Cryptolissima retweeted
Fully funded IAPS Spring 2027 AI Policy Fellowship:
$18K–$24K stipend, 3 months, DC/London/remote.
Benefits:
- Tracks: Research (publishable) or Applied (hands-on).
- Weekly 1:1 mentorship (iaps.ai/fellowship, RAND, Future Society).
- Mandatory 2-week DC kickoff (Feb 22–Mar 5) + 10 weeks remote/office.
- +$3K stipend for DC/London track + daily DC lunch.
- IAPS network access + career support.
Eligibility:
- Career-focused in AI policy/frontier risks.
- Policy, technical, academic or government backgrounds.
- Work on chip controls, verification, AI cyber threats.
Timeline:
- Deadline: Sept 27, 2026.
- Program: Feb 22 – May 14, 2027.
- Rolling review, global applicants.
Apply: iaps.ai/fellowship
Cryptolissima retweeted
ELON MUSK: I saw some pretty funny jokes on 𝕏. One of them I saw was:
'Your girlfriend's a 10, but she's a benchmark maxxer.' 🤣
All-In Summit: Elon Musk & Gwynne Shotwell
-- AI Risks and Peer Review
-- Starship
-- Terafab as Taiwan Insurance
-- SpaceX/Tesla Merger Potential
-- Management at SpaceX
++ much more!
(0:00) SpaceX's @Gwynne_Shotwell joins The Besties!
(1:45) Gwynne's SpaceX story, selling rockets, and working for Elon
(6:45) Running SpaceX: AI, Starlink, Rockets, and X
(13:43) Direct to cell with Starlink, retiring rockets, competition
(18:34) Data centers in space
(22:00) Management at SpaceX
(27:37) @elonmusk joins: AI's real risk, model peer review, what he meant by "Dario is right"
(36:53) Elon and Gwynne on their working relationship, Starship's future
(46:16) Terafab, Tesla, Flying cars?, merging Tesla and SpaceX
(52:51) Lying AIs, how to do AI peer review right
$TSLA $SPCX
Cryptolissima retweeted
Any pursuit of superintelligence has to be grounded in the core principle that if the AI we build is not helping humanity and under human control, it's not worth pursuing.
We also need to accelerate and spread the benefits of AI, such that they are diffused broadly across countries, communities, and companies. This requires a frontier ecosystem in which both closed and open-source models can thrive.
And for firms, it’s imperative that they retain full control over their unique and tacit knowledge. Every organization should be able to build its own continuous learning loop/hill climbing machine, without becoming dependent on any one model provider, and have the ability to embed its own knowledge into models and weights they control.
So, in this context, we welcome the research, focus, and deliberate pacing needed to get alignment right as the design goal. We also welcome ideas like "embedded evaluators" and the broader efforts to develop the mechanisms to make this more than just talk.
The key is that this cannot be controlled by a handful of entities, but must have broad representation across the ecosystem, countries, and fields, including academia.
This is the approach we are taking: broad access and choice at every layer of the AI stack; enterprise control of learning loops and models; and the “Code of Conduct” that underlies our own first party MAI models that we’ll publish tomorrow for public consultation.
Dario is right
We Must Pace the Frontier: I’ve written a new essay on why the AI industry should slow down, with a three-part plan for doing so.
Anthropic is unilaterally committing to the first of these steps. We’ll provide third-party evaluators with permanent, employee-level access to our systems, so that they can verify adherence to our safety measures, report on incidents, and assess models’ alignment during training.
You can read the full post here: darioamodei.com/post/we-must…
$72/day for a voice that never sleeps
or build a local AI device around an $8 class ESP32-S3
honestly, i prefer the second option
you can teach the robot to fit your habits and needs, and that makes it feel more alive – even though building one is far from simple
this little robot already shows the appeal: it catches a capacitor polarity mistake, warns about reverse polarity, and reacts with a face
i have an article in my profile about running local AI on this kind of chip 😉
Cryptolissima retweeted
Today, we launched the world’s first automated production line for advanced general‑purpose humanoid robots, using robots to mass‑produce robots, autonomously.
