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> I have to wonder if those making these grandiose claims about the near future of AI have actually used GPT-4 and its predecessors in their work I have used G

> I have to wonder if those making these grandiose claims about the near future of AI have actually used GPT-4 and its predecessors in their work I have used GPT-3 a fair bit, and used GPT-4 today. The differences are impressive, scary impressive so far. I am basing my `GPT(n+1)` observation on the rapid rate the tech is filling in holes that previous detractors pointed out. The differences in code reviews is amazing. In GPT-3 it basically explained the method and said it looked good, "add some comments" was its only suggestion. GPT-4 on the other hand gave a code snippet to explain why JS "await" was unnecessary, suggested better variable names, and suggested moving some imports to a more simple file structure to reduce verbose import paths. I think that's a beyond expectations improvement, it's so impressive it beats out the humans who reviewed the code and we implemented one of the suggestions. If GPT-4 had ingested the entire code-base code reviews would easily be automated, humans would still do their passes but as a co-worker GPT would be invaluable. It would find swaths of missed efficiencies, fix slow SQL queries, look for testing gaps, and perhaps even assist in refactoring. Personally I think we are underestimating the potential, I feel like we are where the world was in 1990 looking at the emerging internet. So many people underestimated the impact of the internet, many technology writers said it was hyperbole, couldn't replace bricks and mortar stores, email was never going to be for everyone, and so on. All of it wrong, profoundly missing the potential. This stuff is beating out expectations at every release and I think that is reason enough to take it seriously and be much more considered when downplaying the hype. As for junior devs, we don't hire IC1 for the same reasons you outlined. However, small studios do because they are cheap and serve a purpose where it's just WordPress maintenance and HTML POCs. Those jobs will disappear.

badRNG 4y ago
> If GPT-4 had ingested the entire code-base code reviews would easily be automated, humans would still do their passes but as a co-worker GPT would be invaluable. It would find swaths of missed efficiencies, fix slow SQL queries, look for testing gaps, and perhaps even assist in refactoring. This is where my 3-5x efficiency improvement estimate came from for GPT4-based Copilot, especially for CRUD apps using popular frameworks, which while game changing is far from the great efficiency gains programming has seen in the past. Compilers have conservatively led to 100x-1000x gains of efficiency at scale as have operating systems and various key libraries. GPT-assisted code generation doesn't yet seem to offer the same result. Even if it did, if history is our guide, this would lead to developers being able to generate far more economic value with less, which has consistently led to more developer jobs than before. > Personally I think we are underestimating the potential, I feel like we are where the world was in 1990 looking at the emerging internet. It doesn't feel correct to me to think of GPT-x as some technology similar to the internet as much as it is a way of experiencing the already existing internet, like a smart, context-aware search for specific details (though there aren't any good analogies for the role LLMs play/will play in tech moving forward.) If search engines had continued to improve with the momentum they had in the early days, we should've expected some experience not unlike GPT a decade ago (or more.) > However, small studios do because they are cheap and serve a purpose where it's just WordPress maintenance and HTML POCs. Those jobs will disappear. That seems very possible.

badRNG 4y ago

> If GPT-4 had ingested the entire code-base code reviews would easily be automated, humans would still do their passes but as a co-worker GPT would be invaluable. It would find swaths of missed efficiencies, fix slow SQL queries, look for testing gaps, and perhaps even assist in refactoring. This is where my 3-5x efficiency improvement estimate came from for GPT4-based Copilot, especially for CRUD apps using popular frameworks, which while game changing is far from the great efficiency gains programming has seen in the past. Compilers have conservatively led to 100x-1000x gains of efficiency at scale as have operating systems and various key libraries. GPT-assisted code generation doesn't yet seem to offer the same result. Even if it did, if history is our guide, this would lead to developers being able to generate far more economic value with less, which has consistently led to more developer jobs than before. > Personally I think we are underestimating the potential, I feel like we are where the world was in 1990 looking at the emerging internet. It doesn't feel correct to me to think of GPT-x as some technology similar to the internet as much as it is a way of experiencing the already existing internet, like a smart, context-aware search for specific details (though there aren't any good analogies for the role LLMs play/will play in tech moving forward.) If search engines had continued to improve with the momentum they had in the early days, we should've expected some experience not unlike GPT a decade ago (or more.) > However, small studios do because they are cheap and serve a purpose where it's just WordPress maintenance and HTML POCs. Those jobs will disappear. That seems very possible.