Spoken like someone trying to be pedantic

LLMs are not social, not alive, and can’t act on their own.

“Social meaning” need not be applied to LLMs unless you’re trying to be pedantic.

That’s not even to mention that appearing conscious is as good as being conscious as far as the teams behind these LLMs are concerned.

There’s no practical difference

Yep. Generating and properly preprocessing datasets is always where I feel lost when working on a new project

Yeah, exactly my point about image classification. We’ve had it for a long time already.

Where has chat gpt been rigorously shown to have reasoning ability? I’ve heard that it passed some exams, but that could just be the model regurgitating info in its training data.

Admittedly, I haven’t looked to deeply in the reasoning abilities of LLMs, so any references would be appreciated :)

I think classification tasks (like image or face recognition) is really useful, but is more niche. We had image recognition before, NNs just do it better. They don’t open up new use cases for recognition.

Same for speech to text and text to speech.

Translation is another huge one, that’s true.

I don’t think NN code autocomplete is a “big real life use case” as we have perfectly correct autocomplete as is and for anything beyond simple programs, I have seen any model give good suggestions. Plus not everyone writes code.

Natural language “understanding” is a weird one. I’m not convinced (yet) that we have models that “understand” language, just models that are good at guessing the next word.

ChatGPTs tendency to be flat out wrong or give nonsensical answers to very niche and specific questions suggests that it isn’t doing any kind of critical thinking about a question, it’s just generating statistically probable following tokens. It just generates convincing prose as it was trained to do.

I bet stuff like this is gonna be the biggest real life use case for neural networks.

Faster, more portable physics simulations.

We can get infinite training data using naive physics algorithms, then train a model to optimize that

It is purely statistical, isn’t it?

LLMs are statistical models after all.

Attention is still pretty confusing for me. I find diffusion much more intuitive fwiw.

Not a defense of decentralized finance, but the point of the whole blockchain system is to ensure a group of arbitrary nodes can agree on the state of some data.

You can use blockchain technology without having a coin, token, or any of that nonsense. Just not in the way people have been talking about it.

Though blockchains would probably be too slow for something like this.

You can always build one with lisp /s

It doesn’t work well on mobile. It only uses half the width of the screen