They’re throwing billions upon billions into a technology with extremely limited use cases and a novelty, at best. My god, even drones fared better in the long run.
Nah, generative ai is pretty remarkably useful for software development. I’ve written dozens of product updates with tools like claudecode and cursorai, dismissing it as a novelty is reductive and straight up incorrect
As someone starting a small business, it has helped tremendously. I use a lot of image generation.
If that didn’t exist, I’d either has to use crappy looking clip art or pay a designer which I literally can’t afford.
Now my projects actually look good. It makes my first projects look like a highschooler did them last minute.
There are many other uses, but I rely on it daily. My business can exist without it, but the quality of my product is significantly better and the cost to create it is much lower.
Your product is other people’s work thrown in a blender.
Congrats.
Wait til you realize that’s just what art literally is…
You’re confusing ai art with actual art, like rendered from illustration and paintings
it’s as much “real” art as photography, taking a relatively finite number of decisions and finding something that looks “good”.
Really good photography is actually pretty hard and the best photographers are in high demand.
It involves a ton of settings for the camera, frequently post processing to balance out anything that wasn’t perfect during the shoot. Plus there is a ton of blocking, lighting, and if doing portraits and other planned shoots there is a lot of directing involved in getting the subjects to be in the right positions/showing the right emotions, etc. Even shooting nature requires a massive amount of planning and work beyond a few camera settings.
Hell, even stock photos tend to be a lot of work to set up!
If you think that someone taking a photo in focus with adequate lighting and posted it to instagram is the same as professional photography, then you have no idea what is involved.
I liked generative AI more when it was just a funny novelty and not being advertised to everyone under the false pretenses of being smart and useful. Its architecture is incompatible with actual intelligence, and anyone who thinks otherwise is just fooling themselves. (It does make an alright autocomplete though).
AGI models will enter the market in under 5 years according to experts and scientists.
trust me bro, we’re almost there, we just need another data center and a few billions, it’s coming i promise, we are testing incredible things internally, can’t wait to show you!
We are having massive exponential increases in output with all sorts of innovations, every few weeks another big step forward happens
Around a year ago I bet a friend $100 we won’t have AGI by 2029, and I’d do the same today. LLMs are nothing more than fancy predictive text and are incapable of thinking or reasoning. We burn through immense amounts of compute and terabytes of data to train them, then stick them together in a convoluted mess, only to end up with something that’s still dumber than the average human. In comparison humans are “trained” with maybe ten thousand “tokens” and ten megajoules of energy a day for a decade or two, and take only a couple dozen watts for even the most complex thinking.
Humans are “trained” with maybe ten thousand “tokens” per day
Uhhh… you may wanna rerun those numbers.
It’s waaaaaaaay more than that lol.
and take only a couple dozen watts for even the most complex thinking
Mate’s literally got smoke coming out if his ears lol.
A single
Whis 860 calories…I think you either have no idea wtf you are talking about, or your just made up a bunch of extremely wrong numbers to try and look smart.
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Humans will encounter hundreds of thousands of tokens per day, ramping up to millions in school.
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An human, by my estimate, has burned about 13,000 Wh by the time they reach adulthood. Maybe more depending in activity levels.
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While yes, an AI costs substantially more
Wh, it also is done in weeks so it’s obviously going to be way less energy efficient due to the exponential laws of resistance. If we grew a functional human in like 2 months it’d prolly require way WAY more than 13,000Whduring the process for similiar reasons. -
Once trained, a single model can be duplicated infinitely. So it’d be more fair to compare how much millions of people cost to raise, compared to a single model to be trained. Because once trained, you can now make millions of copies of it…
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Operating costs are continuing to go down and down and down. Diffusion based text generation just made another huge leap forward, reporting around a twenty times efficiency increase over traditional gpt style LLMs. Improvements like this are coming out every month.
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