• 2 Posts
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Joined 1 year ago
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Cake day: January 16th, 2024

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  • but i still think that it’s a little suspect on the grounds that we have no idea how many times they had to restart training due to the model borking, other experiments and hidden cost

    Oh ye, I totally agree on this one. This entire genAI enterprise insults me on a fundamental level as a CS researcher, there’s zero transparency or reproducibility, no one reviews these claims, it’s a complete shitshow from terrible, terrible benchmarks, through shoddy methodology, up to untestable and bonkers claims.

    I have zero good faith for the press, though, they’re experts in painting any and all tech claims in the best light possible like their lives fucking depend on it. We wouldn’t be where we are right now if anyone at any “reputable” newspaper like WSJ asked one (1) question to Sam Altman like 3 years ago.


  • Okay I mean, I hate to somehow come to the defense of a slop company? But WSJ saying nonsense is really not their fault, like even that particular quote clearly says “DeepSeek said training one” cost $5.6M. That’s just a true statement. No one in their right mind includes the capital expenditure in that, the same way when you say “it took us 100h to train a model” that doesn’t include building a data center in those 100h.

    Beside whether they actually lied or not, it’s still immensely funny to me that they could’ve just told a blatant lie nobody factchecked and it shook the market to the fucking core wiping off like billions in valuation. Very real market based on very real fundamentals run by very serious adults.




  • don’t even get me started on “whole language learning” and “new math”

    I don’t know what “whole language learning” is, and I’m way too young to have experience it, but wasn’t the curriculum before “new math” like arithmetic and nothing else? In other words, not math at all?

    I didn’t read much into it but from what I did it seems like they started teaching children actual math like algebra and logic and parents got frustrated because they were too stupid to help with homework anymore. Brings into my mind the whole “math was cool before they involved letters” thing that makes me want to throw a book at someone.




  • This is a really weird comment. Assembly is not faster than C, that’s a nonsensical statement, C compiles down to assembly. LLVM’s optimizations will most likely outperform or directly match whatever hand-crafted assembly you write. Why would BEQ 1000 be “considerably faster” than if (x == y) goto L_1000;? This collapses even further if you consider any application larger than a few hundred lines of code, any sensible compiler is going to beat you on optimizations if you try to write hand-crafted assembly. Try loading up assembly code and manually performing intraprocedural optimizations, lol, there’s a reason every compiled language goes through an intermediate representation.

    Saying that C# is slower than C is also nonsensical, especially now that C# has built-in PGO it’s very likely it could outperform an application written in C. C#'s JIT compiler is not somehow slower because it’s flexible in terms of hardware, if anything that’s what makes it fast. For example you can write a vectorized loop that will be JIT-compiled to the ideal fastest instruction set available on the CPU running the program, whereas in C or assembly you’d have to manually write a version for each. There’s no reason to think that manual implementation would be faster than what the JIT comes up with at runtime, though, especially with PGO.

    It’s kinda like you’re saying that a V12 engine is faster than a Ferrari and that they are both faster than a spaceship because the spaceship doesn’t have wheels.

    I know you’re trying to explain this to a non-technical person but what you said is so terribly misleading I cannot see educational value in it.





  • This seems like yet another disconnect between however the fuck science communication has been failing the general public and myself.

    Like when you say space I think, fuck yeah, space! Those crisp pictures of Pluto! Pictures of black holes! The amazing JWST data! Gravitational waves detection! Recreating the conditions of the early universe in particle accelerators to unlock the secrets of spacetime! Just most amazing geek shit that makes me as excited as I was when I was 12 looking at the night sky through my cheap-ass telescope.

    Who gives a single fuck about sending people up there when we have probes and rovers, true marvels of engineering, feeding us data back here? Did you know Voyager 1, Voyager Fucking ONE, almost 50 years old probe, over 150 AU away from Earth, is STILL SENDING US DATA? We engineered the fuck of that bolt bucket so that even the people that designed it are surprised by how long it lasted. You think a human would last 50 years in the interstellar medium? I don’t fucking think so.

    We’re unlocking the secrets of the universe and confirming theories from decades ago, has there been a more exciting time to be a scientist? Wouldn’t you want to run a particle accelerator? Do science on the ISS? Be the engineer behind the next legendary probe that will benefit mankind even after you’re gone? If you can’t spin this into a narrative of technical progrees and humans being amazing then that’s a skill issue, you lack fucking whimsy.

    And I don’t think there’s a person in the world less whimsical than Elon fucking Musk.



  • CIDR 2025 is ongoing (Conference on Innovative Data Systems Research). It’s a very good conference in computer science, specifically database research (an equivalent of a journal for non-CS science). And they have a whole session on LLMs called “LLMs ARE THE NEW NO-SQL”

    I didn’t have time to read the papers yet, believe me I will, but the abstracts are spicy

    We systematically develop benchmarks to study [the problem] and find that standard methods answer no more than 20% of queries correctly, confirming the need for further research in this area.

    (Text2SQL is Not Enough: Unifying AI and Databases with TAG, Biswal et al.)

    Hey guys and gals, I have a slightly different conclusion, maybe a baseline 20% correctness is a great reason to not invest a second more of research time into this nonsense? Jesus DB Christ.

    I’d also like to shoutout CIDR for setting up a separate “DATABASES AND ML” session, which is an actual research direction with interesting results (e.g. query optimizers powered by an ML model achieving better results than conventional query optimizers). At least actual professionals are not conflating ML with LLMs.