In addition to what the other reply says, the current state of AI isn’t necessarily the best AI could be. Even with the iterative changes on the LLM-based model, things are improving so fast that it might be safe to shrink the workforce for technical tasks soon.
But I’m sure I’m not the only one that thinks the LLM-focused approach itself is just a local minimum the industry is stuck trying to optimize while another approach that isn’t just a big data “throw everything we can at it and hope it spits out useful results” but something more methodological that encodes our knowledge from experts to give it a head start as well as robust reasoning strategies and logic to let it improve on that starting point as it seeks and adds relevant data in ways similar to how we do science and engineering.
I believe that it’s a race between an AI that truly can outcompete us and societal collapse, because the real reason AI is more difficult to stop than those other three is how easy it is to hide development. The massive data centers are required for the current approach being scaled up for the world to use it. AI research and development can be done on home PCs, especially if you’re more interested in results than speed (in which case you aren’t limited by cores or memory but just by storage and time).
In addition to what the other reply says, the current state of AI isn’t necessarily the best AI could be. Even with the iterative changes on the LLM-based model, things are improving so fast that it might be safe to shrink the workforce for technical tasks soon.
But I’m sure I’m not the only one that thinks the LLM-focused approach itself is just a local minimum the industry is stuck trying to optimize while another approach that isn’t just a big data “throw everything we can at it and hope it spits out useful results” but something more methodological that encodes our knowledge from experts to give it a head start as well as robust reasoning strategies and logic to let it improve on that starting point as it seeks and adds relevant data in ways similar to how we do science and engineering.
I believe that it’s a race between an AI that truly can outcompete us and societal collapse, because the real reason AI is more difficult to stop than those other three is how easy it is to hide development. The massive data centers are required for the current approach being scaled up for the world to use it. AI research and development can be done on home PCs, especially if you’re more interested in results than speed (in which case you aren’t limited by cores or memory but just by storage and time).