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S1: A $6 R1 competitor?

timkellogg.me

31–40 of 430 posts

Re: S1: A $6 R1 competitor?

#31
> Going forward, it’ll be nearly impossible to prevent distealing (unauthorized distilling). One thousand examples is definitely within the range of what a single person might do in normal usage, no less ten or a hundred people. I doubt that OpenAI has a realistic path to preventing or even detecting distealing outside of simply not releasing models.

(sorry for the long quote)

I will say (naively perhaps) "oh but that is fairly simple". For any API request, add a counter of 5 seconds to the next for 'unverified' users. Make the "blue check" (a-la X/Twitter). For the 'big sales' have a third-party vetting process so that if US Corporation XYZ wants access, they prove themselves worthy/not Chinese competition and then you do give them the 1000/min deal.

For everyone else, add the 5 second (or whatever other duration makes sense) timer/overhead and then see them drop from 1000 requests per minutes to 500 per day. Or just cap them at 500 per day and close that back-door. And if you get 'many cheap accounts' doing hand-overs (AccountA does 1-500, AccountB does 501-1000, AccountC does 1001-1500, and so on) then you mass block them.

Re: S1: A $6 R1 competitor?

#32
post #30
post #8

> If you believe that AI development is a prime national security advantage, then you absolutely should want even more money poured into AI development, to make it go even faster. This, this is the problem for me with people deep in AI. They think it’s the end all be all for everything. They have the vision of the ‘AI’ they’ve seen in movies in mind, see the current ‘AI’ being used and to them it’s basically almost t…

Yes, I'd like to see some examples where our current AI can actually extrapolate rather than interpolate. Let it invent new things, new drawing styles, new story plots, etc. Maybe _then_ it will impress me.

Here you go: https://www.biorxiv.org/content/10.1101/2024.11.11.623004v1

Re: S1: A $6 R1 competitor?

#33

> having 10,000 H100s just means that you can do 625 times more experiments than s1 did I think the ball is very much in their court to demonstrate they actually are using their massive compute in such a productive fashion. My BigTech experience would tend to suggest that frugality went out the window the day the valuation took off, and they are in fact just burning compute for little gain, because why not...

Mainly it points to a non-scientific "bigger is better" mentality, and the researchers probably didn't mind playing around with the power because "scale" is "cool".

Remember that the Lisp AI-labs people were working on non-solved problems on absolute potatoes of computers back in the day, we have a semblance of progress solution but so much of it has been brute-force (even if there has been improvements in the field).

The big question is if these insane spendings has pulled the rug on real progress if we head into another AI winter of disillusionment or if there is enough real progress just around the corner to show that there is hope for investors in a post-deepseek valuation hangover.

Re: S1: A $6 R1 competitor?

#34
post #8

> If you believe that AI development is a prime national security advantage, then you absolutely should want even more money poured into AI development, to make it go even faster. This, this is the problem for me with people deep in AI. They think it’s the end all be all for everything. They have the vision of the ‘AI’ they’ve seen in movies in mind, see the current ‘AI’ being used and to them it’s basically almost t…

What is even the possible usage of AI for national security? Generating pictures of kittens riding nuclear weapons to the very end like in Dr Strangelove?

Re: S1: A $6 R1 competitor?

#36
post #14

Earlier quoted context omitted.

Like a lot of AI boosters, would you like to explain how that works other than magic AI dust? Some forms of optical guidance are already in use, but there's other limitations (lighting! weather!)

Sure thing. The basic idea would be: 1) Have a camera on your drone 2) Run some frames through a locally running version of something like AWS Rekognition's celebrity identification service but for relevant military targets. 3) Navigate towards coordinates of target individuals It isn't exactly magic, here's a video of a guy doing navigation with openCV on images: https://www.youtube.com/watch?v=Nrzs3dQ9exw

I believe this is a capability that the Switchblade 600 or STM KARGU already has.

https://en.wikipedia.org/wiki/STM_Kargu

Re: S1: A $6 R1 competitor?

