441–450 of 527 posts
Tao mentions grad students; I wonder how they feel reading this? As LLMs continue to improve I feel like anyone making a living doing the "99% perspiration" part of intellectual labor is about to enter a world of hurt.
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> Much Much more productive world by just knuckling down and learning how to do the work. The fact everyone that say they've become more productive with LLMs won't say how exactly. I can talk about how VIM have make it more enjoyable to edit code (keybinding and motions), how Emacs is a good environment around text tooling (lisp machine), how I use technical books to further my learning (so many great books out here)…
Or people say "I've been pumping out thousands of lines of perfectly good code by writing paragraphs and paragraphs of text explaining what I want!" its like what are you programming dog? and they will never tell you, and then you look at their github and its like a dead simple starter project. I recently built a Brainfuck compiler and TUI debugger and I tested out a few LLM's just to see if I could get some useful o…
Reading anything Terrence Tao writes is thought provoking and I doubt I’m seeing anything others haven’t. There’s at least a “complexity” if not a “problem” in terms of judging models that to a first approximation have been trained on “everything”. Have people tried putting these things up against serious mathematical problems that are well studied? With or with Lean hinting has anyone gotten like, the Shimura-Taniya…
I believe this is the farthest anyone has gotten: https://deepmind.google/discover/blog/ai-solves-imo-problems... No FLT yet, but as someone who was initially quite skeptical, I’m starting to be convinced!
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The first profession AI seems on track to decimate is programming. In particular, the brilliant but remote and individual contributor. There is an obvious conflict of interest in this forum.
The programmers who will find LLMs most useful are going to be those who prior to LLMs were copying and pasting from Stack Overflow, and asking questions online about everything they were doing - tasks that LLMs have precisely replaced (it has now memorized all that boilerplate code, consensus answers, and API usage examples). The developers who will find LLMs the least useful are the "brilliant" ones who never found…
LLMs free me from the nuts and bolts of the "how", for example I don't have to manually type out a loop. I just write a comment and the loop magically appears. Sometimes I don't have to prompt it at all.
With my brain freed from the drudgery of everyday programming, I have more mental cycles to dedicate to higher concerns such as overall architecture, and I'm just way more productive.
For experienced programmers this is a godsend.
Less experienced developers lack the ability to mentally "see" how software should be architected in a way that balances the concerns, so writing a loop a bit faster it's not as much of an advantage. Also, they lack the reflexes to instantly decide if generated code is correct or incorrect.
LLMs are limited by the user's decision speed, the LLM generates code for you but you have to decide whether to accept or reject. If it takes me 1 second to decide to accept code that would have taken me 10 seconds to physically type, then I'm saving 9 seconds, which really adds up. For a junior developer, LLMs may give negative productivity if it takes them longer to decide if the LLM's version is correct than it would have taken them to type whatever they were going to write in the first place.
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I abandoned 3D art after witnessing DALL-E 2's capabilities, and I've observed the ripple effects across creative fields. Initially, photographers and fellow artists dismissed AI as a non-threat. That turned out to be misguided optimism. Now, with Midjourney producing such impressive work, the majority of us have become largely obsolete. These days, I'm noticing developers exhibiting the same denial. From my perspect…
Sure, Midjourney's work looks visually impressive, but have you seen evidence that it really is displacing professional 3D artists? Are legitimate companies genuinely switching to Midjourney over hiring artists now, or is Midjourney usage still mostly happening in places that previously wouldn't have commissioned custom illustrations at all (instead using things like stock photography)?
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Sure, Midjourney's work looks visually impressive, but have you seen evidence that it really is displacing professional 3D artists? Are legitimate companies genuinely switching to Midjourney over hiring artists now, or is Midjourney usage still mostly happening in places that previously wouldn't have commissioned custom illustrations at all (instead using things like stock photography)?
It raises the bar of 'professional 3D artist'. There're hundreds of thousands of '3D worker' working behind the scene to create the 3D models for makeshift ads, and as far as I know many of them (including my high school mate) already got displaced by Midjourney and lost their job. This used to be a big industry but now almost entirely wiped out by AI.
To my knowledge, 3D artists weren't that huge of an industry to begin with. One of my friends went to college researching 3D physics models, and never landed a job in the field long before the AI wave hit. Unless you're a freelancer or salaried Pixar employee, being a 3D artist is extremely difficult with extraordinarily low job security, AI or no AI.
I think "almost entirely wiped out by AI" is hyperbole, because the primary employer of these artists will still be hiring and products like Sora are a good decade away from being Toy Story quality. AI will be a substitute product for people that didn't even want 3D art in the first place.
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That's not true at all. You can literally learn how to write proofs using Lean: https://djvelleman.github.io/HTPIwL/
The examples in this book are extraordinarily simple, and covers material that many proof assistants were designed to be extremely good at expressing. I wouldn't be surprised if a LLM could automate the exercises in this book completely. Writing nontrivial proofs in a theorem prover is a different beast. In my experience (as someone who writes mechanized mathematical proofs for a living) you need to not only know the…
What do you mean by that? I don't know much about theorem provers, but my POV would be that a proof is used to verify a statement. What other uses are there one should consider?
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Or people say "I've been pumping out thousands of lines of perfectly good code by writing paragraphs and paragraphs of text explaining what I want!" its like what are you programming dog? and they will never tell you, and then you look at their github and its like a dead simple starter project. I recently built a Brainfuck compiler and TUI debugger and I tested out a few LLM's just to see if I could get some useful o…
Here's the thing. 99% of people aren't writing compilers or debuggers, they're writing glorified CRUDs. LLM can save a lot of time for these people, just like 99% of people only use basic arithmetic operations, and MS Excel saves a lot of time for these people. It's not about solving new problems, it's about solving old and known problems very fast.
Look, I get the hype - but I think you need to step outside a bit before saying that 99% of the software out there is glorified CRUDs...
Think about the aerospace/defense industries, autonomous vehicles, cloud computing, robotics, sophisticated mobile applications, productivity suites, UX, gaming and entertainment, banking and payment solutions, etc. Those are not small industries - and the software being built there is often highly domain-specific, has various scaling challenges, and takes years to build and qualify for "production".
Even a simple "glorified CRUD", at a certain point, will require optimizations, monitoring, logging, debugging, refactoring, security upgrades, maintenance, etc...
There's much more to tech than your weekend project "Facebook but for dogs" success story, which you built with ChatGPT in 5 minutes...
This is like when you’re being interviewed for a programming job and the interviewer explains some problem to you that it took their team months to figure out, and then they’re disappointed you can’t whiteboard out the solution they came up with in 40 minutes without access to google.
‘Able to make the same creative mathematical leaps as Terence Tao’ seems like a pretty high bar to be setting for AI. This is like when you’re being interviewed for a programming job and the interviewer explains some problem to you that it took their team months to figure out, and then they’re disappointed you can’t whiteboard out the solution they came up with in 40 minutes without access to google.
Having read what he's saying there, and with my experience, I think your characterisation is inaccurate.
And having been at the talk he gave for the IMO earlier this year he is impressed with some of the interactions, it's just that he feels that any kind of "creative spark" is still missing.