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If you watch his latest interviews you can see him talking about how he finds it useful for simple cases like in the Bloomberg terminal for generating code for
by ashkankiani 1mo ago
If you watch his latest interviews you can see him talking about how he finds it useful for simple cases like in the Bloomberg terminal for generating code for queries, but it still has fundamental limitations for doing anything autonomously.
As someone who has used LLMs heavily at work and at home in various serious experiments, I agree. It still requires heavy babysitting and a lot of its limitations wrt context length are fundamental, not something that’s going to be easy to overcome.
- preg_match 1mo agoI also agree but the autonomous part comes from coding. We build autonomous systems with code, so it AI is really good at writing code (it is), we increase automation. Not with the AI itself, but with what it produces. Which is good, for many reasons: - environmental costs go down. Algorithms are cheap, LLM inference and training is not. - code is deterministic - code can be read and understood by professionals - code can be deployed trivially, whereas deploying an LLM costs huge infrastructure So using an LLM to help write code is the best of both worlds. You get velocity increase from the LLM, with none of the hallucination or environmental downsides at deployment time.