#37
post #8

> If you believe that AI development is a prime national security advantage, then you absolutely should want even more money poured into AI development, to make it go even faster. This, this is the problem for me with people deep in AI. They think it’s the end all be all for everything. They have the vision of the ‘AI’ they’ve seen in movies in mind, see the current ‘AI’ being used and to them it’s basically almost t…

Agreed. I was working on some haiku things with ChatGPT and it kept telling me that busy has only one syllable. This is a trivially searchable fact.

Re: S1: A $6 R1 competitor?

#38
post #8

> If you believe that AI development is a prime national security advantage, then you absolutely should want even more money poured into AI development, to make it go even faster. This, this is the problem for me with people deep in AI. They think it’s the end all be all for everything. They have the vision of the ‘AI’ they’ve seen in movies in mind, see the current ‘AI’ being used and to them it’s basically almost t…

It used to be much easier to be conservative about AI, especially AGI, after living through three cycles of AI winters. No more. Dismissing it as “merely machine learning” is worse than unfair to the last decade of machine learning ;-)

The hard part now is relatively trivial. Does anyone think that there is a fundamental and profound discovery that evolution made purely by selection in the last 200,000 years? I mean a true qualitative difference?

Sure—-We call it language, which is just another part of a fancy animal’s tool kit.

Does anyone think there is an amazing qualitative difference between the brain of a chimp and the brain of a human?

No, not if they know any biology.

(Although that does not stop some scientist from looking for a “language gene” like FOXP2.)

So what did dumb mutations and 200,000 years of selection do that a group of dedicated AI scientists cannot do with their own genuine general intelligence?

Nothing—-nothing other than putting a compact energy efficient LLM with reinforcement learning on a good robotic body and letting it explore and learn like we did as infants, toddlers and teenagers.

Each one of us has experienced becoming a “general intelligence”. I remember it hit me on the head in 6th grade when I dreamed up a different way of doing long division. I remember thinking: “How did I think that?” And each one of us who has watched an infant turn into a toddler has watched it as an observer or teacher. This is what makes babies so fascinating to “play” with.

We have to give our baby AGI a private memory and a layer of meta-attention like we all gain as we mature, love, and struggle.

I read the linked article and as a neuroscientist I realized the “wait” cycles that improved performance so much is roughly equivalent to the prefrontal cortex: the part of the CNS most responsible for enabling us to check our own reasoning recursively. Delay—as in delayed gratification—-is a key attribute of intelligent systems.

We are finally on the door step to Hofstadter’s Strange Loop and Maturana’s and Valera’s “enactive” systems, but now implemented in silicon, metal, and plastic by us rather than dumb but very patient natural selection.

Karl Friston and Demis Hassabis (two very smart neuroscientist) figured this out years ago. And they were preceded by three other world class neuroscientist: Humberto Maturana, Francisco Valera, and Rich Sutton (honorary neuroscientist). And big credit to Terry Winograd for presaging this path forward long ago too.

Re: S1: A $6 R1 competitor?

#39
Off topic, but I just bookmarked Tim’s blog, great stuff.

I dismissed the X references to S1 without reading them, big mistake. I have been working generally in AI for 40 hears and neural networks for 35 years and the exponential progress since the hacks that make deep learning possible has been breathtaking.

Reduction in processing and memory requirements for running models is incredible. I have been personally struggling with creating my own LLM-based agents with weaker on-device models (my same experiments usually work with 4o-mini and above models) but either my skills will get better or I can wait for better on device models.

I was experimenting with the iOS/iPadOS/macOS app On-Device AI last night and the person who wrote this app was successful in combining web search tool calling working with a very small model - something that I have been trying to perfect.

Re: S1: A $6 R1 competitor?

#40
The part about taking control of a reasoning model's output length using tags is interesting.

> In s1, when the LLM tries to stop thinking with "", they force it to keep going by replacing it with "Wait".

I had found a few days ago that this let you 'inject' your own CoT and jailbreak it easier. Maybe these are related?

https://pastebin.com/G8Zzn0Lw

https://news.ycombinator.com/item?id=42891042#42896498

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