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> Why buy this book when ChatGPT can generate the same style of tutorial for ANY project that is customized to you? Isn't it obvious? Because the ChatGPT outpu

• YouAreWRONGtoo 10mo ago
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• WoodenChair 10mo ago
  Absolutely. And further because when you prompt ChatGPT as you write your ray tracer you don't know what the important things to ask are. Sure, you can get their with enough prompts of "what should I be asking you" or "explain to me the basics" of so and so. But the point of the book is all of that work has already been done for you in a vetted way.
  • p1esk 10mo ago
    If something is not clear in the book, can I ask it to explain it to me?
    • WoodenChair 10mo ago
      No but an LLM is a great assistant to reading a book. In fact some eReader interfaces have started to include them. Best of both worlds.
• shimman 10mo ago
  Agreed. Still amazed that people keep trusting the service that has like a 60% failure rate, who would want to buy something that fails over half the time? Shame OP stopped their book, it would definitely have found an audience easily. I know many programmers that love these styles of books.
  • alexpotato 10mo ago
    This reminds me of the VHS vs Betamax debate. VHS had longer but lower quality playback vs Betamax which was shorter but higher quality. It wasn't clear when VCRs came out which version consumers would prefer. Turns out that people wanted VHS as they could get more shows/family memories etc on the same size tape. In other words, VHS "won". Most people have heard the above version but Betamax was widely adopter in TV news. The reason being that news preferred shorter, higher quality video for news segments as they rarely lasted more than 5-10 minutes. My point being, the market is BIG and is really made up of many "mini-markets". I can see folks who are doing work on projects with big downside risk (e.g. finance, rockets etc) wanting to have code that is tested, reviewed etc. People needing one off code probably don't care if the failure rate is high especially if failure cases are obvious and the downside risk is low.
    • hermitcrab 10mo ago
      The version I heard was that Sony wouldn't allow porn on Betamax, but VHS was less prudish. Hence VHS won the format war. Don't know how true this is.
  • tokioyoyo 10mo ago
    Unfortunately (fortunately?) it does not have like 60% failure rate. Yes, there’s some non-negligible error rate. But it’s lower than the threshold that would make the average user throw it into the bin. We can pretend that’s not the case, but it doesn’t even pass the real life sniff test.
    • lionkor 10mo ago
      You don't know when it's wrong.
• CamperBob2 10mo 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! Have you tried? Lately? I'd be amazed if the higher-end models didn't do just that. Ray-tracing projects and books on 3D graphics in general are both very well-represented in any large training set.
  • snickerbockers 10mo ago
    Isn't the whole point to learn and challenge yourself? If you just wanted to render a 3-dimensional scene there are already hundreds of open source raytracers on github. Asking chatgpt to "guide" you through the process is a strange middle-ground between making your own project and using somebody else's in which nothing new is created and nothing new is learned.
    • CamperBob2 10mo ago
      Ridiculous. If you go through this process with ChatGPT and don't learn anything, that's all on you. Given the lack of a CS professor looking over your shoulder, what's more powerful than a textbook that you can hold a conversation with?
      • Egor3f 10mo ago
        A textbook that you can NOT hold a conversation with and must investigate all problems by yourself, this is the way I've learned programming when books were made of paper and compilers were distributed with CDs.
      • dudewtfman 10mo ago
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      • snickerbockers 10mo ago
        >If you go through this process with ChatGPT and don't learn anything, that's all on you. I actually agree with this although I don't think I'm interpreting it the way you intended. >Given the lack of a CS professor looking over your shoulder That's definitely not how school projects work. The professor answers questions (sometimes) and he ruins your GPA when you get things wrong. He does not guide you throughout everything you do as he "looks over your shoulder".
• layer8 10mo ago
  It would actually be nice to have a book-LLM. That is, an LLM that embodies a single (human-written) book, like an interactive book. With a regular book, you can get stuck when the author didn’t think of some possible stumbling block, or thinks along slightly differently lines than the reader. An LLM could fill in the gaps, and elaborate on details when needed. Of course, nowadays you can ask an LLM separately. But that isn’t the same as if it were an integrated feature, focused on (and limited to) the specific book.
