The current trends in software development are being driven primarily by the interests of venture capitalists who are trying to escape the debts they acquired buying into Web 3.0 (remember Web 3.0?), the Metaverse/VR, and cryptocurrency. They’re looking for the next big get-rich-quick option, and manipulating the market to try and force it to happen. The people making decisions about which projects get funded literally do not care if the end product is useful or destructive or whatever, as long as it looks convincing enough to get other people to buy it. This is why there’s been so much recent hype about “AI” “escaping” its test environments and hacking other companies &etc. It makes the product sound more capable than it is in reality. It’s also why the Trump administration is all-in on “AI” development and actively threatening people who object - because Trump loves a good scam that he can make money off of, and he loves to respond with violence or threats of violence when people get in his way.
The current generation of machine learning models requires vast amounts of input data to achieve useful outcomes. The entire content of the public Internet has already been scraped and ingested. There is no more training data to feed in. The current systems will gain marginal improvements in efficiency and in focusing the models to perform better at certain tasks, but that will be it. They will not magically become capable of learning new tasks for which there is not millions of data points for training. The training is done, refining is in progress, but there will not be any major leaps in capability. There certainly won’t be a general artificial intelligence.
Maybe the next generation of machine learning will produce software that can teach itself without an Internet’s worth of input data. That will happen after the current market implodes, and another generation or two of research and development is completed.
Perhaps there is some value in the current generation as you say. Whatever the benefit of it might be, the cost is far too high. It is not and never will be worth the damage being done to the Internet, the economy, human society, and the environment we all live in.
And I haven’t even gotten into generative models being used to create child exploitation material, run massive scam operations, produce massive amounts of propaganda, or enable the authoritarian surveillance state. This stuff is trash, the people in charge of the development are trash, the people peddling it are trash, the people funding it are trash, and the people that support it are trash.
You’re treating the current resource cost as though it’s a fixed characteristic of AI, when cost per unit of useful output has been collapsing the entire time. Stanford found that the inference cost of GPT 3.5 performance fell more than 280x in about two years because hardware and algorithms continue getting more efficient all the time.
Total AI energy use still rose because we’re using vastly more of it, but thats obviously going to happen in an emerging market. If AI becomes 10x cheaper and more efficient while simultaneously becoming useful across millions more tasks, total consumption can increase even as the resource cost of doing any particular task falls dramatically, but efficiency will continue to improve as the technology develops.
Im not saying ‘its good that its using all this energy’, im saying dismissing it as doomed by its energy usage is short-sighted. Its not in its end form.
The other things you mentioned are all regulation issues stemming from a completely fucked political system, not fundamental issues with ai.
So what AI company can I invest in and start making money, today? Which one is a going concern with solid financials? Because I’m pretty sure none of them are actually making more money than they’re spending on electricity. Because this tech doesn’t work on a very basic level.
Maybe it will get better. But it’s been years and I haven’t seen it improve enough to be economically relevant.
https://pluralistic.net/2026/09/12/god-in-the-box/#llms-are-fake
The current trends in software development are being driven primarily by the interests of venture capitalists who are trying to escape the debts they acquired buying into Web 3.0 (remember Web 3.0?), the Metaverse/VR, and cryptocurrency. They’re looking for the next big get-rich-quick option, and manipulating the market to try and force it to happen. The people making decisions about which projects get funded literally do not care if the end product is useful or destructive or whatever, as long as it looks convincing enough to get other people to buy it. This is why there’s been so much recent hype about “AI” “escaping” its test environments and hacking other companies &etc. It makes the product sound more capable than it is in reality. It’s also why the Trump administration is all-in on “AI” development and actively threatening people who object - because Trump loves a good scam that he can make money off of, and he loves to respond with violence or threats of violence when people get in his way.
The current generation of machine learning models requires vast amounts of input data to achieve useful outcomes. The entire content of the public Internet has already been scraped and ingested. There is no more training data to feed in. The current systems will gain marginal improvements in efficiency and in focusing the models to perform better at certain tasks, but that will be it. They will not magically become capable of learning new tasks for which there is not millions of data points for training. The training is done, refining is in progress, but there will not be any major leaps in capability. There certainly won’t be a general artificial intelligence.
Maybe the next generation of machine learning will produce software that can teach itself without an Internet’s worth of input data. That will happen after the current market implodes, and another generation or two of research and development is completed.
Perhaps there is some value in the current generation as you say. Whatever the benefit of it might be, the cost is far too high. It is not and never will be worth the damage being done to the Internet, the economy, human society, and the environment we all live in.
And I haven’t even gotten into generative models being used to create child exploitation material, run massive scam operations, produce massive amounts of propaganda, or enable the authoritarian surveillance state. This stuff is trash, the people in charge of the development are trash, the people peddling it are trash, the people funding it are trash, and the people that support it are trash.
Get correct.
Get correct while making dead arguments haha.
You’re treating the current resource cost as though it’s a fixed characteristic of AI, when cost per unit of useful output has been collapsing the entire time. Stanford found that the inference cost of GPT 3.5 performance fell more than 280x in about two years because hardware and algorithms continue getting more efficient all the time.
Total AI energy use still rose because we’re using vastly more of it, but thats obviously going to happen in an emerging market. If AI becomes 10x cheaper and more efficient while simultaneously becoming useful across millions more tasks, total consumption can increase even as the resource cost of doing any particular task falls dramatically, but efficiency will continue to improve as the technology develops.
Im not saying ‘its good that its using all this energy’, im saying dismissing it as doomed by its energy usage is short-sighted. Its not in its end form.
The other things you mentioned are all regulation issues stemming from a completely fucked political system, not fundamental issues with ai.
So what AI company can I invest in and start making money, today? Which one is a going concern with solid financials? Because I’m pretty sure none of them are actually making more money than they’re spending on electricity. Because this tech doesn’t work on a very basic level.
Maybe it will get better. But it’s been years and I haven’t seen it improve enough to be economically relevant.