this post was submitted on 11 Aug 2025
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I'm using "good" in almost a moral sense. The quality of output from LLMs and generative AI is already about as good as it can get from a technical standpoint, continuing to throw money and data at it will only result in minimal improvement.
What I mean by "good AI" is the potential of new types of AI models to be trained for things like diagnosing cancer, and and other predictive tasks that we haven't thought of yet that actually have the potential to help humanity (and not just put artists and authors out of their jobs).
The work of training new, useful AI models is going to be done by scientists and researchers, probably on a limited budgets because there won't be a clear profit motive, and they won't be able to afford thousands of $20,000 GPUs like are being thrown at LLMs and generative AI today. But as the current AI race crashes and burns, the used hardware of today will be more affordable and hopefully actually get used for useful AI projects.
Ok. Thanks for clarifying.
Although I am pretty sure AI is already used in the medical field for research and diagnosis. This "AI everywhere" trend you are seeing is the result of everyone trying to stick and use AI in every which way.
The thing about the AI boom is that lots of money is being invested into all fields. A bubble pop would result in investment money drying up everywhere, not make access to AI more affordable as you are suggesting.