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this post was submitted on 25 Feb 2024
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Founder of company which makes major revenue by selling GPUs for machine learning says machine learning is good.
It doesn’t make him wrong.
Just like we can now uss LLM to create letters or emails with a tone, it’s not going to be a big leap to allow it to do similar with coding. It’s quite exciting, really. Lots of people have ideas for websites or apps but no technical knowledge to do it. AI may allow it, just like it allows non artists to create art.
I use AI to write code for work every day. Many different models and services, including https://ollama.ai on my own hardware. It's useful for a developer when they can take the code and refactor it to fit into large code-bases (after fixing its inevitable broken code here and there), but it is by no means anywhere close to actually successfully writing code all on its own. Eventually maybe, but nowhere near anytime soon.
I think this is going to age really badly and I don't like LLMs but I think it will be soon. People also said that AI as we see it now is decades away but we got it quite quickly so I think it's a very small step to go from writing fully grammatically correct English to fully correct code. It's basically just a language the ai has to learn. But I guess what do I know. We'll just have to wait and see
I've been doing this for over a year now, started with GPT in 2022, and there have been massive leaps in quality and effectiveness. (Versions are sneaky, even GPT-4 has evolved many times over and over without people really knowing what's happening behind the scenes.) The problem still remains the "context window." Claude.ai is > 100k tokens now I think, but the context still limits an entire 'session' to only make so much code in that window. I'm still trying to push every model to its limits, but another big problem in the industry now is effectiveness via "perplexity" measurements given a context length.
https://pbs.twimg.com/media/GHOz6ohXoAEJOom?format=png&name=small
This plot shows that as the window grows in size, "directly proportional to the number of tokens in the code you insert into the window, combined with every token it generates at the same time" everything that it produces becomes less accurate and more perplexing overall.
But you're right overall, these things will continue to improve, but you still need an engineer to actually make the code function given a particular environment. I just don't get the feeling we'll see that within the next few years, but if that happens then every IT worker on earth is effectively useless, along with every desk job known to man as an LLM would be able to reason about how to automate any task in any language at that point.