complex topic. I think it would be more accepted if people had safety nets and could be excited for AI to take their job instead of having to be terrified, or if AI isn't just used as another tool for increasing wealth inequality.

One reason to take these expected cost reductions more seriously is because it DOESN'T fit the desired narrative for OpenAI. Ideally, from a front-runner competition perspective, it would NOT be possible to create the same level of quality at < 1/10 the cost/energy within a year. But, distillation and other approaches seems to make this possible. There is a LOT of room for optimization with LLMs.

Alright, so can you actually name some numbers so that the stuff you are claiming is at least fasifiable?

Altman mentions a 150x increase in efficiency, you claim that trend will continue through to gpt6. At that point these models would be 22500 as efficient as they currently are, which would mean generating a 10 hour long video would cost around the same amount of electricity as running your microwave for 15 minutes. Will you have some introspection if that doesn't come to pass?

Sure, I'm game. What's your prediction?

Of course I predict this will turn into a logarithmic curve not exponential over time. But I’m always happy to bet on future outcomes with specifics. Like, that gpt5-level intelligence will be able run on contemporary MacBooks within 2-3 years of release.

It's still _additional_ power usage that

1/ did not exist before

2/ does not replace/reduce previous/other power (some, very much more critical and essential) usages.

3/ a LOT of tasks are still way more energy/time-efficiently done with regular existing methods (dedicated software, or even by hand), but are still asked/improperly routed to AI chatbots that ... statistically guess the answer.

It is also additional value creation.

It also leads to automation and efficiency, even if it isn’t a fully linear path.

AI isnt a waste. We can’t let environmental consciousness get in the way of rather natural human development. Especially CO2. (I have different opinions about biodiversity because of the irreversible loss. I also believe that we have the technology to pause and reverse climate change — but don’t pursue it because of degrowth ideologies)

No amount of value, in the economic sense, will solve climate change.

Well, somebody must buy solar panels, batteries, (nuclear reactors) and finance the whole research process.

While “economic value” =/= “solving climate change” without enough tax revenue costly transitions are impossible.

Very capitalistic reasoning.

It's revealing that for some, it's easier to imagine Earth without life than Earth without capitalism.

> It is also additional value creation.

For _who_ really?

Shareholders of AI tools producing companies?

Shareholders of companies that pretend to replace people and verifiable working processes with poorly understood black boxes?

(I can't help but notice the _same_ playbook as with crypto, NFTs, Web3, metaverse, and the same enabling-hardware provider).

Value, automation, efficiency will not solve the climate change challenges, if they are not directed towards it aggressively, as well as humanity acceptance and well-being.

Alas, they are directed towards a very little few bank accounts. Violence and subjugation, in many of their forms, is directed towards the others. It's not by accident.

> It is also additional value creation.

Give some concrete examples and stats?

> It also leads to automation and efficiency, even if it isn’t a fully linear path.

Ditto.

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