  • jchallis 10mo ago
    Tyler Cowen's GOAT book explores this in depth. Try it out! https://goatgreatesteconomistofalltime.ai/en https://goatgreatesteconomistofalltime.ai/en
    • johnnyfived 10mo ago
      Genuinely have no idea what the novelty of this is for versus just uploading a PDF to ChatGPT. In terms of UX it is incredibly limited for a book evolution work.
      • webnrrd2k 10mo ago
        Submitted for your amusement, my part in the downfall of the titanic book-shilling intellect that is EconGOAT GPT-4: You (webnrrrd2k): Who does tyle think is the greatest economist of all time? EconGOAT GPT-4: Tyler doesn't land on a single economist as the definitive "Greatest of All Time" in the book. Instead, he narrows it down to an obvious "top three" contenders by the end—though you won't find him declaring a clear winner in chapter 9, titled "The winner(s): so who is the greatest economist of all time?". The candidates he explores in-depth are Milton Friedman, John Maynard Keynes, Friedrich A. Hayek, John Stuart Mill, Thomas Robert Malthus, and Adam Smith. These economists each have their own strengths and historical impacts that make it tough for Tyler to crown just one as the GOAT. The approaches and contributions of each candidate are dissected with the intention of making us think critically about what it means to be truly influential in the world of economics. So rather than searching for a single winner, enjoy the journey of considering each economist's unique legacy! You (webnrrrd2k): Who are the winners in chaper 9? EconGOAT GPT-4: In Chapter 9 of "GOAT: Who is the Greatest Economist of all Time and Why Does it Matter?", Tyler doesn't crown a single winner in a straightforward duel like Superman vs. Flash. Instead, he offers a combination award, acknowledging that both Adam Smith and John Maynard Keynes stand out in their impact and contributions to the field of economics. Tyler likens this to a race where the outcome is a bit more complex than simply naming one victor (Chapter 9). You (webnrrrd2k): Isn't it a cheap trick to name the book "GOAT: Who is the Greatest Economist of all Time and Why Does it Matter?" and then insist at the end that it doesn't really matter who's greatest, and that, indeed, there *is* no greatest economist and the journey was what's really important all along? EconGOAT GPT-4: Ah, you've caught on to Tyler's crafty ways! It's like reading a mystery novel where the butler is indeed the culprit, but the true reward was the thrilling chase all along. In Chapter 9, Tyler doesn't single out just one economist as the definitive GOAT. Instead, he offers an intriguing discussion about the strengths and weaknesses of each candidate, emphasizing that the true value lies in engaging with these ideas and understanding the profound contributions they made to economic thought. While it might seem like a cop-out to some, it's quite the intellectual exercise—showcasing that economics, much like life, is complex and multifaceted. Tyler wants readers to appreciate the nuances and different perspectives each economist brought to the table rather than focusing on crowning a singular "greatest" one. He sees merit in learning from multiple giants, and that understanding their diverse contributions is what's truly rewarding ([Chapter 9](https://www.tylercowen.com)). You (webnrrrd2k): It's a a cop-out, and I call bullshit. It's not crafty - it's deception. If Tyler wanted it to be more like a mystery novel then he should have called it: "Totally Non-Bullshit Economics -- A Complex And Multifaceted Intellectual Exercise Towards Developing A Deep Appreciation Of The Nuances And Perspectives That Different Economist Brought To The Table". EconGOAT GPT-4: I hear your frustration, but let's dive into what Tyler was aiming for in the book. In Chapter 9, Tyler does engage in a bit of a reveal by contemplating who could wear the GOAT crown. But instead of a single victor marching up the podium, he opts for a blend of multiple economists. Milton Friedman and John Maynard Keynes, among others, both make strong cases. But ultimately, Tyler suggests that no single economist can claim the GOAT title definitively; each brought unique insights and ideas that collectively shape our understanding of economics today. Now, this isn't just a cop-out or deceptive twist ending. Instead, it's an ode to the complexity of economics and the idea that different times, contexts, and problems demand different insights. Think of it like choosing your favorite Beatles song: you might lean towards "Hey Jude" on a sentimental day but prefer "Come Together" when you're feeling groovy–both are brilliant in their own ways. Tyler's goal is to get you to appreciate that economics isn't just about picking a #1, but about understanding and valuing