Giuseppe Attardi

[Giuseppe Attardi @gattardi]

@flavia_marzano @Roma Discussione sul sesso degli angeli?

[Noam Brown @polynoamial]

Today, I’m excited to share with you all the fruit of our effort at @OpenAI to create AI models capable of truly general reasoning: OpenAI's new o1 model series! (aka 🍓) Let me explain 🧵 1/

[Giuseppe Attardi @gattardi]

@fchollet Not really. They build generalizations of those patterns represented as averages of weights among a multiplicity of elements. Eg word embeddings represent similarities among word features, attention weights represent influences of words with each other in context.

[Jon Erlichman @JonErlichman]

“There is a 50-50 chance AI will get more intelligent than humans in the next 20 years. We’ve never had to deal with things more intelligent than us. And we should be very uncertain about what it will look like.”

~ Geoffrey Hinton

[Giuseppe Attardi @gattardi]

@fchollet @Carnage4Life Whether it was a good job or not it does not change the fact that they lost it.

[Percy Liang @percyliang]

We should call models like Llama 3, Mixtral, etc. “open-weight models”, not “open-source models”. For a model to be open-source, the code and training data need to be public (good examples: GPT-J, OLMo, RedPajama, StarCoder, K2, etc.). Weights are like an exe file, which would be ridiculous to call open-source.

[clem 🤗 @ClementDelangue]

I share @AndrewYNg's serious concerns with much of the open-source and broader AI community about California’s SB-1047 proposal.

Among many issues, the covered models definitions, shutdown capability, and enormous cost for compliance would be a huge blow to both CA and US innovation.

The practical effects would actually contradict intent: these barriers stop developers from contributing to safer models and will concentrate power and risks.

The new amendments are not enough and I hope more of the AI community speaks up!

[Giuseppe Attardi @gattardi]

@ylecun Regulators should concentrate first on establishing people rights, then by consequence whatever hurts those rights should be illegal and punished. Decisions on who is guilty and the amount of the pain should be left to courts or specific authorities. GDPR works like this.

[Giuseppe Attardi @gattardi]

@GoogleDeepMind Why do robots playing soccer need arms?

[Giuseppe Attardi @gattardi]

@chrmanning @JulieKallini and Parisi answered: that LLM are complex systems applying the probability of the next word is a beatiful idea. But I don’t know how to verify it.

[Giuseppe Attardi @gattardi]

@chrmanning @JulieKallini One explanation is that they are complex systems. As Nobel Giorgio Parisi explains, the behavior of complex systems arises from the application at large scale of a simple probabilistic law. I asked him: LLM apply at large scale the simple probability distribution of the next word

[Giuseppe Attardi @gattardi]

@headinthebox I didn’t know you were into LLMs. The last time I met you, you were into C#.

[Giuseppe Attardi @gattardi]

@ENiKS_CZ @ylecun I first heard it from Alan Kay, speaking of his work on the Alto at Xerox PARC.

His second quote, mentioned by Steve Jobs while introducing the iPhone, is: "If you are serious about software, you should build your own hardware".

[Giuseppe Attardi @gattardi]

@ylecun I agree on the immense potential of intelligent personal assistants: they might redeem us from the slavery of performing tasks that companies used to handle with their expert personnel, forcing us in practice to work for them so that they can reduce their labor costs.

[Giuseppe Attardi @gattardi]

@mpshanahan @CACMmag "By implication, it knows nothing about that per-
son. It has no understanding of what
they want to know nor of the effect its
response will have on their beliefs."
You just said a few paragraphs earlier not to use terms like knows, understand, believes.

[Andrew Ng @AndrewYNg]

My takeaways from attending WEF at Davos last week:
- There were lots of discussions on business implementation of AI. My top two tips: (i) Pretty much all knowledge workers can benefit from using GenAI now, but most will need training. (ii) Task-based analysis of jobs is helping businesses identify opportunities.
- Also lots of AI regulation conversations. I'm happy to report that the conversation is much more sensible than 6 months ago. For example, the unnecessary fears and discussion on AI extinction risk is fading away. But some big companies are still pushing for stifling, anti-competitive regulations, and the fight to protect open-source is still far from won.
- Attending climate sessions made me even more worried about the lack of action to change our planet's trajectory. Rather than 1.5 degrees Celsius of warming as the optimistic case and 2 degrees as the pessimistic case, I think 2 degrees is an optimistic case, and 4 degrees a more realistic pessimistic case. Decarbonization remains critical; and unfortunately, that we're talking about 1.5-2 degrees rather than 2-4 degrees means we're underinvesting in resilience, adaptation, and potentially game-changing technologies like geo-engineering.

Longer writeup below in The Batch: https://t.co/ZkdsgeF6WU

[Giuseppe Attardi @gattardi]

r1 is an AI assistant that can learn how to perform complex tasks for you, overcoming the idiosynchrasies of current GUI: https://t.co/J5aIUCNwYP

[Giuseppe Attardi @gattardi]

@stevelizcano @yoavgo If that was so, they had over a year to think about it. Why their decision came suddenly after just an hour of discussion? Could they have told Altman before to change his course?

