Linux server admin, MySQL/TSQL database admin, Python programmer, Linux gaming enthusiast and a forever GM.
LLMs don’t “create”. Under the hood, they’re tokenizing the queries, looking for “clouds” of tokens that are similar to the query, then returning a sequence of tokens (with some random noise thrown in) that match what their training data says the answer should be.
In short: all LLM code is an amalgamation of their training data by definition. If there’s nothing similar in there, it’s literally not possible for it to be part of any response.
The problem is you don’t decide when your camera is running, Meta does. Even if you’re not doing the creepy shit that other people are doing, it’s still somewhat invasive to everyone you look at.
Not if you have pets. You’ll need a screen to stop hair getting into the case if you have cats/dogs.
By death toll, number one was the Qing dynasty, very much not communist. Number 2 was communist China. You have to go all the way to number 11 before you hit the USSR.
I don’t know. I’m not a lawyer, and copyright for code was a hot mess even before LLMs got involved. With how many opportunistic copyright/patent trolls there are and how easily convinced judges have been in the past, it could go either way.
The good programmers normally code by breaking down the problem into constituent parts and logically working through the problem, step by step. What differentiates this from tokenization is that instead of just looking for code that is similar for a similar problem, programmers can usually understand the effects of each line of code, visualize what the state of each variable will be in that step (or dump out the variables to look directly if unsure), and then move on to the next step. This logical problem-solving approach is fundamentally different from a tokenization+noise looking for a similar-looking problem approach. For one thing, you can solve problems that haven’t been solved before.