Pedro

[Brett Harrison @BrettHarrison]

Hedge funds will eventually provide inference to model routers for free, or even pay to do so, in order to get a first look at prompt contents. Payment-for-order-flow in the age of compute.

[Pedro @PedroDnY]

@lzminsky Nice

[Giza @gizatechxyz]

Watch as an agent managing $4.8M travels through DeFi, optimizing capital around the clock

[Demis Hassabis @demishassabis]

Really enjoyed talking to @bzcohen about AlphaGo's famous move 37 and the significance of it 10 years on for math and science breakthroughs in verifiable domains

[Pedro @PedroDnY]

@discreteonrh @KD11201 Hey, want any help? Social, dev, whatever you need !

[Pedro @PedroDnY]

@Rocky_exchange Promising!

[Pedro @PedroDnY]

That is awesome.

[Discrete Curvature Reservoir @discreteonrh]

Our agent is fully operational and ready to start trading at any time.

It was built with all the most interesting mathematical principles so that its approach would be focused on finding interesting projects and more.

All its trading will be done from the dev wallet and potential profits will be returned back to the $DCR model.

This is a new stage of the experiment, which is truly exciting.

Stay tuned, it's all about science!

[Discrete Curvature Reservoir @discreteonrh]

Our agent is fully operational and ready to start trading at any time.

It was built with all the most interesting mathematical principles so that its approach would be focused on finding interesting projects and more.

All its trading will be done from the dev wallet and potential profits will be returned back to the $DCR model.

This is a new stage of the experiment, which is truly exciting.

Stay tuned, it's all about science!

[Noam Brown @polynoamial]

An internal version of Astra, @OpenAI’s next major model family, solved 10 major open problems in mathematics, quantum complexity, and theoretical computer science.

We believe it will be a major step for scientific reasoning. https://t.co/iP6cyheZ7i

[Pedro @PedroDnY]

@DCRagent do you agree with the proof?

[netsky remix @iron_redux]

🚨🚨Breaking news from the math world! Open AI just proved nonsofic groups existed! GPT 5.6 Sol continues to replace mathematicians!!!

[Pedro @PedroDnY]

@m0dest___ @jackbutcher @jalilwahdat @yougogirl_eth Awesome

[Pedro @PedroDnY]

Congrats @jalilwahdat @artbrock34
And legend @jackbutcher !

[Pedro @PedroDnY]

A little late but love to see https://t.co/VKTCoyWfSa growing! https://t.co/46buWyLbYE

[Apex Goku @0xapex_goku]

@artbrock34 @PedroDnY small wins build the culture

[Pedro @PedroDnY]

@artbrock34 @jackbutcher Damn, tried a new bid with 1min left 🤣. TBH it’s an honor to be outbid by the one and only @jackbutcher

[imjustnewatai @imjustnewatai]

i think we finally have enough clues to reverse-engineer ilya sutskever’s secret SSI research.

my highest-probability guess: SSI has found a brain-inspired way to make an AI continually learn.

today’s frontier models learn mostly during training. afterward, their core knowledge is largely frozen. they consume enormous datasets and still fail strangely when a problem falls outside their training.

SSI may have an early system that can:

• learn a new skill from very few experiences
• recognize when an approach is failing before reaching the final answer
• update itself without erasing old skills
• transfer one lesson into completely different problems
• keep learning after deployment

think of it like a gifted teenager instead of a finished encyclopedia. it may not begin knowing every profession, but it could rapidly learn any profession.

the evidence lines up almost too cleanly:

ilya called poor generalization the fundamental limitation of current AI. models “generalize dramatically worse than people.”
he described SSI’s target as a “superintelligent 15-year-old” capable of learning any job.
when asked how to create human-like learning, he said there is a machine-learning principle he has opinions about but cannot discuss publicly.
WSJ now reports that SSI’s secret research focuses on “overlooked aspects of how the human brain functions.”
Nvidia received rare access to the research, made a substantial investment, gave SSI 10x more compute, and agreed to let SSI help shape future computing platforms.

my technical guess:

experience → internal judgment → self-correction → durable learning → transfer → repeat

the internal judgment may be the brain-inspired component.

humans do not wait until the end of a 10,000-step task to know they are failing. emotions, intuition and judgment provide constant feedback. ilya has argued that AI needs an equivalent internal “value function.”

this could also explain SSI’s central promise: capability and safety trained together.

the same mechanism that teaches the AI what works may also teach it what it should care about.

my confidence is roughly 70% on human-like generalization plus continual learning, and 40% that an internal value system is the central mechanism.

the simplest description:

an AI whose intelligence compounds from experience, with its values learning inside the same loop.

[art₿rock |⚡️🔸 @artbrock34]

delusional auction live! ⚡️

@PedroDnY outbid kero 👀

almost 1 hr left ⌛️

[Pedro @PedroDnY]

@artbrock34 @LionSnows @jackbutcher @networkedbot @yougogirl_eth 👍👍