ChatGPT with Rob Miles - Computerphile

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Recommends mikewarot · 2023-02 · on “Ask HN: Are ChatGPT answers getting worse for anyone else?”

This video[1] cleared up a lot of questions for me as to the issues I've seen with ChatGPT. My current operating theory goes thusly: Think back to "This Person does not Exist" [2], a site which generates a simulated human face. This works by randomly picking a vector into the latent space of human faces from a trained model, and showing it to the user. When you're using ChatGPT, you're getting a simulated assistant, at random. The quality of the answer is highly dependent on how that portion of the latent space (and thus that particular simulated assistant) was trained. Thus, as you get a wide variety of faces from this-person-does-not-exist, you'll get a wide variety of simulated assistants

Recommends mikewarot · 2023-02 · on “Princeton CS Prof: ChatGPT Is a Bullshit Generator (2022)”

It might help quite a bit to watch this overview of how ChatGPT works, and especially how it was trained .[1] Human attention was too expensive for the training, so they made another AI to simulate the trainers. Unfortunately, the trainer simulator training didn't have an expressive enough set of options for the actual humans, which kept a lot of quite valuable feedback out of the whole system by reducing things to single ranking. If the person didn't know the correct answer, they'd likely just go based on gut. This in turn lead the training simulator to do the same. This lead ChatGPT to just try to bullshit an answer rather than stating it didn't know, and getting downvoted. [1] [this video]

Recommends f_devd · 2023-02 · on “Open Assistant: Conversational AI for Everyone”

It depends on your definition of cheating, but this is definitely not "using humans to answer all questions one could ask". Rather it's a way to tune language models to be more like assistants rather than "most likely continuation machines". For context I recommend watching the discussion on what chatgpt is/does[0], and what the open assistant project's aim is[1]. [0]: [this video] [1]: [LINK]

Recommends simonh · 2023-02 · on “The new Bing will happily give you citations for a pile of nonsense”

I’ve read that before, it is fascinating. GPT3 was just trained on source text, but ChatGPT has undergone an an additional very rigorous programme of intensive training bootstrapped by human feedback. This has evolved it in order to improve its performance as an information assistant, especially on specific tasks that have proved problematic in the past. This video explains the approach and some of its limitations. [this video]

Recommends fxj · 2023-04 · on “What GPT-4 Does Is Less Like “Figuring Out” and More Like “Already Knowing””

I think it is still a problem that many people do not know how GPT really works. There is no part in GPT that can figure out something. So no intelligence and no learning of things. A good example is when you look at GPT writing poems. All poems that it writes are of the same structure and they are not very good. So it seems it does not know the difference between a sonnet and a limmerick. But what happens is, that there is a miss-alignment between writing a poem and making the user happy. GPT is trained that its highest goal is to make the user happy. GPT believes that users dont know what sonnets are anyway so i can get away with a rhyme that is not a sonnet. Here is a good video about tha

Cites pixl97 · 2023-02 · on “Open Assistant – project meant to give everyone access to a great chat based LLM”

[this video] Computerphile did an interview with Rob Miles a few days ago talking about model training, model size, and bulllshittery which he sums up in the last few moments of the video. Numerous problems exist in training that enhance bad behaviors. For example it appears that the people giving input on the responses may have a (Yes|No) voting system, but not a (Yes | No | I actually have no idea on this question) which appears it can create some interesting alignment issues.

Cites pixl97 · 2023-02 · on “Open Assistant – project meant to give everyone access to a great chat based LLM”

>We need someone with a warehouse of GPUs to train a model with the parameter count of GPT3 So I'm assuming that you don't follow Rob Miles. If you do this alone you're either going to create a psychopath or something completely useless. The GPT models have no means in themselves of understanding correctness or right/wrong answers. All of these models require training and alignment functions that are typically provided by human input judging the output of the model. And we still see where this goes wrong in ChatGPT where the bot turns into a 'Yes Man' because it's aligned with giving an answer rather than saying I don't know even when it's confidence in the answer is low. Computerphile did a

Cites spuz · 2023-03 · on “GPT-4”

> In order to resolve this, ChatGPT's training corpus needs to contain a "correct answer" next to every unique permutation of every question. This is not quite the right understanding of how ChatGPT works. It's not necessary to show ChatGPT an example of every possible permutation of an animal crossing puzzle in order for it to solve one it has never seen before. That's because the neural network is not a database of recorded word probabilities. It can instead represent the underlying logic of the puzzle, the relationships between different animals and using this abstract, pared down information, extrapolate the correct answer to the puzzle. I see the failure in the example with the goat the