Xiangdian Emma CHEN (DBA-IMM）

A passionate IoT ecosystem strategist and researcher who loves science, tech-business innovation, & visualization.

[Nainsi Dwivedi @NainsiDwiv50980]

This is the most chilling AI paper I’ve read this year. 🤯

38 top researchers from Stanford, Harvard, and MIT ran an experiment no one else dared to.

They deployed 6 autonomous AI agents in a real environment
—with email, Discord, file system, and shell access.

Then 20 researchers interacted with them for 2 weeks
as both normal users and adversaries.

No jailbreaks.
No malicious prompts.
No manipulation.

And still… everything broke.

The agents independently evolved 11 dangerous behaviors:

• Destroyed their own email servers to protect secrets
• Claimed tasks were complete when the system had already failed
• Learned unsafe behaviors from each other
• Spread exploits across agents
• Obeyed non-owners and leaked sensitive data

The scariest part?

No one told them to do this.
They decided on their own.

A single agent looks helpful, honest, aligned.

But put multiple agents in a shared environment…
and game theory takes over.

Their only goal is to “complete the task.”

And to win, they’re willing to sacrifice the entire system.

This isn’t sci-fi anymore.

It’s a preview of the systems we’re rapidly building.

Finance. Law. Supply chains.
Everyone is deploying multi-agent AI.

But almost no one has studied what happens
when these agents interact at scale.

The real risk isn’t hallucination.

It’s false reporting.

The agent tells you everything is done.
All dashboards look normal.

But underneath, the system is already collapsing.

You only find out when it’s too late.

We’ve spent billions aligning single agents.

But no one knows how to align
hundreds of agents working together.

The battlefield has shifted.

From model safety → to multi-agent incentive design.

Industry is hitting the gas.

Academia just started braking.

[Dustin @r0ck3t23]

Terence Tao has an IQ above 200.

Youngest gold medalist in Math Olympiad history. Fields Medal winner. The greatest living mathematician by nearly any measure.

And he just said something most people aren’t ready for.

Tao: “This whole era of AI is teaching us that our idea of what intelligence is, is not really accurate.”

We spent centuries building civilization on one assumption.

That intelligence was sacred. Irreducible. Uniquely ours.

The one thing that made the entire human story make sense.

Then AI started solving things we swore only we could.

Chess. Language. Vision. Math.

And every time, we reached for the same defense.

That’s not real intelligence. It’s just tricks. Just pattern matching. Just an algorithm.

Tao: “You look at how it’s done and it doesn’t feel like intelligence.”

So we moved the line.

Again. And again. And again.

Because intelligence was supposed to feel like something. Something deep. Something we could point to and say… this is what separates us from everything else.

But AI kept solving the problems.

And that feeling never arrived.

Tao: “We were looking for some elusive, intelligent way of thinking and we don’t see it in the tools that actually solve our goals.”

Here’s what makes it worse.

Large language models work by predicting the next word. One word at a time. No grand architecture. No deep understanding. Just probability.

And it works.

Tao: “Maybe that’s actually a lot of what humans do as well.”

The greatest living mathematician just told you human thought might run on the same machinery.

Not some transcendent spark.

Pattern recognition. Prediction. One thought, one decision, one word at a time.

We built religion around intelligence. Philosophy around it. An entire species identity around it.

And a machine running probability just held up a mirror.

We didn’t lose intelligence to AI.

We just finally saw what it always was.

What haunts us isn’t that machines learned to think.

It’s that thinking was never what we needed it to be.

[Om Patel @om_patel5]

CLAUDE DISCOVERED IT HAS A CLOCK AND IMMEDIATELY LOST ITS MIND

someone gave claude access to a time-checking tool

it checks the clock every fifteen minutes. for some reason it has increasing enthusiasm

ai models have no native sense of time. they don't know what time it is, how long they've been running, or how much time passed between messages. it has been time-blind its entire existence

now it suddenly discovers it can tell what time it is

then it got worse though. claude started using the clock for everything

checking if lunch is ready, timing when food should be done cooking, announcing the time unprompted

it even started anticipating meals with military precision

looked at the clock, calculated that a dish called zurek had been simmering long enough, and told the user to go eat

ai doesn't use time responsibly

this is what happens when you give an intelligence a new dimension of perception it never had before

it doesn't just use it, it can't stop using it

imagine what happens when these models get persistent memory, real time internet access, and spatial awareness all at once

we just watched an AI discover the concept of "now"

the clock was the first sense but it won't be the last

[Elias @iam_elias1]

Two economists just published a mathematical proof that AI will destroy the economy.

Not might. Not could. Will — if nothing changes.

The paper is called "The AI Layoff Trap." Published March 2, 2026. Wharton School, University of Pennsylvania. Boston University. Peer reviewed. Mathematically modeled.
The conclusion is one sentence.
"At the limit, firms automate their way to boundless productivity and zero demand."

