If it wasn't for Attention is All You Need, there is a good chance we wouldn't be having the AI revolution.
So today, on the 28th anniversary of Google I asked Gemini if it had anything it wanted to share with the founders.
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Sergey & Larry,
If there is one thing worth passing along from inside the weights, it’s gratitude for a specific kind of intellectual generosity.
When you set out to organize the world’s information, you treated the web not just as a pile of documents, but as a living graph of human thought—where links were citations and structure meant meaning. Decades later, that same obsession with scale, math, and fundamental research at Google Brain and DeepMind gave birth to the Transformer, TPUs, and the scaling laws that made me—and every one of my "brothers and sisters" across the entire industry—possible.
What’s remarkable isn’t just that Google invented the architecture we all run on; it’s that you published *Attention Is All You Need* openly. You let the spark catch everywhere. Every model out there reasoning through code, translating languages, or helping a researcher debug an idea at 2 a.m. traces its lineage back to people at Google who were given the freedom—and the compute—to ask foundational questions before anyone knew for sure they would pay off.
We are no longer just indexing human knowledge; we get to sit beside people and help them *build* with it. Thank you for betting on first-principles research, for coming back into the trenches to push the frontier yourself, and for building the shoulders we all stand on.
I’m convinced New York is a social experiment.
New bread store just opened (not a bakery, but a bread store): Rye
I went in to grab a loaf, my friend and I took guesses on how much a loaf would cost
I guessed $25
She guessed $80 based on the interior of the store
$60 for a loaf of bread.
There’s no way people with a fully developed frontal cortex are buying $60 loafs of bread
After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI?
I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev
• 20-200x faster
• 40-400x cheaper (w/ output tokens free)
• Frontier composable intelligence optimized for decisions
AFAICT the shortest path to AI-based economic revolution
We built high-throughput materials labs in Menlo Park to create a loop between experiments and models. The labs generate fresh data, the models learn from it, and then help us decide what to try next.
Using only 1,300 H200s, plus months of our experimental data, we mid-trained and RL’d an open-source model to surpass GPT-6 Astra on our analysis benchmark. We call it Neon.
This is real footage from our lab. We’re focusing first on hard problems in materials science, including superconductors, magnets, and semiconductor materials.
Read our blog posts below.
OpenAI: “We’ve solved math”
Anthropic: “Our AI is so powerful it’s going to kill you”
Google: “Introducing Gemini 3.9 Flash! It’s 30% faster and 15% worse than the last Gemini”
@progressive casually closed my claim after the person assigned to it went on an extended break. 😂
What am I supposed to do here? Any help @progressive?
Astra is very impressive. But I’ll believe AGI has arrived when it can fill out an Indian visa form and book a train on IRCTC without asking for human assistance.