Michael Phillips

#SocialMedia Strategist & Consultant | Community Mgmt | Web/Graphic Designer | R&D | #Science & #Technology Enthusiast | Online Growth Initiatives

[Michael Phillips @MyGrayMatter]

Ryan Deboodt's Tour into Lgst Cave System & the #Drone Footage that Mesmerized the Planet https://t.co/1DGa2LCrvX

[Markus J. Buehler @ProfBuehlerMIT]

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.

[Brian Roemmele @BrianRoemmele]

Harvard and MIT Researchers Simulate the Entire Planet with 8.3 Billion AI Personas

It is big.

In a development that feels straight out of science fiction, a large collaborative team led by researchers from Harvard University and the Massachusetts Institute of Technology has unveiled MatrAIx: a population-scale AI simulation infrastructure designed to model the behavior of virtually every person on Earth.

MatrAIx centers on Persona 8B, a dataset containing 8.3 billion unique digital profiles. Each persona is defined across 1,290 categorical dimensions that capture everything from demographic background and psychological traits to spending habits, technical literacy, behavioral quirks, and lifestyle preferences.

I am using Persona 8B quite a bit and it is interesting.

The system is not merely a static database. Researchers bring these personas to life as agents powered by frontier large language models, including. These agents can then be dropped into four distinct digital environments: surveys, AI chat interfaces, live web browsing, and native desktop and mobile applications.

How MatrAIx Works

Persona 8B was constructed using a sophisticated dependency graph that preserves realistic correlations between attributes. Some records are synthetically generated while others are carefully extracted and grounded in real human data from biographies, reviews, surveys, and consented self-reports.

For practical research use, the team has released a high-quality coreset of approximately one million personas.

Once activated, the agents interact with real digital products and systems. Researchers have already run more than 18,000 evaluation trials across 1,010 tasks spanning commerce, software, finance, healthcare, and more than 20 other domains. The system records granular behavioral signals — how long an agent hesitates after a price increase, when it abandons a broken checkout flow, how much latency it will tolerate before closing an app, and whether it continues after an AI assistant fails.

Strong Validation Results

In a controlled study of 400 trials measuring adherence to ten behavioral attributes across all four environments, the agents successfully expressed or correctly suppressed their assigned traits 91.5 percent of the time. Human judges also rated the quality of the human-grounded personas highly (average 4.135 out of 5).

These results suggest that MatrAIx can generate coherent, demographically and psychologically consistent simulated users at a scale previously impossible.

Implications for Research and Business

Traditional market research and user testing are slow, expensive, and limited in sample diversity. MatrAIx offers a complementary approach: the ability to simulate how billions of different types of people might react to a new product feature, pricing change, interface redesign, or AI system — overnight, on a single server.

Product teams could stress-test ideas before expensive real-world launches. Researchers studying human-AI interaction could explore rare behavioral edge cases. Policymakers and social scientists might model the downstream effects of new technologies across highly diverse populations.

The project is open source. Code is available on GitHub, a project website has been launched at https://t.co/l3hUuIuiYt, and the one-million-persona coreset is being released for broader research use.

MatrAIx is not intended as a replacement for real human feedback. The researchers emphasize that it is a powerful tool for exploration, hypothesis generation, and large-scale stress testing.

As the underlying language models improve and the persona models grow more sophisticated, the fidelity of these digital populations is expected to increase further.

For now, the system represents one of the most ambitious attempts yet to create a usable, population-scale digital mirror of humanity a simulation infrastructure that lets us ask “what if” at planetary scale before deploying them in the real world.