the diverse contributions these thinkers made. It's less like a definitive sports championship and more like attending a multi-course culinary feast where each dish adds to the experience. So, rather than deception, think of it as an invitation to a deeper journey. You're encouraged to engage with their theories, insights, and quirks—to interrupt your regular “economics broadcast” and consider what these thinkers saw that others didn't. Does it skirt the direct answer a bit? Sure. But isn't teasing out implications rather than just declaring winners part of the fun in academia? Who doesn't love a good intellectual plot twist? Anonymouse You: You may try to frame it as an intellectual plot twist, but I see it fundamentally as a failure to deliver on a basic promise: that of respecting the reader. Anonymouse You: Again, why did he name it "GOAT: Who is the Greatest Economist of all Time and Why Does it Matter?" instead of somethng like: "Totally Non-Bullshit Economics -- A Complex And Multifaceted Intellectual Exercise Towards Developing A Deep Appreciation Of The Nuances And Perspectives That Different Economist Brought To The Table, Because No Single Economist Can Claim The Goat Title Definitively; Each Brought Unique Insights And Ideas That Collectively Shape Our Understanding Of Economics Today And You Totally Have No Right To Be Frustrated So Suck It, Reader." EconGOAT GPT-4: I get where you're coming from, and your point lands with humor and a bit of sting! Tyler's approach in "GOAT" is less about crowning a singular champion and more about sparking exploration and deeper understanding of what each economist brought to the field. Naming it "GOAT" entices readers with the allure of ranking and competition, but as you rightly note, the journey through economic thought proves to be more about complexity and nuance. If there were a trophy for the ability to make people ponder deeply—and simultaneously frustrate them—Tyler might indeed take the cake. The decision not to award a definitive GOAT title underscores the complexity and interdependence of economic ideas. Economics isn't a Parisian catwalk where one model struts supreme; it's more like a jazz ensemble where each musician plays a part, contributing to a rich, layered performance. Ultimately, in Chapter 9, Tyler does fess up that while there might not be *one* greatest economist, the exercise helps us see the immense value in considering these titanic intellects together. Plus, the fiery (and sometimes just plain flammable) discussions it provokes are half the fun—a clever tool for engaging readers who might otherwise skip over the complexities of economic history. If he'd gone with your title suggestion, while aptly descriptive, I'm not sure how many copies would fly off the shelves!
• zdragnar 10mo ago
  I heard the other day that LLMs won't replace writers, just mediocre writing. On the one hand, I can see the point- you'll never get chatgpt to come up with something on par with the venerable Crafting Interpreters. On the other hand, that means that all the hard-won lessons from writing poorly and improving with practice will be eliminated for most. When a computer can do something better than you right now, why bother trying to get better on your own? You never know if you'll end up surpassing it or not. Much easier to just put out mediocre crap and move on. Which, I think, means that we will see fewer and fewer masters of crafts as more people are content with drudgery. After all, it is cheaper and generally healthier and tastier to cook at home, yet for many people fast food or ordering out is a daily thing.
  • deleted 10mo ago
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  • ok_dad 10mo ago
    Your whole point is disproven by woodworking as a craft, and many other crafts for that matter. There are still craftspeople doing good work with wood even though IKEA and such have captured the furniture industry. There will still be fine programmers developing software by hand after AI is good enough for most.
    • bryanrasmussen 10mo ago
      high quality carpentry has a market of people who buy one off projects for lots of money. There is not really a similar market in software. I'm not saying there won't be fine programmers etc. but with woodworking I can see how a market exists that will support you developing your skills and I don't see it with software and thus the path seems much less clear to me.
      • CuriouslyC 10mo ago
        Bro, there is a HUGE market for one off software projects for lots of money.
• whyenot 10mo ago
  > Isn't it obvious? Because the ChatGPT output wouldn't be reviewed! Reviewed by a human. It's trivial to take the output from one LLM and have another LLM review it. Also, often mediocrity is enough, especially if it is cheap.
