Comment by crazygringo

1 day ago

> There's just no way in hell ChatGPT at its current level is going to guide you flawlessly through all of that if you start with a simple "I want to build a raytracer" prompt!

I mean, maybe not "flawlessly", and not in a single prompt, but it absolutely can.

I've gone deep in several areas, essentially consuming around a book's worth of content from ChatGPT over the course of several days, each day consisting of about 20 prompts and replies. It's an astonishingly effective way to learn, because you get to ask it to go simpler when you're confused and explain more, in whatever mode you want (i.e. focus on the math, focus on the geometry, focus on the code, focus on the intuition). And then whenever you feel like you've "got" the current stage, ask it what to move onto next, and if there are choices.

This isn't going to work for cutting-edge stuff that you need a PhD advisor to guide you through. But for most stuff up to about a master's-degree level where there's a pretty "established" progression of things and enough examples in its training data (which ray-tracing will have plenty of), it's phenomenal.

If you haven't tried it, you may be very surprised. Does it make mistakes? Yes, occasionally. Do human-authored books also make mistakes? Yes, and often probably at about the same rate. But you're stuck adapting yourself to their organization and style and content, whereas with ChatGPT it adapts its teaching and explanations and content to you and your needs.

How did you verify that it wasn't bogus? Like, when it says "most of the time", or "commonly", or "always", how do you know that's accurate? How do those terms shape your thinking?

  • > when it says "most of the time", or "commonly", or "always", how do you know that's accurate?

    Do you get those words a lot? If you're learning ray-tracing, it's math and code that either works or doesn't. There isn't a lot of "most of the time"?

    Same with learning history. Events happened or they didn't. Economies grew at certain rates. Something that is factually "most of the time" is generally expressed as a frequency based on data.

    • > Something that is factually "most of the time" is generally expressed as a frequency based on data.

      that is exactly my point. This is purely anecdotal, but LLMs keep pretenting there is data like that, so they use those words

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