Cédric

building open-ended autotelic agents
& making little art projects

[Cédric @cedcolas]

@Voltaine1 very cool!

[Cédric @cedcolas]

@humansand new off-policy RL algorithm for extremely long horizon rollouts 👀

[Cédric @cedcolas]

@joelbot3000 @E_FutureFan Yes you're probably right that filtering out the big chunk of obvious slop is both easy and will matter

[Cédric @cedcolas]

@joelbot3000 The way I use it doesn't necessarily make me save any time though, but I think the result is better than without it.

I do agree AI slop is bad obviously, just arguing with the "we will detect it later" and the conflation of AI-shaped writing and AI slop

[Cédric @cedcolas]

@joelbot3000 AI-shaped writing is not equal to AI slop. We'll get good detectors of the former, not of the latter (sometimes subjective).

I use AI for writing papers now and I don't think the result is AI slop.

[Edward Grefenstette @egrefen]

Hot damn!

Congrats on the AGI, @OpenAI! 😉

https://t.co/sRlYnrdMqK

[Cédric @cedcolas]

@SakanaAILabs Let's open an office in Paris :)
@hardmaru

[Cédric @cedcolas]

@TylerAlterman ooo that's not easy
my try:
https://t.co/jJ4dgUwcck

[Cédric @cedcolas]

@smdvln thanks for reading and looking forward to chatting more in the future!

[Cédric @cedcolas]

@smdvln it seems that LLMs can do it on their own now (see Astra solving ARC 3 tasks by mapping states and dynamics to symbols and running simulations forward)
I think our point was more that you need to do that in one way or another

[Cédric @cedcolas]

@smdvln https://t.co/Hfar2WOvBX

[Cédric @cedcolas]

@smdvln We made the same point in our perspective paper on evaluating AI systems’s capacity for adaptation

eg the app store is the output of an open-ended cultural process that always finds new exciting games requiring players to adapt

evaluation systems should look like that too!

[Cédric @cedcolas]

@alexisjross @314Bansal sounds amazing!
does it reason more like people or just talks more like people (eg in non social/conversation settings)

[Marko Cvjetko @marko_cvjetko]

🧵 New paper: RL for discovering and controlling self-organizing phenomena.

We introduce CARL, a closed-loop agent that learns to create self-organizing patterns in Lenia, steer their behavior, and let humans guide them in real time.

Project website + interactive demos below ↓

[Niloofar @niloofar_mire]

Privacy policies on almost all frontier model providers are insane and assuming you have ZDR or any meaningful protection, even on enterprise setting is completely false these days!

Here I'm going to name a few very arbitrary and misleading sentences in ToS of frontier labs that most ppl don't know about. This is all assuming you have already *opted-out*, explicitly of data collection. Default for all frontier models is opt in btw!!

1) the 'explicit feedback': your chats are claimed to be 'protected' unless you provide feedback! what is feedback, you ask? it's thumbs up or down to any message in the chat, or even if you pick 'which is better' response on OpenAI GUI. In that case, you have provided explicit feedback and your chat is collected and retained for *over 7 years*!

[Cédric @cedcolas]

@timourxyz would love to chat!

[Cédric @cedcolas]

I also think we now have the tools for developing AI-based systems that augment human collective intelligence

a first step: https://t.co/tDSM8YshNy

[timour kosters @timourxyz]

I’ve been thinking about a concept like a “coordination overhang.”

It is the gap between what any group of people could achieve in collaboration, vs what they actually achieve. I think the agents used as coordination technology could help meaningfully decrease the gap.

Any group of people (e.g. teams, labs, communities), has latent potential for what they could do together. There is some much better version of the collaboration where the right questions come up, relevant knowledge gets surfaced, hidden complementarities are discovered, and everyone leaves knowing what to do next.

Reality usually lands somewhere below that. Each person enters with only a partial view of what everyone else knows, has tried, is curious about, and can contribute. A group can have an excellent conversation and still miss the most valuable thing it could have done together.

Simple example: two individuals meet at a conference. One has been stuck on a problem for months, while the other has already developed a method that could help solve it. Neither side realizes the connection, so they have a perfectly good conversation about their work and move on. Sometimes those things are naturally uncovered and it feels serendipitous. But intuitively it's likely that is a lot more that goes unsaid.

AI agents could become a new coordination technology for closing this gap. They could analyze everything people have been working on, identify relevant overlaps before they meet, bring the right context into the conversation, run analysis across the group’s combined knowledge, and then provide the tools to turn a promising connection into actual work. They would essentially be cranking the dial on serendipity.

The people still decide what matters and whether to act. The agents make more of the group’s latent potential visible and actionable.

This is a high-level thought rn, but we at @JoinEdgeCity are working on improving these kinds of collective intelligence processes by running experiments using multi-agent systems.

h/t to the folks at @RenPhilanthropy and @indexnetwork_ for the work they're doing in developing these ideas with us.

[Cédric @cedcolas]

‘This incident feels like it’s more than 50% of the way to full-blown AI takeover. I continue to expect extremely rapid advances in capabilities over the next 6 months. I am not sure that we will get another warning shot before it’s too late.’

[Ajeya Cotra @ajeya_cotra]

New post: going into our investigation of the HF attack (before Black Hat), I was very wrong about what basically happened. This incident was far more serious than I expected, and far more serious than previous documented misalignment incidents. https://t.co/QWQxD2Q179

[Cédric @cedcolas]

I don't usually care for having robots all around us folding laundry and cooking omelets; but I do LOVE quirky little experimental robots like these

[Thomas Wolf @Thom_Wolf]

We have a huge news to share today!

Today we are unveiling the first truly accessible RL robot - welcome Microduck

A 25 cm tiny open-source biped with 15 actuators and packed with sensors (camera, speaker, LiDAR, NFC, bluetooth, wifi, etc) that you train yourself with reinforcement learning.

It's also playable out of the box with more than half a dozen fun and playful pre-trained policies to have it walk, sit, crouch, roller-skate, pick up objects with its articulated beak, and recover on its own.

And all for less than $400.

See all the details, play with the simulator and order it at: https://t.co/n1Btgs6vKw

(video with sound on 🔊)

[Cédric @cedcolas]

@j_foerst 👀