[Michael Phillips @MyGrayMatter]

@LuxAlptraum @roseveleth

[World of Science & Technology @worldofscitech]

🤖This is when #Robots will Overtake Humans 🤖

#ArtificialIntelligence #innovation #AI #ml #computing #language #economics #bigdata

[World of Science & Technology @worldofscitech]

.@sanitationconvo has developed online training & certification to disrupt unsafe sanitation practice in the makeup industry! Visit https://t.co/OLCKDR9C4g to learn more

#makeup #beauty #skincare #sanitation #onlinetraining #certification #fashion #beautyblogger #COVID19

[World of Science & Technology @worldofscitech]

🐘Their last argument ended with Edison walking Topsy, the Elephant in front of a crowd of 1,500. He then fed her some carrots laced w/ cyanide. He then electrocuted the poor animal w/ 6,600 volts for 74 seconds..until she was smoking -- To prove a point! Real class act, Thomas!

[World of Science & Technology @worldofscitech]

Explore The Truth About #Disinfectants w/ Dawn Testagrossa of @sanitationconvo & Robert Urfer, of @LucasProductsCo via #InstagramLive

🎬Watch the Full Discussion on Instagram @ https://t.co/mOIT6Vzm7z

#Beauty #InstagramLive #Sanitizer #COVID19 #Coronavirus #Salon #ml

[World of Science & Technology @worldofscitech]

World’s Largest #SuperComputer can Perform 200 #Quadrillion Actions per Second 🤯

#AI #DeepLearning #NeuralNetwork #ML #Data #BigData #Computing #MachineLearning #data #technology #QuantumComputing #TechNews #ArtificialIntelligence #computing

[World of Science & Technology @worldofscitech]

Why Researchers are Making Clear Human Organs V/@Seeker @MargaretSiegien

#3Dprinting #HealthTech #HealthIT #3dprinted #Health #3dprint #TechNews #tech

[Michael Phillips @MyGrayMatter]

How REV Ocean Is Working to Tackle the #Ocean's Toughest Problems With #Data https://t.co/TWEdfNIEu1 via @SeaAhead #environmental #savetheoceans

[Michael Phillips @MyGrayMatter]

Bevi’s Sean Grundy talks about the environmental origins of his company and ... https://t.co/exGtA0Ot0l

[SeaAhead Bluetech Innovation @SeaAhead]

New on SeaAhead: @Aquaai's Robotic Fish Are Harnessing Data to Save Our Seas https://t.co/CckhjpSVDN #bluetech

[Mike Quindazzi @MikeQuindazzi]

1000 times faster with just 1% of the power! >> @wef via @mikequindazzi >> #supercomputers #iot #CloudComputing #emergingtech #tech #megatrends

[World of Science & Technology @worldofscitech]

Forget plastic water bottles, now there's a #biodegradable #water orb you can consume https://t.co/E1KOgdoYO6

[David @davehirschman]

As lab-grown meat advances, U.S. lawmakers call for regulation https://t.co/Hgk2FYJTRA

[Michael Phillips @MyGrayMatter]

No department store has embraced #technology more aggressively than #Nordstrom. Will that strategy keep shoppers coming back? https://t.co/JTO7n6hYZm via @FortuneMagazine

[symmetry magazine @symmetrymag]

"We ended up with a world filled with particles. And not just any particles—particles whose masses and charges were just precise enough to allow human life."
https://t.co/jpGXQYD18r

[Michael Phillips @MyGrayMatter]

"I believe there is no deep difference between what can be achieved by a biological brain and what can be achieved by a computer. It, therefore, follows that computers can, in theory, emulate human intelligence — and exceed it." #StephenHawking #AI

[Michael Phillips @MyGrayMatter]

@evankirstel Shooo! Get otta there! #ALEXA .. NO! BAD Alexa
@amazon may have launched a delivery service to rival @FedEx & @UPS! The creature may be an experimental #AI #Drone with #4K Live Feed Peepers & an IP address.. Thanks Bezos! Malnutrished Drone Owls Delivering Mail.. Perfect!

[Dennis Olympios @DennisOlympios]

In the era of “content shock” we are living in, the expression “Build it and they will come” doesn’t work anymore.
We need to focus our efforts in getting our stellar #Content in front of the right audiences.
https://t.co/hKLIcLJ18J #DennisKoutoudis #LinkedSuperPowers