This is a most excellent place for technology news and articles.
There's such a huge gap between what I read about GPT-5 online, versus the overwhelmingly disappointing results I get from it for both coding and general questions.
I'm beginning to think we're in the end stages of Dead Internet, where basically nothing you see online has any connection to reality.
The stock market is barely connected to reality and that is required to be updated every 3 months by every single company. Just imagine what the internet's going to be like.
People who fawn over generative AI haven't tried to use it for more than 5 seconds. I wish it could run a ttrpg game for me or even just remember the details of its original prompt but its not even close.
Well yeah, it's a for-profit company. They exist solely to make money, that's their entire goal.
It's almost all marketing and has been for a while. ChatGPT peaked with 4o (and 4.5 if you used their API), 4.1 was a step backwards despite them calling it an improvement, and 5 was another step backwards.
They are not any closer to AGI, and we're not going to see AGI from LLMs no matter how much they claim just how close we are to seeing AGI.
Isn't this the back plot of the game, Rain World? With the slug cats and the depressed robots stuck on a decaying world when the sapient, organic species all left?
I didn't know there was such a backstory
Spoilers dude.
For reference, this is roughly equivalent to playing a PS5 game for 4 minutes (based on their estimate) to 10 minutes (their upper bound)
calulation
source https://www.ecoenergygeek.com/ps5-power-consumption/
Typical PS5 usage: 200 W
TV: 27 W - 134 W → call it 60 W
URI's estimate: 18 Wh / 260 W → 4 minutes
URI's upper bound: 48 Wh / 260 W →10 minutes
It is also the equivalent of letting a LED light bulb run for an entire day (depending on bright it is, some LED bulbs use under 2 watts of power).
I love playing PS5 games!
I was just thinking, in more affordable electric regions of the US that's about $5 worth of electricity, per thousand requests. You'd tip a concierge $5 for most answers you get from Chat GPT (if they could provide them...) and the concierge is likely going to use that $5 to buy a gallon and a half of gasoline, which generates a whole lot more CO2 than the nuclear / hydro / solar mixed electrical generation, in reasonably priced electric regions of the US...
That doesn't seem right. By my calculations it should be like 5¢. Can you show your work?
The last 6 to 12 months of open models has pretty clearly shown you can substantially better results with the same model size or the same results with smaller model size. Eg Llama 3. 1 405B being basically equal to Llama 3.3 70B or R1-0528 being substantially better than R1. The little information available about GPT 5 suggests it uses mixture of experts and dynamic routing to different models, both of which can reduce computation cost dramatically. Additionally, simplifying the model catalogue from 9ish(?) to 3, when combined with their enormous traffic, will mean higher utilization of batch runs. Fuller batches run more efficiently on a per query basis.
Basically they can't know for sure.
And how many milliwatts does an actual brain use?
1.21 jigawatts
Ahh but you need 8 for a round trip
It's shockingly tricky to answer precisely, but the commonly held value is that a human brain runs on about 20w, regardless of the computational load placed on it.
So maybe .5 kwh/d. Still vastly more efficient than a code-based one.
I have an extreme dislike for OpenAI, Altman, and people like him, but the reasoning behind this article is just stuff some guy has pulled from his backside. There's no facts here, it's just "I believe XYX" with nothing to back it up.
We don't need to make up nonsense about the LLM bubble. There's plenty of valid enough criticisms as is.
By circulating a dumb figure like this, all you're doing is granting OpenAI the power to come out and say "actually, it only uses X amount of power. We're so great!", where X is a figure that on its own would seem bad, but compared to this inflated figure sounds great. Don't hand these shitty companies a marketing win.
Yeah, I saw some people speculating GPT-5 is having worse performance in some tasks than older models but still being forced to everyone because it's a consolidation and cost cutting version, but how could it be cutting costs if it consumes 8 times more power?
This figure is already not bad. 40 watt hours = 0.04kWh - you know kWh? That unit on your electric bill that is around $0.18 per kWh (and data centers tend to be in lower cost electric areas, closer to $0.11/kWh.) Still, 40Wh would register on your home electric bill at $0.0072, less than a penny. For comparison, an average suburban 4 ton AC unit draws 4kW - that 40Wh request? 1/100th of an hour of AC for your home, about 36 seconds of air conditioning. I don't know that this article is making anybody "look bad" in terms of power used.
I don't care how rough the estimate is, LLMs are using insane amounts of power, and the message I'm getting here is that the newest incarnation uses even more.
BTW a lot of it seems to be just inefficient coding as Deepseek has shown.
For training yes, but during operation by this studies measure Deepseek actually has an even higher power draw, according to the article. Even models with more efficient programming use insane amounts of electricity
This was higher than all other tested models, except for OpenAI's o3 (25.35 Wh) and Deepseek's R1 (20.90 Wh).
BTW a lot of it seems to be just inefficient coding as Deepseek has shown.
Kind of? Inefficient coding is definitely a part of it. But a large part is also just the iterative nature of how these algorithms operate. We might be able to improve that via code optimization a little bit. But without radically changing how these engines operates it won't make a big difference.
The scope of the data being used and trained on is probably a bigger issue. Which is why there's been a push by some to move from LLMs to SLMs. We don't need the model to be cluttered with information on geology, ancient history, cooking, software development, sports trivia, etc if it's only going to be used for looking up stuff on music and musicians.
But either way, there's a big 'diminishing returns' factor to this right now that isn't being appreciated. Typical human nature: give me that tiny boost in performance regardless of the cost, because I don't have to deal with. It's the same short-sighted shit that got us into this looming environmental crisis.
And water usage which will also increase as fires increase and people have trouble getting access to clean water
https://techhq.com/news/ai-water-footprint-suggests-that-large-language-models-are-thirsty/
And an LLM that you could run local on a flash drive will do most of what it can do.
Can you give an example?
I mean no not at all, but local LLMs are a less energy reckless way to use AI
Fucking Doc Brown could power a goddamn time machine with this many jiggawatts, fuck I hate being stuck in this timeline.
I think AI power usage has an upside. No amount of hype can pay the light bill.
AI is either going to be the most valuable tech in history, or it's going to be a giant pile of ash that used to be VC capital.
Bit of a clickbait. We can't really say it without more info.
But it's important to point out that the lab's test methodology is far from ideal.
The team measured GPT-5’s power consumption by combining two key factors: how long the model took to respond to a given request, and the estimated average power draw of the hardware running it.
What we do know is that the price went down. So this could be a strong indication the model is, in fact, more energy efficient. At least a stronger indicator than response time.