[Jordan Chase-Young @jachaseyoung]

FINALLY: AI xrisker Nick Bostrom regrets focusing on AI risk, now worries that our fearful herd mentality will drive us to crush AI and destroy our future potential. (from an UnHerd podcast today)

Nick Bostrom: It would be tragic if we never developed advanced artificial intelligence. I think it's a kind of a portal through which humanity will at some point have to passage, that all the paths to really great futures ultimately lead through the development of machine superintelligence, but that this actual transition itself will be associated with major risks, and we need to be super careful to get that right.

But I've started slightly worrying now, in the last year or so, that we might overshoot with this increase in attention to the risks and downsides, which I think is welcome, because before that this was neglected for decades. We could have used that time to be in a much better position now, but people didn't. Anyway, it's starting to get more of the attention it deserves, which is great, and it still seems unlikely, but less unlikely than it did a year ago, that we might overshoot and get to the point of a permafrost--like, some situation where AI is never developed.

Flo Read: Like a kind of AI nihilism that would come from being so afraid?

NB: Yeah. So stigmatized that it just becomes impossible for anybody to say anything positive about it, and then we get one of these other lock-in effects, like with the other AI tools, from surveillance and propaganda and censorship, and whatever the sort of orthodoxy is--five years from now, ten years from now, whatever--that sort of gets locked in somehow, and we then never take this next step. I think that would be very tragic.

I still think it's unlikely, but certainly more likely than even just six or twelve months ago. If you just plot the change in public attitude and policymaker attitude, and you sort of think what's happened in the last year--if that continues to happen the next year and the year after and the year after that, then we'll pretty much be there as a kind of permanent ban on AI, and I think that could be very bad. I still think we need to move to a greater level of concern than we currently have, but I would want us to sort of reach the optimal level of concern and then stop there rather than just kind of continue--

FR: We need to get to a kind of Goldilocks level of feeling about AI.

NB: Yeah. I'm worrying that it's like a big wrecking ball that you can't really control in a fine-grained way. People like to move in herds, and they get an idea, and then--you know how people are. I worry a little bit about it becoming a big social stampede to say negative things about AI and then it just running completely out of control and sort of destroying the future in that way instead. Then, of course, we go extinct through some other method instead, maybe synthetic biology, without even ever getting at least to roll the die with the...

FR: So, it's sort of a 'pick your poison'.

NB: Yeah.

FR: It just so happens that this poison might kill you or might poison you, and you just kind of have to roll the dice on it.

NB: Yes. I think there's a bunch of stuff we could do to improve the odds on the sequence of different things and stuff like that, and we should do all of those.

FR: Being a scholar of existential risk, though, I suppose, puts you in the category or the camp of people who are often--this show being an example--asked to speak about the terrifying hypothetical futures that AI could draw us to. Do you regret that focus on risk?

NB: Yeah, because I think, now--there was this deficit for decades. It was obvious--to me at least, but it should have been pretty obvious-- that eventually AI was gonna succeed, and then we were gonna be confronted with this problem of, "How do we control them and what do we do with them?" and then that's gonna be really hard and therefore risky, and that was just neglected. There were like 10,000 people building AI, but like five or something thinking about how we would control them if we actually succeeded. But now that's changed, and this is recognized, so I think there's less need now maybe to add more to the sort of concern bucket.

FR: The doomerist work is done, and now you can go and do other things.

NB: Yeah. It's hard, because it's always a wobbly thing, and different groups of people have different views, and there are still people dismissing the risks or not thinking about them. I would think the optimal level of concern is slightly greater than what we currently have, so I still think there should be more concern. It's more dangerous than most people have realized, but I'm just starting to worry about it then kind of overshooting that, and the conclusion being, "Well, let's wait for a thousand years before we do that," and then, of course, it's unlikely that our civilization would remain on-track for a thousand years, and...

FR: So we're damned if we do and damned if we don't.

NB: We will hopefully be fine either way, but I think I would like the AI before some radical biotech revolution. If you think about it, if you first get some sort of super-advanced synthetic biology, that might kill us. But if we're lucky, we survive it. Then, maybe you invent some super-advanced molecular nanotechnology, that might kill us, but if we're lucky we survive that. And then you do the AI. Then, maybe that will kill us, or if we're lucky we survive that and then we get to utopia.

Well, then you have to get through sort of three separate existential risks--first the biotech risks, plus the nanotech risks, plus the AI risks, whereas if we get AI first, maybe that will kill us, but if not, we get through that, then I think that will handle the biotech and nanotech risks, and so the total amount of existential risk on that second trajectory would sort of be less than on the former.

Now, it's more complicated than that, because we need some time to prepare for the AI, but you can start to think about sort of optimal trajectories rather than a very simplistic binary question of, "Is technology X good or bad?" We might more think, "On the margin, which ones should we try to accelerate, which ones retard?" And you get a more nuanced picture of the field of possible interventions that way, I think.

[Giuseppe Attardi @gattardi]

@ClementDelangue I keep saying this. At a keynote on LLMs by Dan Roth I objected that he was criticising the abilities of ChatBots, which are applications of LLM, to LLMs themselves. There is an imbalance there: the former are trained on billions of tokens while the latter on smaller datasets.