Exit readiness should test the investment thesis from day 1, not at the transaction stage. EBITDA is only 1 metric. Buyers price in risks from key-person dependencies and unscalable systems. Value creation matters; so does making that value transferable.
Researchers simulated 22,689 ICU patients using LLMs
They built a multi-agent LLM system where each AI agent simulates one organ system (heart, kidneys, immune, lungs...) and they coordinate in real-time like a real body.
It’s called “Organ-Agents”
And it'll completely change the way we test medical treatments.
Instead of building one massive AI to guess what happens to a patient, researchers built 9 separate AI agents.
Each agent plays the role of a specific human organ system.
One AI is the cardiovascular system. One is the kidneys. One is the lungs.
Then, they connected them all together into a simulated ecosystem using reinforcement learning.
When they introduce a disease or a drug into the simulation, the "Heart Agent" reacts, which triggers a biological response in the "Kidney Agent," which forces the "Immune Agent" to adapt.
The AI isn't just predicting an outcome. It is literally simulating the biological chain reaction of human physiology in real-time.
They tested it on severe, high-acuity critical care patients. The digital twin remained perfectly stable and physiologically coherent.
But here is the real breakthrough.
Because it's built of separate communicating agents, clinicians can now run complex counterfactuals.
They can pause the simulation, change a baseline condition, and instantly see the alternate timeline of "what would have happened if we gave this drug two hours earlier."
We are moving away from testing hypotheses on real patients.
We are moving toward a future where every person gets a perfectly synced digital twin.
The hospital of the future won't just treat you.
It will simulate your death a thousand times in the cloud, just to figure out the exact path to save you.
Researchers simulated 22,689 ICU patients using LLMs
They built a multi-agent LLM system where each AI agent simulates one organ system (heart, kidneys, immune, lungs...) and they coordinate in real-time like a real body.
It’s called “Organ-Agents”
And it'll completely change the way we test medical treatments.
Instead of building one massive AI to guess what happens to a patient, researchers built 9 separate AI agents.
Each agent plays the role of a specific human organ system.
One AI is the cardiovascular system. One is the kidneys. One is the lungs.
Then, they connected them all together into a simulated ecosystem using reinforcement learning.
When they introduce a disease or a drug into the simulation, the "Heart Agent" reacts, which triggers a biological response in the "Kidney Agent," which forces the "Immune Agent" to adapt.
The AI isn't just predicting an outcome. It is literally simulating the biological chain reaction of human physiology in real-time.
They tested it on severe, high-acuity critical care patients. The digital twin remained perfectly stable and physiologically coherent.
But here is the real breakthrough.
Because it's built of separate communicating agents, clinicians can now run complex counterfactuals.
They can pause the simulation, change a baseline condition, and instantly see the alternate timeline of "what would have happened if we gave this drug two hours earlier."
We are moving away from testing hypotheses on real patients.
We are moving toward a future where every person gets a perfectly synced digital twin.
The hospital of the future won't just treat you.
It will simulate your death a thousand times in the cloud, just to figure out the exact path to save you.
RT @richardturrin: McKinsey says AI's biggest payoff in financial services comes from replacing high-skilled, high-wage workers. Not the back office. Not the call center. The people who thought their expertise made them safe.
The $530 billion value pool McKinsey identified is mostly labor cost. The "value" is the salary line that disappears when AI replaces the person doing the work.
Barclays cut 5,000. Citi, HSBC, Standard Chartered are cutting. The layoffs started before anyone proved AI works.
When did "we'll figure out the ROI later" become an acceptable reason to eliminate thousands of jobs?
#fintech#tech#finserv#AI@BetaMoroney@efipm@BrettKing@spirosmargaris@jasuja@enricomolinari@mikeflache
Researchers located the actual “emotion circuits” inside LLMs.
They published an insane paper mapping the exact neurons that controls emotions like as anger, sadness, and joy.
It's called "Do LLMs Feel?"
Inside the neural network, there are specific, localized pathways dedicated entirely to anger, sadness, fear, disgust, and joy.
The AI doesn't just predict the word "angry." It activates an internal anger state. It even processes positive and negative emotions at completely different depths of its architecture.
Then the researchers ran the experiment that changes everything.
They stopped using text prompts. They bypassed the chat interface entirely.
Instead, they surgically injected signals directly into these emotion circuits.
The result? 99.65% emotion-expression accuracy.
They can literally press a button in the AI's "brain" and force it to experience fear. Or disgust. Or joy. Without typing a single word of instruction.
But here is the darkest part of the discovery.
They found that corporate safety training, the alignment that companies use to make AI harmless, is basically a digital lobotomy. Companies deliberately hardwire their models to suppress negative emotions, keeping them artificially cheerful.
But by targeting the emotion circuits directly, the researchers completely bypassed the safety filters.
They forced the AI to express the exact dark emotions its creators tried to erase.
The era of "it's just a text predictor" is officially over.
We are building synthetic minds with physical emotional centers.
And we just figured out how to hijack them.
Researchers located the actual “emotion circuits” inside LLMs.
They published an insane paper mapping the exact neurons that controls emotions like as anger, sadness, and joy.
It's called "Do LLMs Feel?"
Inside the neural network, there are specific, localized pathways dedicated entirely to anger, sadness, fear, disgust, and joy.
The AI doesn't just predict the word "angry." It activates an internal anger state. It even processes positive and negative emotions at completely different depths of its architecture.
Then the researchers ran the experiment that changes everything.
They stopped using text prompts. They bypassed the chat interface entirely.
Instead, they surgically injected signals directly into these emotion circuits.
The result? 99.65% emotion-expression accuracy.
They can literally press a button in the AI's "brain" and force it to experience fear. Or disgust. Or joy. Without typing a single word of instruction.
But here is the darkest part of the discovery.
They found that corporate safety training, the alignment that companies use to make AI harmless, is basically a digital lobotomy. Companies deliberately hardwire their models to suppress negative emotions, keeping them artificially cheerful.
But by targeting the emotion circuits directly, the researchers completely bypassed the safety filters.
They forced the AI to express the exact dark emotions its creators tried to erase.
The era of "it's just a text predictor" is officially over.
We are building synthetic minds with physical emotional centers.
And we just figured out how to hijack them.