At least anecdotally, Andreas over at 82MHz.net tried running a AI model locally on his laptop and it took over 10 minutes for just one prompt.
OK just the 4th sentence clearly shows this person has no clue what they're talking about.
this post was submitted on 04 May 2025
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Yep, clueless. I stopped reading at that point. For the audience, large language models come in all sizes and you can run some small but useful ones fairly quickly even without a GPU. They keep getting more capable for the size as well. Remember the uproar about Deepseek R1? Well, progress hasn’t stopped.
It's not even that. It's like trying to run an AAA game on a 10 year old laptop and complaining the game is garbage because your frame rates are too low.
These endless "AI bad" articles are annoying. It's just click bait at this point.
Energy use: false. His example was someone using a 13 year old laptop to get a result and then extrapolating energy use from that. Running ai locally is the same energy as playing a 3d AAA game for the same time. No one screams about the energy footprint of playing games.
AAA game development energy use ( thousands of developers all with watt burning gpus spending years creating assets) dwarfs AI model building energy use.
Copyright, yes it's a problem and should be fixed. But stealing is part of capitalism. Google search itself is based on stealing content and then selling ads to find that content. The entire "oh we might send some clicks your way that you might be able to compensated for" is backwards.
His last reason was new and completely absurd: he doesn't like AI because he doesn't like Musk. Given the public hatred between OpenAI and Musk it's bizarre. Yes Musk has his own AI. But Musk also has electric cars, and space travel. Does the author hate all EV's too? If course not, that argument was added by the author as a troll to get engagement.
Copyright, yes it's a problem and should be fixed.
The quick fix: stick to open-source like Jan.ai.
Long-term solution: make profiting AI companies pay for UBI. How to actually calculate that, though, is anyone's guess...
make profiting AI companies pay for UBI
As I said, many companies steal content and repackage it for sale. Google did it long before AI. AI is only the most recent offender. Courts have been splitting hairs for decades over music similarities and that's ignoring that entire genres are based on copying the work of influential artists.
Don't make "profiteering AI companies" pay for UBI. Make all companies pay for UBI. Just tax their income and turn it around into UBI payments.
One of the major benefits of UBI is how simple it is. The simpler the system is the harder it is to game it. If you put a bunch of caveats on which companies pay more or pay less based on various factors, then there'll be tons of faffing about to dodge those taxes.
OP said "people like Musk" not just Musk. He's just the easiest example to use.
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I agree on the part that Musk sucks, OpenAI also sucks.
And yup, open source (if you can really call them that, I’d say they’re more like openly available) locally hosted LLMs are cool and have gotten pretty efficient nowadays.
My 5 year old M1 MacBook Pro runs models like Qwen3:14b at decent speeds and it’s quite capable (although I only ever use it for bullshitting lol).
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Regarding energy/water use:
ChatGPT uses 3 Wh. This is enough energy to: [...] Play a gaming console for 1 minute.
If you want to prompt ChatGPT 40 times, you can just stop your shower 1 second early. If you normally take a 5 minute shower, set a timer for 299 seconds instead, and you’ll have saved enough water to justify 40 ChatGPT prompts.
(Source: https://andymasley.substack.com/p/a-cheat-sheet-for-conversations-about)
I recall all the same arguments about how much energy and carbon are involved in performing one Google search. Does anyone care? Nope.
I’ve always ignored the energy issue on the assumption that it will be optimized away. Right now, leapfrogging the competition to new levels of functionality is what’s important. But when (if?) these tools settle into true mass usage, the eggheads will have every incentive to focus on optimization to save on operating costs. When that finally starts happening, we will know that AI has passed out of its era as a speculative bet and into prime time as an actual product.
I find it funny that in the year 2000 while attending philosophy at University of Copenhagen I predicted strong AI around 2035. This was based on calculations of computational power, and estimates of software development.
At the time I had already been interested in AI development and matters of consciousness for many years. And I was a decent programmer. I already made self modifying code back in 1982. So I made this prediction at a time where AI wasn't a very popular topic, and in the middle of a decades long futile desert walk without much progress.
And for 15 about years, very little continued to happen. It was pretty obvious the approach behind for instance Deep Blue wasn't the way forward. But that seemed to be the norm for a long time.
But it looks to me that the understanding of how to build a strong AI is much much closer now. We might actually be halfway there!
I think we are pretty close to having the computational power needed now in AI specific datacenter clusters, but the software isn't quite there yet.
I'm honestly not that interested in the current level of AI, although LLM can yield very impressive results at times, it's also flawed, and I see it as somewhat transitional.
For instance partially self driving cars are kind of irrelevant IMO. But truly self driving cars will make all the difference regarding how useful it is, and be a cool achievement for current level of AI evolution when achieved.
So current level AI can be useful, but when we achieve strong AI it will make all the difference!
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