AI Explained retweeted

Anthropic@AnthropicAIJul 20
United States
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We're offering grants of up to $50,000 in Claude usage credits to researchers accelerating cures for rare diseases.
This is our first focused call within AI for Science, our program supporting scientists using Claude to speed up discovery. anthropic.com/news/rare-dise…
🚨 AGENT SWARMS - BUILD COMPLEX APPS AND AUTOMATIONS WITH ONE PROMPT
Combine Gemini 3.1 Pro, Opus 4.7 and GPT 5.5 to create complex multi-agent systems
Each agent excels at a particular task - coding, testing, mobile app, research and monitoring
Master agent orchestrates worker agents - use english to instruct the master
AI Explained retweeted
Instead of watching an hour of Netflix, watch this 2 hour hour Stanford lecture will teach you more about how LLMs like ChatGPT and Claude are built than most people working at top AI companies learn in their entire careers.
AI Explained retweeted
Signed by Jensen at Dell Technologies World. Built for the future of agentic AI. 🚀
Sam Altman just revealed he put his ENTIRE liquid net worth into one company to reverse aging.
The company is called Retro Biosciences.
He put $180 million of his own money as the seed round. Then he came back for a $1 billion Series A. The company is now valued at $5 billion.
Here's what they're building:
Retro is working on something called partial cellular reprogramming. The basic idea is that your cells can be rewound to a younger state without turning them all the way back into stem cells.
You stay you, but your biology gets younger.
Most diseases are diseases of age. 20yo rarely get sick the way 80yo do.
So instead of fighting cancer, Alzheimer's, and heart disease one by one, what if you just made the cells younger so those diseases never develop in the first place?
That's the bet. One solution that cuts through EVERYTHING.
And here's where AI enters the picture:
OpenAI built a specialized model called GPT-4b micro specifically for Retro's research. They used it to redesign the proteins responsible for turning adult cells back into stem cells, a technique that won the Nobel Prize when it was first discovered.
The original method was painfully slow. Worked on fewer than 1 in 1,000 cells.
OpenAI's AI-designed proteins made the process 50 TIMES more efficient.
Cells that used to take 3 weeks to reprogram were doing it in 7 days. And the AI came up with protein modifications so radical that human scientists would never have tried them, some differing by over 100 amino acids from the originals.
Altman said AI compressed years of biological research into a fraction of the time. Retro's CEO said the model delivered results faster and better than any human-led effort they'd attempted.
They've already started human trials for a drug targeting Alzheimer's.
But here's the part that should make everyone stop and think...
Altman also revealed that GPT-5 was specifically upgraded to handle healthcare queries.
People are already uploading their medical records, asking about symptoms, and getting real answers. He told a story about taking a picture of a skin issue and ChatGPT correctly diagnosing it and offering to prescribe medication on the spot.
Doctors at hospitals across the country are secretly using it at home because their workplaces don't have HIPAA-compliant versions yet.
Every clinic he visits tells him the same thing: Every doctor here uses ChatGPT, they just can't admit it publicly.
His prediction is that within 10 years, every person on Earth will have access to BETTER healthcare than the best healthcare anyone can get today.
Think about this for a second...
The CEO of the world's most powerful AI company put every dollar he had into an anti-aging startup.
Then he built a custom AI model exclusively for that startup's research. That model produced results 50x better than anything humans achieved.
And simultaneously his main product is being quietly adopted by the entire medical profession without official approval.
OpenAI is becoming the backbone of a healthcare revolution that most people haven't even noticed is underway.
The billionaire longevity race used to be an irrelevant sidequest. Bezos put some into Altos Labs. Zuckerberg and Thiel backed similar ventures.
Nothing serious.
But Altman's approach is different because he has something none of them had: An AI capable of doing the actual science faster than human researchers ever could.
If Retro's cellular reprogramming works at scale, the first generation of people who get to live significantly healthier and longer lives might already be alive today.
And Altman is barely talking about it, I wonder why.
Readers added context they thought people might want to know
Sam Altman stated he invested his liquid net worth in two companies—$180 million in Retro Biosciences and additional funds in Helion Energy—not his entire liquid net worth in one company. Retro Biosciences is seeking but has not yet achieved a $5 billion valuation. technologyreview.com/2023/03/08/106… statnews.com/2025/12/03/agi…
AI Explained retweeted
the engineer who built Claude Code just dropped a 28-minute video on how to write prompts that actually work
I've seen $300 courses that don't cover what he shows in the first 10 minutes
CLAUDE.md files, memory shortcuts, parallel sessions, prompting patterns
all in one video and completely free
works whether you're a developer, a beginner, or someone who's been using Claude for months
based on this, I put together 18 things you can copy and use in Claude today
full guide in the article below
AI Explained retweeted
“Discovery may become the job of AI. Understanding remains ours.”
Sam Altman says biology may be too complex for humans to discover alone.
A smarter system could solve what we can’t, then explain it in a way we can understand.
AI Explained retweeted
Lisa Su (CEO of AMD) unveils the world's smallest AI development PC, capable of running 200B parameter models locally.
Last week, we made Gemini Embedding 2, our first natively multimodal embedding model, available to the general public. Since then, developers have used it to build video analysis tools, visual shopping assistants, and more.
But you might be wondering... what is an embedding model? 🤔 Let’s break it down!
1. What is it?
Think of an embedding model as a "universal translator." It takes text, images, video, and audio data and turns them into a long string of numbers, like a unique digital fingerprint.
2. How does it work?
Historically, search has been text only. Now, instead of just matching data by keyword, Gemini Embedding 2 maps multiple modalities in the same space based on meaning. It "feels" the connection between a video of a soccer goal and the words "game-winning shot" without needing tags.
For example, "ocean" and "waves" are placed close together, but "ocean" and "toaster" are miles apart.
3. How can you use it?
Developers have been using it to incorporate smarter search functionality into their builds. This means creating tools where you can snap a photo of a product and type "find this in yellow," or search through thousands of hours of video by describing what happens in a scene.
4. Ready to try it out for yourself?
You can start using it today via the Gemini API or the Gemini Enterprise Agent Platform.































