Fuck AI

This is literally one of the most famous essays in AI (it has it's own Wikipedia article) and I mentioned it by name but sure here you go: https://www.cs.utexas.edu/~eunsol/courses/data/bitter_lesson.pdf

As for more recent stuff, people are doing experiments on it all the time, here's Nvidia very recently trying to figure out the best mix of training data (how much task-specific training, how much general-knowledge training for optimal results) https://arxiv.org/html/2606.24747

Google's 2022 "A generalist agent" - 1091 citations https://arxiv.org/abs/2205.06175

The entire field is built on statistics. It has many flaws, but this is like, the entire thing people are working on actively. Their goals may not be compatible with the flourishing of humanity, but finding the best way to automate various tasks is their one goal.

Even from gpt-1 people have been trying to make fine-tuned models for specific tasks and they keep failing compared to general models.

Elements of this idea do live on though, in MoE architectures, where they take a base model with knowledge of everything, then fine tune various versions of it for different things, and route your request to one of the models fine tuned for your task. This is mainly a workaround for the fact a large model with all parameters doesn't fit in memory so easily even in the massive Nvidia datacenter gpus, if it did, we can be pretty sure it would beat the smaller "experts" in most of the tasks

Also like, china isn't doing different to this? Deepseek (China) and glm5.2 (China) and mistral (France) and various other models are doing the same thing, because that's the thing that works (for the narrow definition of ai success that tech companies and politicians believe in)