vrighter

it's "my way or the highway" but for gui

i wish the phrase "maybe later" would be forced to be changed to "no". The word no has disappeared!

randomly doesn't mean equiprobable. If you're sampling a probability distribution, it's random. Temperature 0 is never used, otherwise a lot of stuff would consistently hallucinate the exact same thing

they can't if they distribute the mod as a patch, "for educational purposes"

The patch does not contain anything proprietary.

if it's allowed to use its own interactions as data, it will collapse. This has been studied. Stuff just does not work the way you think it does. Try coding one yourself.

The llm does not give you the next token. It gives you a probability distribution of what the next token coould be. Then, after the llm, that probability distribution is randomly sampled.

You could add billions of attention heads, it will still have an element of randomness in the end. Copilot or any other llm (past, present or future) do have this problem too. They all "hallucinate" (have a random element in choosing the next token)

turning jhonny into an llm does not work. because that's not how the kid learns. kids don't learn math by mimicking the answers. They learn math by learning the concept of numbers. What you just thought the llm is simply the answer to 2+2. Also, with llms there is no "next time" it's a completely static model.

yeah. what's your point. I said hallucinations are not a solvable problem with LLMs. You mentioned that alpaca used synthetic data successfully. By their own admissions, all the problems are still there. Some are worse.

from their own site:

Alpaca also exhibits several common deficiencies of language models, including hallucination, toxicity, and stereotypes. Hallucination in particular seems to be a common failure mode for Alpaca, even compared to text-davinci-003.

here's that same conversation with a human:

"why is X?" "because y!" "you're wrong" "then why the hell did you ask me for if you already know the answer?"

What you're describing will train the network to get the wrong answer and then apologize better. It won't train it to get the right answer

Yeah that implies that the other network(s) can tell right from wrong. Which they can't. Because if they did the problem wouldn't need solving.

the problem isn't being pro ai. It's people puling ai supposed ai capabilities out of their asses without having actually looked at a single line of code. This is obvious to anyone who has coded a neural network. Yes even to openai themselves, but if they let you believe that, then the money stops flowing. You simply can't get an 8-ball to give the correct answer consistently. Because it's fundamentally random.