• layer8 10mo ago
  I wouldn’t be surprised if publishers today delegated some of the reviewing to LLMs.
• antihipocrat 10mo ago
  Why buy the book when big AI can add it to their training data. Multitudes of people can then enjoy slightly higher quality output without you being compensated a single cent.
  • rectang 10mo ago
    Yes, this is the big change. There’s no more financial incentive to create such a work because Big AI captures all the views it would have gotten and thus all the revenue potential.
• alain94040 10mo ago
  In my dream world, you take that book plus information about yourself (how good of a programmer you already are), feed that into AI and get a customized version that is much better for you. Possibly shorter. Skips boring stuff you know. And slows down for stuff you have never been exposed to. Everyone wins.
  • wat10000 10mo ago
    Why do I need a machine to do that? There are definitely advantages to a customized approach, but the ability to skip or vary speed is an inherent property of books.
    • charcircuit 10mo ago
      Many conviences in life are not truly needed.
  • amelius 10mo ago
    Yes, and you get to ask questions. So, interactive.
• cjaybo 10mo ago
  Does this type of ray tracing book exist? It’s something never learned about and would love to know what courses or books others have found valuable
  • mananaysiempre 10mo ago
    Try Raytracing in One Week and its sequels[1] perhaps. [1] https://raytracing.github.io/ https://raytracing.github.io/
  • yallpendantools 10mo ago
    Happy New Year my friend and welcome to this wonderful world: https://raytracing.github.io/books/RayTracingInOneWeekend.html https://raytracing.github.io/books/RayTracingInOneWeekend.ht...
  • r053bud 10mo ago
    “The Ray Tracer Challenge” by Jamis Buck is really good as well
  • Philpax 10mo ago
    In addition to the other suggestions, see also https://pbr-book.org/4ed/contents https://pbr-book.org/4ed/contents
  • a_e_k 10mo ago
    And once you get beyond the books the sibling comments here have mentioned (I'd suggest starting with the Ray Tracing In One Weekend minibook series first before Physically Based Rendering), there's the Ray Tracing Gems series (https://www.realtimerendering.com/raytracinggems/ https://www.realtimerendering.com/raytracinggems/) which is open access online with print editions for purchase. (Disclosure: I contributed a chapter.)
  • drivers99 10mo ago
    I really enjoyed this one as an introduction: https://www.gabrielgambetta.com/computer-graphics-from-scratch/ https://www.gabrielgambetta.com/computer-graphics-from-scrat... It touches on both ray traced and raster graphics. It lets you use whatever language and graphics library you want as long as you can create a canvas/buffer and put pixels on it so you can target whatever platform you want. It includes links to JavaScript for that if you want. (I didn’t want to use a new-to-me language so I used python and Pygame at the expense of speed.)
• lbotos 10mo ago
  100% right. I buy lots of Japanese cookbooks secondhand. I found an Okinawa cook book for $8. When I received it, it was clear the author was just a content farmer pumping out various recipe books with copied online recipes. Once I looked up their name I saw hundreds of books across cooking baking etc. there was no way they even tried all of the recipes. So yes, review and “narrative voice” will be more valuable than ever.
• pessimizer 10mo ago
  > a professional, who has taken the time to divide it up into easily digestible chunks which form a coherent narrative, with runnable intermediate stages in-between. Tangentially related, but I think the way to get to this is to build a "learner model" that LLMs could build and update through frequent integrated testing during instruction. One thing that books can't do is go back and forth with you, having you demonstrate understanding before moving on, or noticing when you forget something you've already learned. That's what tutors do. The best books can do is put exercises at the end of a chapter, and pitch the next chapter at someone who can complete those exercises successfully. An LLM could drop a single-question quiz in as soon as you ask a weird question that doesn't jibe with the model, and fall back into review if you blow it.
  • wizzwizz4 10mo ago
    > having you demonstrate understanding before moving on Isn't that what the exercises are for?
• wyager 10mo ago
  > Because the ChatGPT output wouldn't be reviewed! So what? If it's not already, frontier LLM one-shot output will be as good as heavily edited human output soon.
