Right, should say deep neural networks. Perceptrons hit a brick wall because there’s some problems they cannot handle. Multi-layer networks stalled because nobody went ‘what if we just pretend there’s a gradient?’ until twenty-goddamn-twelve.

Broad applications will emerge and succeed. LLMs kinda-sorta-almost work for nearly anything. What current grifters have proven is that billions of dollars won’t overcome fundamental problems in network design. “What’s the next word?” is simply the wrong question, for a combination chatbot / editor / search engine / code generator / puzzle solver / chess engine / air fryer. But it’s obviously possible for one program to do all those things. (Assuming you place your frozen shrimp directly atop the video card.) Developing that program will closely resemble efforts to uplift LLMs. We’re just never gonna get there from LLMs specifically.