[HN Gopher] 10-202: Introduction to Modern AI (CMU)
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10-202: Introduction to Modern AI (CMU)
Author : vismit2000
Score : 215 points
Date : 2026-03-01 07:35 UTC (15 hours ago)
(HTM) web link (modernaicourse.org)
(TXT) w3m dump (modernaicourse.org)
| emil-lp wrote:
| [flagged]
| axseem wrote:
| It really depends on the target audience, because a lot of
| people have no idea what they are using is called an LLM or
| that there are various types of generative AI.
| gignico wrote:
| I think the problem is the under representation of other
| branches of AI research: knowledge representation, automated
| reasoning, planning, etc.
|
| These are important topics with important industrial
| applications which have the only downsides to not be suitable
| for implementing friendly chatbots and for raising the stocks
| of Silicon Valley companies.
| Kaethar wrote:
| I doubt renowned US universities don't offer courses that
| cover those topics.
|
| As someone who studied in a university system where the
| courses you had to take were mostly set in stone (just
| starting to offer some electives now), I really fancy the
| option of being able to choose what you study as much as
| possible.
|
| The AI course I took was mostly symbolic methods and some
| classic ML at the end. Most students were not interested at
| all and would've probably been more engaged studying ML
| directly. Too bad that wasn't an option.
| small_model wrote:
| Well it's the dominant and most successful implemented AI,
| would a comp sci course teach every failed computer
| architecture or focus on the ones that are in wide use today.
| suddenlybananas wrote:
| I think comp sci courses focuse on fundamentals rather than
| what's popular. Besides, other kinds of AI are not
| "failures", they have plenty of uses.
| gield wrote:
| Your analogy to computer architectures doesn't make sense,
| unless comparing GPT-like LLMs to different LLM architectures
| like Mamba or RWKV. It indeed wouldn't make sense to not
| teach about Mamba or RWKV in an introductory AI or LLM
| course.
|
| AI is much broader than LLMs alone. Computer vision, RL,
| classical ML, recommender systems, speech recognition, ...
| are still part of AI, just not very visible to the average
| consumer.
| utopiah wrote:
| > most successful implemented AI
|
| According to what? Spent money? Number of users? Outcomes and
| if so which ones?
| boredemployee wrote:
| probably according to marketing and not limited to
| hallucination
| smokel wrote:
| Don't trip over words. The course offers quite a range of
| knowledge that is suitable outside LLMs. It's an introduction.
| cubefox wrote:
| This is a perfectly reasonable take. It's quite outrageous that
| this was flagged.
| sim04ful wrote:
| Nothing on symbolic reasoning ?
| cultofmetatron wrote:
| I believe that would be part of whats now "classical ai"
| cubefox wrote:
| It's called GOFAI, or not AI at all. It's basically all
| machine learning nowadays.
| Barbing wrote:
| good old-fashioned artificial intelligence
|
| https://en.wikipedia.org/wiki/GOFAI
| xdavidliu wrote:
| that would be the exact opposite of modern
| chvid wrote:
| No. That will be covered by the Post-modern AI course in the
| fall semester.
| leonvoss wrote:
| That's not AI.
| DonaldFisk wrote:
| Why not? It was called AI at the time.
| aanet wrote:
| > AI Policy for the AI Course
|
| " Students are permitted to use AI assistants for all homework
| and programming assignments (especially as a reference for
| understanding any topics that seem confusing), but we strongly
| encourage you to complete your final submitted version of your
| assignment without AI. You cannot use any such assistants, or any
| external materials, during in-class evaluations (both the
| homework quizzes and the midterms and final).
|
| The rationale behind this policy is a simple one: AI can be
| extremely helpful as a learning tool (and to be clear, as an
| actual implementation tool), but over-reliance on these systems
| can currently be a detriment to learning in many cases. You
| absolutely need to learn how to code and do other tasks using AI
| tools, but turning in AI-generated solutions for the relatively
| short assignments we give you can (at least in our current
| experience) ultimately lead to substantially less understanding
| of the material. The choice is yours on assignments, but we
| believe that you will ultimately perform much better on the in-
| class quizzes and exams if you do work through your final
| submitted homework solutions yourself."
| linhns wrote:
| This is the way it should be. AI to speed up the understanding
| process, and one final evaluation without any help to cement
| the understanding.
| topherhunt wrote:
| I don't think the final evaluation is to "cement the
| understanding" so much as _verify_ that students have taken
| accountability for their own learning process.