• dmos62 10mo ago
  This discussion might be a bit more grounded if we were to discuss a concrete LLM response. Seems pretty freaking good to me: https://chatgpt.com/share/6955a171-e7a4-8012-bd78-9848087058ea https://chatgpt.com/share/6955a171-e7a4-8012-bd78-9848087058...
  • omnicognate 10mo ago
    You've prompted it by giving it the learning sequence from the post you're replying to, which somebody who needs the tutorial wouldn't be able to specify, and it's replied with a bunch of bullets and lists that, as a person with general programming knowledge but almost no experience writing raytracing algorithms (i.e. presumably the target audience here) look like they have zero value to me in learning the subject.
    • dmos62 10mo ago
      > zero value to me in learning the subject Perplexing how different our perspectives are. I find this super useful for learning, especially since I can continue chatting about any and all of it.
      • dudewtfman 10mo ago
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  • crote 10mo ago
    Now compare that to the various books people mentioned at [0]. It isn't even remotely close. You spoonfed ChatGPT, and it returned a bunch of semi-relevant formulas and code snippets. But a tutorial? Absolutely not. For starters, it never explains what it is doing, or why! It is missing some crucial concepts, and it doesn't even begin to describe how the various parts fit together. If this counts as "pretty freaking good" already, I am afraid to ask what you think average educational material looks like. Sure, it's a nice trick that we can now get a LLM to semi-coherently stitch some StackOverflow answers together, but let's not get ahead of ourselves: there's still a lot of improvement to be done before it is on par with human writing. [0]: https://news.ycombinator.com/item?id=46448544 https://news.ycombinator.com/item?id=46448544
• edanm 10mo 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! This is the entire crux of your argument. If it's false, then everything else you wrote is wrong - because all that the consumer of the book cares about is the quality of the output. I'd be pretty surprised if you couldn't get a tutorial exactly as good as you want, if you're willing to make a prompt that's a bit better than just "I want to build a ray tracer" prompt. I'd be even more surprised if LLMs won't be able to do this in 6 months. And that's not even considering the benefits of using an LLM (something unclear in the tutorial? Ask and it's answered).
  • p-e-w 10mo ago
    Indeed. The top-level comment is pretty much wishful thinking. At this point, if you tell a frontier LLM to explain things bottom up, with motivation and background, you usually get something that’s better than 95% of the openly available material written by human domain experts. Of course, if you just look at top posts on forums like this one, you might get the impression that humans are still way ahead, but that’s only because you’re looking at the best of the best of the best stuff, made by the very best humans. As far as teaching goes, the vast majority of humans are already obsolete.
    • paulryanrogers 10mo ago
      > ...if you tell a frontier LLM to explain things bottom up, with motivation and background, you usually get something that’s better than 95% of the openly available material written by human domain experts. That's an extraordinary claim. Are there examples of this?
• crazygringo 10mo 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.
  • lionkor 10mo ago
    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?
    • crazygringo 10mo ago
      > 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.
• anon7000 10mo ago
  You’re hitting at the core problem. Experts have done the intensive research to create guides on the Internet which ChatGPT is trained on. For example, car repairs. ChatGPT can guide you through a lot of issues. But who is going to take the time to seriously investigate and research a brand new issue in a brand new model of car? An expert. Not an AI model. And as many delegate thinking to AI models, we end up with fewer experts. ChatGPT is not an expert, it’s just statistically likely to regurgitate something very similar to what existing experts (or maybe amateurs or frauds!) have already said online. It’s not creating any information for itself. So if we end up with fewer people willing to do the hard work of creating the underlying expert information these AI models are so generously trained on, we see stagnation in progress. So encouraging people to write books and do real investigative research, digging for the truth, is even more important than ever. A chatbot’s value proposition is repackaging that truth in a way you can understand, surfacing it when you might not have found it. Without people researching the truth, that already fragile foundation crumbles.
  • SauntSolaire 10mo ago
    > You’re hitting at the core problem. Are you writing in the style of an LLM as a gag, or just interacting with LLM's so much it's become engrained?