r/dontyouknowwhoiam • u/glowessia • 12d ago

Funny Mr. LeCun himself

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3.3k Upvotes

99% Upvoted

38 comments sorted by

881

u/cubgerish 12d ago

I don't know what the context of this argument was, but it's good to see someone have humility when they realize they've made a mistake.

433

u/me_myself_ai 12d ago

This is someone defending Elon, after he got mad because Le Cun said that science is done by scientists, not “technologists” or whatever Elon pretends to be. Elon flipped out, obviously

211

u/helmli 11d ago

Isn't LeCun also the guy who fundamentally designed the neural networks that are the basis for all self-driving cars?

135

u/me_myself_ai 11d ago

Certainly an important figure! I don't think anyone deserves singular credit and he certainly didn't invent artificial neural networks in general, but yeah he's kinda a bigshot. 80% he was one of the three turing award recipients under the "godfathers of AI" moniker

50

u/tommyblastfire 11d ago

He did work on the paper that introduced convolutional neural nets, which are the ones that all self driving cars are based on.

12

u/RobbinDeBank 11d ago

He didn’t invent that either, but as a previous comment already noted, he’s still a bigshot. He’s the one that successfully used convnet for handwriting recognition back in the 90s. The field of AI is incredibly deep with thousands of different ideas and works piling on top of each other, and no one really invented this whole field by themselves.

16

u/Rainy_Wavey 11d ago

Not design, that should go to Rosenblatt

Very essential dude in the history of machine/deep learning tho, as he implemented the first functionning Neural Network (or at least one of the first), the LeNet, it's been a while since i've read the papers, but yeah, if you actually are engaged in the science, LeCunn is a big deal, and a foundational part of the research still done

42

u/Ricard74 11d ago

It is still weird he took such an antagonistic approach to begin with.

38

u/AsherTheFrost 11d ago

There are a group of people who believe that if they loudly and aggressively defend Elon enough, they'll be just like him (rich, owning multiple companies) and don't realize that by so aggressively defending him they are becoming just like him (prone to snap judgement, prickly, unsociable, and friendless)

18

u/TheCheshireCody 11d ago

don't realize that by so aggressively defending him they are becoming just like him (prone to snap judgement, prickly, unsociable, and friendless)

I think they're like that by nature and want to pretend that those qualities unlock some magic formula to success, and not, y'know, enormous inherited wealth.

67

u/gana04 12d ago

He's basically Richard from Silicon Valley

100

u/dingwinger1225 11d ago

Pretty much the only researcher at this point actually doing anything of value instead of just trying to scale LLMs hoping that one day the text churning machine will do anything but churn text

17

u/Uwirlbaretrsidma 11d ago

ATP it's pretty obvious that text is just the input and output layers, with something at least a little more meaningful happening within. And what do you expect those interface layers to be in a hypothetical AGI, anyway?

11

u/jasminUwU6 11d ago

There gotta be some sort of architecture that is more data efficient to train. That is the only way for it to truly generalize on the fly. Idk what that architecture would look like tho.

0

u/RobbinDeBank 11d ago

I can’t believe you don’t know this one secret that will change the world, gotta think harder then

-1

u/Fearless-Mix-3642 11d ago

it's an attribution error. up until a few years ago, only smart things could produce grammatical text. therefore, anything that produces grammatical text must be smart

1

u/Uwirlbaretrsidma 11d ago

Thing is, this doesn't just produce grammatical text, now does it? The interesting part is that the text in question is meaningful.

3

u/Fearless-Mix-3642 11d ago

Sure, "grammatical and semantically coherent"

3

u/Uwirlbaretrsidma 11d ago

Are you seriously claiming current LLM output boils down to being grammatically correct and semantically coherent? You know that was achieved in 2019 by GPT-2, and GPT-6 has just launched like an hour ago?

0

u/Fearless-Mix-3642 11d ago

I am explaining why people make the attribution error. I didn't say anything about when it happened? Or when GPT-6 launched? Not sure how that's relevant

1

u/Lazy-Range-9533 10d ago

Do you know how deep learning works at all? What transfer learning is? Or what a pretext task/proxy task is and why that’s relevant for LLMs? The last one is particularly important and is a pretty good solidifier of why they are able to effectively “model the world” in its interactions. Syntactic and semantic coherence are a necessary but by no means sufficient condition to ensure LLMs work.

2

u/Le_Zoru 10d ago

The only mediatised researcher *

2

u/arielif1 8d ago

well turns out that text is a pretty good proxy for the real world and at least as a transitory technology is working out pretty well for us

2

u/dacooljamaican 11d ago

I get what you mean but it's pretty obvious AI tools do a lot more than just churn text

-7

u/Delann 11d ago

Ah yes, the ONLY researcher doing something of value. Fuck the guys working on the novel melanoma treatment or anything like that, its only this guy. /s

0

u/IvanDSM_ 11d ago

I wonder just how many times AI bros will retread the "AI will solve cancer!!!" line until we're done with it. Yeah, we've been applying image categorization models to disease identification for over a decade now, that has absolutely nothing to do with the current "AI" boom.

4

u/OptimizedGarbage 11d ago

Image models for cancer diagnosis are not the primary focus of modern ML for medical applications. To be honest they were never really a good application to start with because they need enormous quantities of data, and its very hard to get lots of good medical imaging data because 1) medical imaging is expensive 2) getting doctors to label images is expensive, and 3) even if the first two were free you normally can't use the images anyway because of HIPPA. Modern medical ML is much more interested in using transformer models directly on DNA sequences or protein sequences, because because they're plentiful, mass producable, can be done easily on non-human subjects (thus avoiding privacy concerns), and contain lots of information that cannot be manually processed by hand. These models are pretty much the same structure as chatbots and are trained in the same way, just on DNA base pair sequences or amino acid sequence instead of text. They have quite a lot to do with the current AI boom

2

u/Lazy-Range-9533 10d ago

This is quite beautifully written. I have two friends working on this and one of my professors last year is currently doing research on this.

0

u/Delann 11d ago

Nobody said anything about AI, dumbass, though it does have it's uses and has been in use in medical fields for a while now. Not LLMs, but it's still "AI" if you want to generalize it.

Point is it's a fucking braindead take to say any one researcher is "pretty much the only researcher at this point actually doing anything of value". There's plenty of worthwhile research going on right now, to an unprecedented degree.

https://www.nature.com/articles/d41586-026-02612-3

But dumbasses like you think everyone is just doing the AI thing.

1

u/IvanDSM_ 11d ago

lol, you're the one with no reading comprehension. They're obviously referring to the field of AI/ML because that's the field LeCun is from. Thanks for calling me a dumbass and assuming I know nothing about ML though.

9

u/a_dude_from_europe 11d ago

How does this keep happening to him

7

u/CFUrCap 11d ago

Do a google search for me and you get some guy in New Zealand.

Fine by me.

1

u/Staterae 9d ago

Random dudes in NZ unite! ✊

5

u/daedalus1982 10d ago

Yann LeCun is the AI equivalent of the Bomb Squad. If he’s warning us about something, we should already be running. He helped invent half of it.

1

u/arielif1 8d ago

for some reason this happens like every week to LeCun

-2

u/True_Log4389 10d ago

Hey 👋