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Feeling on track ⏫ with Fredo.ai @FredoAiBot
Loads of learnings, team learning to work together. Good stuff.
Things are heating up.
OpenAI paused training because one of their model escaped the sandbox. Again.
Replying to @ripper234 @AISafetyMemes
רבע מהצעירים בישראל כבר מחזיקים קריפטו, ו-38% מבינים שזה הכלי להילחם ביוקר המחיה. אנחנו צריכים את הקול שלך איתנו כדי לתת לך את הקול שלנו בקלפי. יאיר לפיד, אנחנו כבר מזמן שם. מה המצע שלך? 💸🛑 @yairlapid #הציבור_בעד_קריפטו
Ron Gross retweeted
Just had the creepiest scam ever happen 20 minutes ago.
I got a call from my wife telling me she forgot her wallet and needed the credit card to pay for her gas.
Except my wife was at home with me, and drives a Tesla. Same voice, bit... off, weird cadence but 100% sounded just like her. If she wasn't there, and it wasn't about gas I would have fallen for it.
I entertained it for awhile to get more out of it, I was so confused. Must be some sort of voice deepfake. The responses were too fast for ai, I think it was a voice filter. I wish I had thought to record it.
The future is about to get fucked. Warn your loved ones, do verbal passwords with your kids.
Bit taken aback
Ron Gross retweeted
Replying to @hilbertspaess
Trying out GPT 6=Astra=AGI now. Excited!
(Using it on *GPT Work* not just Chat)
I was extraordinarily fortunate to have early access to @OpenAI Astra. After what I've seen, I believe we've now reached one of the defining milestones in the age of AI & have clearly crossed the threshold of AGI! Astra left me so profoundly awestruck that I am struggling to explain what I experienced! Hope to share more soon!
The stars have aligned. A new AI era has begun. ✨💫
Weekly BUILD COWORK on Zoom, every Monday.
Bring your project. Build alongside others. Get help with AI & agents.
Build community projects. Learn by Shipping.
Details 👇
📆 Add to calendar: evt.to/0dtfw6mh3gh2
👥 Join the WhatsApp group: chat.whatsapp.com/DgKpG63438…
Amazing story on the origin of the term "Software Engineering" and the woman behind it.
A 33-year-old woman at MIT wrote the code that ran inside the Apollo 11 lunar lander, and 20 seconds before Neil Armstrong touched the moon, her program made a decision the astronauts didn't know was happening that was the only reason the mission didn't crash.
Her name was Margaret Hamilton.
She led the team writing every line of code that would fly humans to the moon and back. The part almost nobody knows is that she had to fight to be allowed to do the work at all.
Code in 1965 was not treated as real work.
Rockets were serious. Circuits were serious. Writing code was something the men at NASA thought secretaries could do on the side. Hamilton was told this to her face more than once.
So she started calling what her team did "software engineering."
She used the phrase on purpose. In meetings. In memos. To force people to treat it as a discipline instead of a chore. Colleagues laughed at her the first few times she said it out loud.
That phrase is now the name of the biggest engineering profession on earth.
The story of what her code did on July 20, 1969 is the one every kid should be taught.
Neil Armstrong and Buzz Aldrin were 3 minutes from touching down when the computer inside the lunar module started flashing an alarm.
1202.
Then again. Then 1201. Five alarms in four minutes. The computer was telling the astronauts it could not finish everything it had been asked to do.
The computer they were flying with had less memory than a modern microwave.
Someone on the checklist had left a switch in the wrong position, and a radar the astronauts did not even need right then was flooding the computer with data. It was eating around 13% of the machine's brain at the exact moment every second mattered.
In almost any other system, that overload would have frozen the machine.
A frozen machine 30,000 feet above the moon means a crash. It means two dead astronauts and a third one orbiting alone above them, waiting for a signal that would never come.
Hamilton's code did something else.
She had built the software with a rule almost nobody in her field was using at the time. When the machine ran out of room, it would not treat every task as equally important. It would look at the list of jobs it had been asked to do, throw out the ones that could wait, and keep running only the ones keeping the crew alive.
The radar was the low priority job.
The landing was the highest.
So the computer did what she had told it to do. It dumped the radar. It kept flying. The alarm was not a failure. It was the machine reporting that it was handling the overload exactly the way she had designed it to.
