Not all of us have a chance to say my code made a spacecraft land on the moon. That's Margaret Hamilton, who was the Director of the Software Engineering Division at the MIT Instrumentation Laboratory, which developed the onboard flight software for NASA's Apollo space program.
I'm so excited to share that we are acquiring the financial services app, @step
Nobody taught me about investing, building credit, or managing money when I was growing up. That's exactly why we’re joining forces with Step! I want to give millions of young people the financial foundation I never had. Lots to share soon :D
🔝 Great goalkeeper moments 🔝
😱 When @ClubBrugge number one Senne Lammens sent his team to the play-offs with a last-gasp equaliser! 👏
#UYL | #FlashbackFriday
Stripe offered to acquire us for $1.2 billion when we had $2M in revenue.
Today, we've raised $330M at an $8B valuation and reached $1B ARR.
We could've died three times during this journey.
This is the story I've never told anyone before:
We disrupted a highly sophisticated AI-led espionage campaign.
The attack targeted large tech companies, financial institutions, chemical manufacturing companies, and government agencies. We assess with high confidence that the threat actor was a Chinese state-sponsored group.
Google just dropped "Attention is all you need (V2)"
This paper could solve AI's biggest problem:
Catastrophic forgetting.
When AI models learn something new, they tend to forget what they previously learned. Humans don't work this way, and now Google Research has a solution.
Nested Learning.
This is a new machine learning paradigm that treats models as a system of interconnected optimization problems running at different speeds - just like how our brain processes information.
Here's why this matters:
LLMs don't learn from experiences; they remain limited to what they learned during training. They can't learn or improve over time without losing previous knowledge.
Nested Learning changes this by viewing the model's architecture and training algorithm as the same thing - just different "levels" of optimization.
The paper introduces Hope, a proof-of-concept architecture that demonstrates this approach:
↳ Hope outperforms modern recurrent models on language modeling tasks
↳ It handles long-context memory better than state-of-the-art models
↳ It achieves this through "continuum memory systems" that update at different frequencies
This is similar to how our brain manages short-term and long-term memory simultaneously.
We might finally be closing the gap between AI and the human brain's ability to continually learn.
I've shared link to the paper in the next tweet!
NEWS: Jeff Bezos has created a new AI startup where he will be Co-CEO.
It's called Project Prometheus and has received $6.2B in funding, some from Bezos himself. The startup is going to build AI products for engineering and manufacturing in fields like computers, aerospace and automobiles.
The company already has almost 100 staff, including researchers from Meta, OpenAI and Google DeepMind.
Claude 4.5 Sonnet just refactored my entire codebase in one call.
25 tool invocations. 3,000+ new lines. 12 brand new files.
It modularized everything. Broke up monoliths. Cleaned up spaghetti.
None of it worked.
But boy was it beautiful.