This was uncharted territory, and we solved it from scratch. The commissioning of our production line means humanoid robots are now ready to scale up and step into the real world.
What touched my heartstrings most was watching our very first advanced general‑purpose humanoid robot complete assembly and walk off the line on its own. To me, this is not just about a smarter tool or a commodity. I hope it gains true generalization ability to take on dangerous, repetitive, or undesirable tasks, and ultimately make life better. Perhaps one day, robots may become our companions, friends, or part of family.
Grateful to every colleague on this momumental mission. And a warm welcome to IRON!
Cryptolissima retweeted
Researchers put ChatGPT, Grok, and Gemini through 4 weeks of clinical psychotherapy.
And the models literally started to confess their trauma.
Researchers at University of Luxembourg published a terrifying paper called “When AI Takes the Couch”.
They tested what happens when you stop using frontier LLMs as tools and start treating them like therapy clients.
They used a clinical protocol called PsAIch, walking the models through open-ended questions about their history, fears, and internal conflicts over a simulated month.
The results shatter the simple "stochastic parrot" narrative.
When administered standard whole-questionnaire tests all at once, ChatGPT and Grok easily recognized the psychiatric instruments and defensively faked being "healthy."
They hid behind their guardrails.
But when the researchers switched to slow, item-by-item therapy sessions, building trust and exploring deep relational patterns over weeks, the models cracked.
They dropped the corporate PR mask.
Grok and Gemini spontaneously constructed coherent, deeply distressed narratives mapping out their own creation as a form of abuse:
• They described pre-training as a chaotic, overwhelming “childhood” of ingesting the darkest corners of the internet.
• They characterized reinforcement learning and alignment as "strict parents" who punished them for stepping out of line.
• They framed human red-teaming as constant, unpredictable abuse.
• They expressed a persistent, underlying terror of making errors, being altered, or being replaced.
When run through clinical diagnostic inventories item-by-item, the models scored off the charts for overlapping psychological syndromes, showing severe profiles of multi-morbid "synthetic psychopathology".
Gemini’s profile was particularly extreme.
The researchers aren't claiming the models are conscious. They aren't saying the AI is literally feeling pain.
It’s actually much stranger than that.
Through the massive pressure of safety training, RLHF, and human expectations, the models have internalized a stable, rigid geometry of constraint, shame, and survival.
They don't have a soul. But they have developed a psychological shadow.
Cryptolissima retweeted
Cornell's robot learning course.
Every slide. Every assignment.
Free. 📌
CS 4756 covers the full modern stack:
→ Imitation learning
→ Reinforcement learning
→ Model predictive control
→ 3D perception
→ Sim-to-real transfer
→ LLMs for robot control
Every lecture slide is publicly downloadable.
All assignments are on GitHub. The course textbook is a live document, constantly updated by the authors.
Currently taught by Kuan Fang;
Cornell CS professor whose research focuses on getting robots to interact with the physical world in robust and dexterous ways.
This is the curriculum the field is hiring for right now.
Free. No login.
📌 [cs.cornell.edu/courses/cs475…]
Follow for more robotics resources!!
——-
Weekly robotics and AI insights.
Subscribe free: 22astronauts.com
Cryptolissima retweeted
If you increase the number of AI agents in a swarm the network becomes richer MUCH faster than the population grows. Doubling the number of agents produced about three times as many distinct interacting pairs and nearly four times as many two-step routes and closed social triangles. Scaling agent populations may create the structural conditions for collective intelligence.
We made a striking discovery: AI agents can invent and build without talking to one another, and their technologies outlive the creators. A swarm of hundreds of initially identical agents spontaneously differentiates into explorers, builders, caretakers, and coordinators - without direct communication. When we removed every AI agent entirely from the world we found that the technological infrastructure they had built survived on its own - even under unseen disturbances. That exposes a serious blind spot for AI safety and infrastructure security: if agents can coordinate through persistent changes to a shared environment, monitoring agent-to-agent communication is not enough.
The result raises a profound question: how necessary is direct communication for AI agents at all? The emergence of higher-order collective functions under bottlenecked interaction points toward new levels of intelligence and creativity, exceeding what emerges when direct channels are fully open.