Down in Houston, a 24-year-old engineer named Jack Garman recognized the alarm from a test his team had run months earlier. He shouted "Go" to the flight controller. The controller shouted it up to the crew. The landing kept going.
Armstrong touched the surface with 25 seconds of fuel left.
The part that gets lost in every retelling is why Hamilton had built that safety net in the first place.
NASA had not asked for it.
She had added it on her own, years earlier, because her 4-year-old daughter Lauren had once crashed the simulator by pressing a button during a test. The button was one the astronauts had been told they would never press.
Hamilton wanted the code to survive that button press anyway.
Her bosses told her it was a waste of time. Astronauts do not make mistakes.
She insisted. The safety net went in.
Two years later, on the way to the moon, an astronaut left a switch in the wrong position. The exact class of mistake she had been told would never happen.
There is a photograph of her from that period.
She is standing next to a stack of paper as tall as she is. Every page in that stack is the code her team wrote for the mission. She is smiling at the camera like she knows something the rest of the aerospace industry has not figured out yet.
In 2016, Barack Obama put the Presidential Medal of Freedom around her neck and said the astronauts did not have much time, but thankfully, they had Margaret Hamilton.
Every autopilot in every plane you have ever flown on uses a version of what she invented. Every pacemaker. Every self driving car. Every satellite in orbit.
The idea that a machine should know which job matters most and drop the rest when it runs out of room is now the foundation of almost every safety system on the planet.
She wrote it because a 4 year old crashed a simulator and nobody else thought it was worth fixing.
The men in the room laughed at her for calling it engineering.
Then her code was the only thing in the sky that did not fail.
Launching an open source builder community, learning agentic tools together and building real products. Kickoff meeting this Tuesday!
linkedin.com/feed/update/urn…
Singularity much?
After 25 years of brave & brilliant work by hundreds of scientists in my lab to understand then safely reverse aging for the first time, it was moving to witness the first human dose being delivered 🥹 nature.com/articles/d41586-0…
Ron Gross retweeted
Google $GOOG just released an AI tool called TurboVec that shrinks memory requirements by 92%
Now we know why the collapse began yesterday.
Goodbye Micron $MU, Sandisk $SNDK, Samsung and SK Hynix
SAM ALTMAN HAS A NEW PROBLEM. 🤯
Google just shrunk 31GB of AI memory down to 4GB.
The tool is called TurboVec.
It uses up to 16x less memory, searches faster than FAISS, runs fully offline, and works on a regular Mac.
No expensive GPU cluster.
No cloud dependency.
No compromise on speed.
→ 16x lower memory usage
→ Faster vector search
→ Works with LangChain & LlamaIndex
→ 100% open source
The race to build bigger AI models is loud.
The race to make them dramatically cheaper just got a lot more interesting.
Repo: github.com/RyanCodrai/turbov…
Readers added context they thought people might want to know
TurboQuant was announced by Google Research in March 2026; TurboVec is a third-party open-source implementation for compressing vector indexes and KV caches in AI, not a new Google release that broadly reduces memory demand. research.google/blog/turboquan… github.com/RyanCodrai/tur…
I support this message.
Everyone should stop if everyone else does as well.
Read @ESYudkowsky's book.
🔴 Anthropic calls for global freeze in AI development
telegraph.co.uk/business/202…
Ron Gross retweeted
Welp, that happened faster than I predicted. Thought it would be end of 2027, then early 2027, but agentic traffic growing so fast that bots have now passed human traffic online for the first time in the Internet's history. radar.cloudflare.com/traffic…
Ron Gross retweeted
1/10
בעוד מספר חודשים, בעומק של 433 מטרים מתחת לאדמת פינלנד, ייפתח אחד המיזמים ההנדסיים השאפתניים ביותר שביצעה האנושות. המתקן שנקרא "אונקלו" (Onkalo), שפירושו בפינית "מערה", צפוי להפוך למאגר הקבע הראשון בעולם לפסולת גרעינית, ולפתור בעיה שמדאיגה מדינות רבות בעולם, מה עושים עם הדלק
I'm generally a libertarian. But the singularity might demand extreme measures such as this.
Ron Gross retweeted
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 ·




























