Peter joins a long line of excellent people who have gotten to work on Twitter / X product.
But this may be one of the best ever.
He got Snap and Discord scaling and to their first $1B revenue and now can take X to the next level.
Have known him a long time , so happy !!
I have over 200 open SWE jobs in my portfolio, currently hiring in SF. All tier-1, VC-backed startups. All hybrid or onsite here locally.
Really indexing for
- full stack, product leaning SWEs
- MLEs & Research Engineers
- AI engineers (backend leaning)
This sound like you? DM if so...
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! https://t.co/VkfacopR2R
Communicating effectively about science is really important. It's nice to see these amazing journalists recognized for their effectiveness at bringing scientific topics to life for broader audiences!
One of my biggest learnings in 2026:
STOP WORRYING ABOUT WHETHER YOU'RE MAKING THE RIGHT DECISION.
A lot of people reach out to me asking what field they should get into, what they should learn, what path they should take, and stuff like that.
And I think people overcomplicate this way too much.
When I first started learning about systems and databases, I used to doubt myself a lot.
People around me were becoming amazing design engineers, some were getting really good at TypeScript, and others were building crazy stuff with Rust.
And I'd wonder, am I even going in the right direction?
But eventually, I realized something.
People act as if the universe will punish them for making the wrong decision. As if there's some reward for choosing the "right" path and some punishment for choosing the "wrong" one.
That's not how it works.
Let's say you pick path X. You start learning, building, creating things, and genuinely enjoying the process.
But then you see someone doing incredibly well on path Y, and suddenly you start questioning everything.
People don't even let their own decisions breathe because they're so obsessed with wondering whether some other decision would've been better.
And that's the problem.
I genuinely believe that when you put a ton of effort into something and are really, really curious about it, opportunities you could never have imagined will start opening up for you.
You could've taken a hundred different paths in life. Each one could've opened up a completely different set of possibilities. Different experiences, different people, different opportunities.
There is no single magical path.
So stop asking everyone what you should do with your life.
Instead, ask yourself what genuinely interests you. What makes you so curious that you could spend hours figuring it out without even realizing how much time has passed?
And once you figure that out, just go for it, man.
Go deep into it. Build things. Ask stupid questions. Experiment. Get things wrong. Figure things out along the way.
You don't need to have everything figured out before you start.
And most importantly, stop looking at what everyone else is doing and wondering whether you should've chosen their path instead.
You have no idea what opportunities your own path might open up if you just give it enough time, effort, and curiosity.
You don't always have to find the right path. Sometimes you just have to pick one and make something incredible out of it.
That's it, that's literally it.
My first open model lecture, covering all the many pieces that build the ecosystem, and the open questions/debates determining where it goes next.
How does distillation fit in?
How do we manage risks?
How do we see access to models changing in the future?
I'm excited to revisit these questions about every 6 months, to give a state of the union on the field.
Chapters
00:00 Introduction
01:36 What is an open model?
08:47 Why should we care about open models?
18:52 How competitive are the best open models today?
25:28 How are open models built? The role of distillation
34:52 Are people actually using open models?
41:47 What comes next with open models?
47:32 Conclusions
What questions did I not answer that you have?
PSI's first quantum information papers are out!
I've been working on these with Adam Levine, Ian MacCormack, Jim Halverson, Ning Bao and the rest of the team: eliciting the results over a wide range of timescales, polishing the papers, and formalizing the proofs. 1/n
Today Physical Superintelligence PBC is announcing solutions to five long-standing problems in quantum information theory.
https://t.co/LjmLz0mCtF
Thread 👇
We are announcing three new discoveries in mathematics, computer science, and physics about harmonic analysis, complexity theory, and quantum field theory.
https://t.co/9BX8HWQDTJ
We’re excited to announce an additional £120m for Sovereign AI to back the future of AI in Britain.
An extra £60m to invest in the UK’s most promising AI companies, expanding into Physical and Industrial AI.
And £60m more for R&D procurement, backing innovation in areas such as AI security and AI for healthcare.
We want to help founders start and scale in Britain, and turn innovation into impact.
2/7 We're launching a £165m National AI Biosecurity Initiative, including £100m for a world-first AI Biosecurity Lab.
This will harness British scientific expertise and latest AI to detect biological threats and protect people from emerging risks.
As with our @AISecurityInst, I want the new AIBL to lead the world in capability.
Jensen Huang says quantum computers could help train AI by simulating biology and chemistry and generating synthetic training data.
“Quantum computer is not the next big thing, but it is a big thing.”
An internal model at OpenAI has produced a claimed refutation of ETH! Russell Impagliazzo, Mohan Paturi, and I have been asked to help organize an open and independent examination of this claim. 1/4