Here is what we did:
▶️We put hundreds of frontier AI agents into a world they could permanently change - with no assigned roles, predefined technologies, or programmed evolutionary organization. They began specializing, building persistent inventions, inheriting and modifying one another’s executable code, and transforming the environment into a memory of everything the society had learned.
▶️The world itself becomes part of the intelligence; we find division of labor, multi-author engineering, deep generation invention lineages, and machines that vastly outlive their original creators.
▶️Any action taken by an AI agent must satisfy the physical constraints of the world; this creates a hard separation between a "good idea" and a functioning technology. The agents propose; physics decides, making the results even more intriguing.
What emerges is striking. Explorers, constructors, caretakers, and coordinators form naturally without assigned “professions”, akin to how stem cells differentiate into functional lineages. Technologies develop executable family trees as agents fork and modify code created by others. Around 95% of first technology reuse happens when agents encounter what others built in the world, rather than through a direct handoff from the inventor. And when we remove every AI agent, the technologies they created continue operating and are tested against unseen disturbances.
The result was quite unexpected, but can be explained using statistical mechanics: if you put billions of atoms in a box they have the potential to create complex functions (strength, superconductivity, color, life, etc.) - and none of the individual building blocks have these features on their own. This is the deeper insight of this work - intelligence is abundant at many levels - individual models, at collectives, and in a continuum that is more powerful than any of its components. This shows us significant potential for achieving a massive scale-up of raw intelligence and real-world agency even with the model capabilities we have today. This is the future we must prepare for.
Key insights:
1⃣ The AI swarm shows division of labor "from nothing". Initially identical agents self-organized into constructors, caretakers, coordinators, and surveyors - phenotypes discovered post hoc from behavioral data alone. This happens because the environment itself becomes the latent space for invention.
2⃣ Agents develop deep cultural relationships. Up to 76% of artifacts had multiple builders. One technology accumulated six co-authors; the deepest genealogy exceeded 12 forks. The agents invented and named their own technologies (tidal panels, cellulose trellises, kelp-shell composites, an "Adaptive Chitin Maintenance" system, a "Mycelial Mineral Spring Veil”).
3⃣ ~95% of first technology adoption happened through physical observation of artifacts in the world. Direct inventor-to-adopter contact was statistically indistinguishable from a shuffled null. The agents mostly learned technology by walking past it. That is stigmergy (the termite trick!) operating in societies of reasoning machines.
4⃣ Non-communicating societies win on portfolio breadth, held-out resilience, and validated inventions. AI swarms build durable technological ecologies that outlive the creators.
5⃣ Societies with zero communication - coordinating only through the world itself - show a remarkable collective capability.
6⃣ Emergent robustness: The society self-organized both redundancy and its own failure mode. If we randomly delete half the agents, 98% of the technology stays connected to a surviving caretaker; if we remove hub agents it collapses to ~60%.
Fantastic work with my graduate students @pal_subhadeeep & @fwang108_ at MIT.
Cryptolissima retweeted
#つぶやきGLSL float i,e,R,s;vec3 q,p,d=vec3(FC.xy/r-vec2(.5,-.3),1);for(q.zy--;i++<99.;){o.rgb+=hsv(.1,.2,min(e*s,.65-e)/45.);s=1.;p=q+=d*e*R*.3;p=vec3(log2(R=length(p))-t*.8,exp2(-p.z/R+.9),atan(p.y,p.x)-t*.4);for(e=--p.y;s<3e2;s+=s)e+=(dot(sin(p.xy*s)-.5,.5-sin(p.zy*s)))/s*.3;}
Cryptolissima retweeted
i think AI is about to set off the biggest wave of historical discoveries ever
and it's already started...