| aanet wrote:
| ^ This
|
| This is what a student, who truly wants to learn rather
| than simply complete a course / certification, would do...
| Use AI tools to explain + learn, but not outsource the
| learning process itself to the tools.
| _345 wrote:
| I disagree. I think we should treat AI tools like calculators
| for the exam.
| andsoitis wrote:
| > AI to speed up the understanding process
|
| What's your hypothesis of how AI can accelerate how your
| brain understands something?
| allthetime wrote:
| Quick, easy access to explanations and examples on complex
| topics.
|
| In my case, learning enough trig and linear algebra to be
| useful in game engine programming / rendering has been made
| a lot easier / more efficient.
|
| The same way Google or Wikipedia enables learning.
| wrs wrote:
| I have some success with this method: I try to write an
| explanation of something, then ask the LLM to find problems
| with the explanation. Sometimes its response leads me to
| shore up my understanding. Other times its answer doesn't
| make sense to me and we dig into why. Whether or not the
| LLM is correct, it helps me clarify my own learning. It's
| basically rubber duck debugging for my brain.
| piker wrote:
| My money is on extraordinarily poor final exam results and/or
| cheating.
| khannn wrote:
| In my day professors said that you'd never have an AI in your
| pocket
| piker wrote:
| True. Why even bother with school anyway?
| _joel wrote:
| but can I write 5318008 on my AI?
| eeixlk wrote:
| There are no correct answers, you just have to predict what
| one could be while micro-dosing.
| ashertrockman wrote:
| It feels downstream of CMU's "reasonable person principle".
| They know that people are going to use AI on their homework,
| but they trust that they want to learn and improve their skills
| -- and this is good advice for doing so.
|
| I'm somewhat biased because I was involved in a previous,
| related course. The important takeaways aren't really about
| gritty debugging of (possibly) large homework assignments, but
| the high-level overview you get in the process. AI assistance
| means you could cover more content and build larger, more
| realistic systems.
|
| An issue in the first iteration of Deep Learning Systems was
| that every homework built on the previous one, and errors could
| accumulate in subtle ways that we didn't anticipate. I spent a
| lot of time bisecting code to find these errors in office
| hours. It would have been just as educational to diagnose those
| errors with an LLM. Then students could spend more time
| implementing cool stuff in CUDA instead of hunting down a
| subtle bug in their 2d conv backwards pass under time
| pressure... But I think the breadth and depth of the course was
| phenomenal, and if courses can go further with AI assistance
| then it's great.
|
| This new class looks really cool, and Zico is a great teacher.
| gabrieledarrigo wrote:
| Do you think this is a good course? Or, what do you suggest as a
| structured course to learn how LLMs work?
| aboardRat4 wrote:
| Nice to finally see the revival of Lisp and Prolog.
| signa11 wrote:
| prolog in another skin is called erlang you know.
| hearsathought wrote:
| Lisp and Prolog never really "vived" nor were they ever really
| gone/dead. So they can't be revived. They've always been there,
| in the background, in their niche. As they always will.
| DonaldFisk wrote:
| Sadly, not part of this course, though Lisp and Prolog are very
| useful for other things. C's fine for building neural networks
| from scratch, and you can glue different subsystems together to
| make anything more complex than that using Python.
| mold_aid wrote:
| Can't wait for postmodern AI.
| blackoil wrote:
| How to flip burgers better than an AI robot!
| aanet wrote:
| :) Too true
|
| But tbh, it'll more likely be repairing those burger flippin'
| robots
| frankdenbow wrote:
| thanks for sharing, these look great.
| teleforce wrote:
| I hope the instructor will publish a textbook to support and
| accompany the course, will buy in a heartbeat.
| apavlo wrote:
| For those that are unaware, the instructor of this is on the
| board of OpenAI:
|
| https://openai.com/index/zico-kolter-joins-openais-board-of-...
| somethingsome wrote:
| I'm a little annoyed that 'modern AI' refers here only on LLMs,
| modern AI is way bigger than that.
|
| Having said that, it's probably a good course, CMU courses are
| often great.
|
| I was just expecting way more sota models in many fields due to
| the title.
|
| If someone has this kind of ressource I would be extremely
| interested!
| neriymus wrote:
| I started doing the free version of the course a few days ago -
| the lessons are excellent but what is even better are the
| homework tasks which allows me to run my tests locally!
|
| It's sometimes easy to just listen and understand, but be unable
| to write the code myself - having this coding homework task has
| really helped me solidify this new knowledge.
|
| 10/10 would recommend
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