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Tag: ai

How I use LLMs to program

Studies have shown that LLMs help novice programmers more than experienced programmers. This matches my experience. At work I see that interns or new hires have some LLM window open almost all the time. I use them maybe once a week. But you could say the same thing about Stack Overflow. I used it all the time when I started programming. Now I use it occasionally. While it’s easy to point at their obvious issues, I think they are also clearly a net-positive on average. So how do LLMs help me?

Big plus: Languages that I don’t use as often

I don’t often write SQL statements. I can obviously write the simple ones, but SQL is a language that has all the features you could ever possibly want, and I don’t know how to use them and don’t know how to google for them. So I ask a LLM. Similarly for javascript/css/html programming. I used to hate doing web frontend work, now it’s not so bad because LLMs can help me get out of the tricky edge cases.

I have also used LLMs to translate functionality from one language to another. E.g. if I know what a function is called in C++ but I can’t find an equivalent one in the standard library of another language, an LLM will often do a decent first pass of rewriting the C++ function in the other language.

Small minus: The code is overly generic

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Why Video Game AI does not Use Machine Learning

I used to be an AI programmer working on video games, and I’m currently trying to learn machine learning. As part of this I find myself having to repeatedly explain why video games don’t use machine learning. People seem to find it interesting enough because it’s not just the obvious reasons (machine learning is hard and far from solved for game playing) but it’s also about developer control and about making an understandable game for the player. Video game AI is designed to deliver a certain experience, which is more difficult to do with machine learning. So this blog post lists the main reasons why video game AI does not use machine learning.

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Neural Networks Are Impressively Good At Compression

I’m trying to get into neural networks. There have been a couple big breakthroughs in the field in recent years and suddenly my side project of messing around with programming languages seemed short sighted. It almost seems like we’ll have real AI soon and I want to be working on that. While making my first couple steps into the field it’s hard to keep that enthusiasm. A lot of the field is still kinda handwavy where when you want to find out why something is used the way it’s used, the only answer you can get is “because it works like this and it doesn’t work if we change it.”

At least that’s my first impression. Still just dipping my toes in. But there is one thing I am very impressed with: How much data neural networks can express in how few connections.

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