Yann has been a refreshing source of reason and common sense with regards to AI safety, regulation and open-source. I wish we had more people like him and less AI doomer cultists.
People like his takes because he gives an authoritative gloss to what they already believe. But his points are usually lacking in argument or rigor. Anyone that essentially expects the public to trust them when it comes to the outcome of AI/AGI should be view with suspicion.
On the contrary, he gives good arguments about why open is safer and closed is more dangerous whereas other side gives, imho, convoluted arguments and asks for them to be proven wrong (as opposed to trying to prove themselves right).
His arguments in defense of barreling forward with AI are terrible. They have zero chance to convince someone who doesn't share his intuitions/interests. For example: https://twitter.com/ylecun/status/1718764953534939162
How easily smart people convince themselves of what they want to be true with zero self-awareness makes me much more fearful of what's to come.
>other side gives, imho, convoluted arguments and asks for them to be proven wrong (as opposed to trying to prove themselves right).
The question is what should our default stance be until proven otherwise? I submit it is not to continue building the potentially world-ending technology.
Burden of proof is a tragically misapplied concept. The question is what position should be the default given some uncertainty? This isn't decided in a vacuum. The default should be decided based on the facts and utility estimates of various outcomes where relevant. In the case where the issue is of purely academic interest, the burden of proof is on those making the claim. When the issue has real world consequences, then utility estimates of various outcomes are the overriding concern.
When you see a gun on the table, what do you do? You assume its loaded until proven otherwise. For some reason, those who imagine AI will usher in some tech-utopia not only assume the gun is empty, but that pulling the trigger will bring forth endless prosperity. It's rather insane actually.
> The default in science is that the side arguing a point has the burden of proving it correct
Right, and Yann is arguing the point that AI and LLMs are not or will not be dangerous. Where's his proof? As the parent posters have said, he has none.
I've read a fair bit of LeCunn and frankly have been very unimpressed. He is, as far as I can tell, the only big AI name who doesn't think that if we somehow managed to make an actual superintelligent AI it wouldn't be dangerous.
And his reasoning for it is absurd, a combination of evolutionary psychology (not the most scientifically rigorous field to begin with and not even his field) and the belief that no one would choose to make an unsafe AI system, while simultaneously arguing for open sourcing everything so that anyone on the planet can do so if they want.
His reasoning is that good guy’s AI will counteract bad guy’s ones or a an AI that has developed his own objective against humanity if that happens, which is I think a reasonable argument.
He effectively is arguing that the "good guys" will develop a superhero AI that will protect us simply because it feels that is the right thing to do. I'm not sure how any logical basis can be used to back that up, or where any meaningful example of similar behavior that didn't ultimately lose to the "bad guys" can be found in human history.
In the 20th century this same thinking lead to MADD and massive stocks of nuclear weapons that still present an existential threat to humanity. Depending on the scaling potential of intelligence this just adds further risks at this level, not less or balanced risks.
This was a view that was initially taken by the government for encryption as well. But everyone can agree open sourcing the algorithms and libraries has been the best move.
It is the same with AI/AGI. Anything closed source and having regulatory oversight is useless, decreases innovation, increases bureaucracy and will only serve those who wish to build a “moat” to further their hold on the technology.
Sure, open source worked well for encryption. It wouldn't work well for bioweapons or nuclear weapons technology. The question is which category does AGI best fit? We shouldn't elide analysis for obtuse comparisons to the past.
> Anything closed source and having regulatory oversight is useless
Source isn't even the problem, unless you're a billionaire, you can't afford to train the model.
This isn't the wheel, the printing press, the PC, or the public internet, which created opportunities for everyone.
This is pay-to-play that is only affordable to the nation-state the mega-corporation, and the latter might let you play around as a digital sharecropper on their platform, until they cut you off, because they can make more money by having first-party ownership of whatever you built.
The model is the instance because the instance is what is being used at inference time. The training simply produces some set of weights.
Open source would mean someone could see and run the model code locally/independently to create an instance. For an LLM, this is much less insurmountable of an issue in terms of resources needed.
We should probably be calling for an open model or open data approach if that's what we think is best.
Calling it open source leaves plenty of gray area in the definition.
For example, I run a few instances of open source software though my instances' databases are private.
We are still answering questions on LLM/AI scaling. Ya, you might have your cottage industry AI giving out answers on the trickle of information you feed it, but will that even be comparable to one being fed megawatts of power with terabytes of data per second flowing into its databanks?
At the same time, it seems like some antidote is needed to the breathless, quasi-mystical hype that cryptic OpenAI claims seem designed to stoke. Demanding precise and substantive criticisms of something about which almost no technical details have been provided seems like an unfair bar.
But the post links to Twitter (X.) That's the wrong place for argument or rigor. But do you really need that? Seems to me like his post is essentially saying "Pay attention to all this stuff which people have been working on for a long time." He's just casting a vote. The argument and rigor is already there for further reading. That's interesting for me, because I don't know much about the topic. If you already know all this stuff, then maybe it's not interesting.
I mean I don’t think predicting the future is something that typically involves rigor. The outcome is pretty clear: whatever makes a ton of money. Probably a trusted friend in your pocket that sometimes helps you buy stuff. The most negative predictions are silly because they don’t involve making a ton of money for anybody.
The point about money is important, but we should also keep in mind most outcomes will make a ton of money for someone somewhere.
Hell, there's wars killing tens of thousands of people going on right now, and a ton of money is changing hands making a juicy business for whole industries.
> I wish we had more people like him and less AI doomer cultists.
There are many sources like him, often with even more detail and references. The problem is that these people are not famous and thus do not have as many followers and are less likely to make it into your feeds. Lots of grad students are in this region as they write to help increase their name and visibility due to the need to market one's self. Don't be afraid to look at those who are not from big name schools. Instead look for those that are willing to mention details and nuance. But this may be hard to accurately determine being on the outside, but that's the thing hype people take advantage of. I don't think they're malicious, but if you're the "smartest person in the room" it's easy to think you're the smartest person in many rooms and have a high confidence in bullshit. For example, we see such comments on places like Reddit and HN. I'm not sure if there's a good way to realistically filter out non-experts from experts (I don't think we should require credential checking). But experts are probably usually more boring as is reality to fantasy.
Yann LeCun is a clown lol. The Chief AI Scientist at _Facebook_ of all companies expects me to just trust him when he says "it'll be safe guys, we'll figure it out, we wouldn't release anything that was harmful :)"