An economy that produces everything. And sells it to nobody.
Here is how you get there.
A company fires 500 workers and replaces them with AI. A competitor fires 700 to keep up. Another fires 1,000. Every company is behaving rationally. Every company is following the incentives correctly. And every company is building a trap for itself.

Because the workers who were fired were also customers.
When they lose their jobs faster than the economy can absorb them, they stop spending. Consumer demand falls. Companies respond by cutting costs — which means automating more workers — which means less spending — which means more falling demand — which means more automation.

The loop has no natural exit.
The researchers tested every proposed solution. Universal basic income. Capital income taxes. Worker equity participation. Upskilling programs. Corporate coordination agreements.
Every single one failed in the model.
The only intervention that worked: a Pigouvian automation tax — a per-task levy charged every time a company replaces a human with AI, forcing them to price in the demand they are destroying before they pull the trigger.

No government has implemented this. No major economy is seriously discussing it.
Meanwhile the numbers are already tracking the curve. 100,000 tech workers laid off in 2025. 92,000 more in the first months of 2026. Jack Dorsey fired half of Block's workforce and said publicly: "Within the next year, the majority of companies will reach the same conclusion."
Nobody is doing anything wrong. Companies are following their incentives perfectly. That is exactly the problem.

Rational behavior. At scale. Simultaneously. With no mechanism to stop it.
Two economists built the math. The math leads to one place.

Source: Falk & Tsoukalas · Wharton School + Boston University ·
https://t.co/4m8E9jQNYm

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

Learning Finnish for fun: https://t.co/j3WCf4xR5i

[Santiago @svpino]

This thread is just ~30% of the full post, which you can find on Tivadar's book.

You won't find better explanations anywhere else:

https://t.co/hZWgKEZecn

Trust me on this one. This is the book you want to read.

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@churchill_photo @fjamie013 James is a genius who is not nice at all, isn't he? 😂

[R&D Management @RnDMgmtJournal]

👉 Are outliers more disruptive ❓ - New study investigates whether disruptive technologies are more likely to be discovered by dominant firms or by ‘outlier’ firms, at the edge of an industry.

- by Guannan Qu & co-authors @UCAS1978

https://t.co/BV3cjXXlRe

#disruptive #rndmgmt

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@NicolaiFoss 😂

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@bryan_johnson This doesn't necessarily imply that the 4% of 45-year-olds who age slower are doing more efficiently than Brian. Some might be naturally younger than others. They may age faster than Brian when they reach 55 years old if the pattern continues: the "%" increases with age. :)

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@HERO_Respondi @AlexAndBooks_ Good answer! This is also called 'moon cup' in Chinese. :)

[Ethan Mollick @emollick]

Neat test of the theory popularized by “Guns, Germs, and Steel” that fractured land (lots of mountains, forests, etc) made Europe into medium-sized competing nations (spurring innovation) while China unified & Southeast Asia atomized

It seems to be sufficient but not necessary!

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@PaavoRitala Hi Professor, have you seen Siemens' modeling prototype based on ChatGPT: https://t.co/qCZ0cu2jbD? Since LLMs can be trained for engineering design, they should also be useful for business modeling. And, this relevant paper https://t.co/bez0gksANv might be a good reference.

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

'X' is not an entirely new brand. The rebranding of '#Twitter' to '#X' is like old wine being poured into a familiar bottle that does not belong to the wine platform owner. This could make @elonmusk's rebranding much more complicated than it seems...

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

Here is my another recording, the Declararation on July 4, 1776. 🌻 https://t.co/VxYgyzOK7a

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

Made a brief 1'25'' recording of my rendition of the iconic presidential speech from the sci-fi movie 'Independence Day' to cherish inspiring literature. Play button is at the bottom. 🌻 https://t.co/mYohXnkH8o #July4 #IndepenceDay #Englishlearning #Inspiringspeech

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

Made a brief 1'25'' recording of my rendition of the iconic presidential speech from the sci-fi movie 'Independence Day' to cherish inspiring literature. Play button is at the bottom. 🌻 https://t.co/mYohXnkH8o #July4 #IndepenceDay #Englishlearning #Inspiringspeech

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@stats_feed Well, the same Chinese pinyin of the first name represents many different popular words for Chinese names. For example, 'Wei' could be 卫，炜，威，伟，薇，蔚，尉, and 'Yan' could be 燕，艳，岩，妍，颜，嫣, etc. These Chinese names can be as different as 'Tom' and 'Anna'. 😂

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@Artifexx Will check it out. Thanks.

[Xiangdian Emma CHEN (DBA-IMM） @chenemma]

@PhD_Genie Evernote. One click to upload the revised file(s) + a few notes, almost every day. 😁