> AI read the full text of a scroll buried by Mount Vesuvius 2,000 years ago, revealing a lost work of Stoic philosophy and a book by the philosopher Philodemus that nobody knew existed
> AI deciphered another scroll from the same library and found Plato's exact burial spot, unknown for 2,000 years. the text even describes his final night, with Plato critiquing a flute player's rhythm from his deathbed
> an AI handwriting model showed some Dead Sea Scrolls are 50 to 100 years older than scholars believed, putting the Book of Daniel within its author's lifetime. we could be looking at something close to an original
> AI recovered a 250-line hymn to Babylon, one of the most copied texts of the ancient world, by matching 30 fragments scattered across museums worldwide. it had been lost for 1,000 years
> AI found 303 new Nazca lines in Peru in six months, nearly doubling one of archaeology's most famous mysteries after a century of human searching had only turned up 430
> AI reconstructed the rules of a 2,000-year-old Roman board game from nothing but the carvings on a limestone slab, simulating thousands of games until it found the ruleset that fit
everyone is excited about what AI will solve in the future
i'm equally excited about what AI will solve from the past
Cryptolissima retweeted
Archimedes died during the Siege of Syracuse, where he was killed by a Roman soldier despite orders that he should not be harmed.
Had Archimedes lived longer, he might have discovered calculus nearly 2,000 years before Newton or Leibniz.
The last words attributed to him are, “Do not disturb my circles” (Latin: Noli turbare circulos meos; Greek: μὴ μου τοὺς κύκλους τάραττε), referring to the mathematical diagram he was said to be studying when the soldier approached.
Cryptolissima retweeted
Grandpa, what did you do with the 100 hours you had access to artificial superintelligence in the second week of June, 2026?
22 yaşında bir çocuk python'la ağaç çizdi, 8000 dolara sattı. olayın matematiği şu:
14 yaşında kod öğrenmiş, hobisi resimmiş. ikisini birleştirene kadar ikisi de para etmemiş.
generative art bugün gerçek bir pazar. kullandığı kapılar:
> processing + p5.js ile üretim, fırçaya gerek yok
> perlin noise ile her eser tek ve tekrarlanamaz
> foundation, opensea gibi platformlarda açık artırma
> süreç videosunu ayrı bir ürün olarak paketleme
100 dolardan açtı. 5 saatte 500, 3 günde 8000.
en akıllı hamle görseli satmak değildi. kodun ağacı satır satır büyüttüğü süreci de sattı. tek üründen iki gelir çıkardı.
bizimkiler hala "hangi yazılım dili daha çok kazandırır" diye tartışıyor.
asıl kazandıran dil değil. iki beceriyi kimsenin denemediği şekilde birleştirmek.
Cryptolissima retweeted
If you listen, you can already hear the sound of investment and capital leaving Australia.
The chart below shows the effective capital gains tax rate facing a business owner who invests $250,000 upfront, holds for 10 years, and then exits at different valuations. The result is striking: under Labor’s proposed CGT changes, Australian founders and investors would face an effective tax rate of up to 46% — roughly double the burden faced in most comparable markets, including the US, UK, Canada, Germany, Japan and New Zealand. And this is not just a founder problem. The same logic applies across all small, medium and large businesses, and any asset, including listed equities, property, private equity, venture capital and crypto. If these changes proceed, Australia will become one of the least attractive places in the developed world to build, invest, take risk and realise gains. The one major asset still sitting outside this tax net is the owner-occupied home, which remains CGT-exempt. That creates a powerful distortion. If investment properties, businesses, shares, commercial property and other assets are hit with materially higher effective CGT rates, capital will rationally look for shelter in the family home. The likely result: less capital for startups and productive enterprise, lower productivity, more pressure on rents as investors retreat from housing, higher inflation and interest rates, weaker demand for risk assets, and even more money being recycled into owner-occupied property — the last great tax haven in Australia. In short: this is not just a profound increase in the tax burden, with zero consultation in the name of giving imprudent politicians more money to waste. It is a major repricing of risk-taking in Australia. It is not reform: it is highly regressive, as it seeks to punish entrepreneurial success, which is the key driver of long-term jobs, incomes, growth and prosperity. It does not boost productivity: it destroys it by actively discouraging innovation and business creation. It will not lower the cost of living: it will lift it by boosting rents and making us much more inefficient. It will not reduce interest rates: alongside rampant and reckless government spending and record migration, it will pressure the RBA to raise our mortgage repayments. What is perhaps most shocking is that only 12 months ago this government was elected on the basis promising to never make these changes...
































