I'm at Neurips! 🌴 I've been thinking more about how large models can synergize with approaches that provide guarantees like classical planning and combinatorial optimization. Please reach out if you want to chat or catch up!

i gave a keynote talk at NeurIPS'25 just last week. here's the slide deck (link below) i've used to share my thoughts on who we are and what we do.

Sixth, and last, #runconference at #NeurIPS2025 had the best turnout yet! Thanks to everyone who came out, until the next conference! The second picture is of those who stayed until the end 😅🏅 🤖🏃🏾👋🏾

You can make your own sticker at the @AmazonScience booth!

Wondering how to attend an ML conference the right way? ahead of NeurIPS 2025 (30k attendees!) here are ten pro tips: 1. Your main goals: (i) meet people (ii) regain excitement about work (iii) learn things – in that order. 2. Make a list of papers you like

The Rocky Mountains are so cool

I’ll be at @NeurIPSConf this week! I am also actively recruiting grad students for my group at U Alberta and Amii 🇨🇦. If you’re interested in ML/generative models for bio🧫 and biochemistry🧬, feel free to reach out! Looking forward to catching up with everyone.

I love this description of Toronto: "It’s the unlikely combination of friendliness, energy, culture, ease of movement, safety, and sheer human variety."

Exactly. I learned a ton of math during my PhD, and it was fun and easy *because I had a goal* to use it in my research. Coding it up is also a great way to detect gaps in your understanding. Totally different from learning in class. Another common fallacy is that you need to

What is the MNIST / CIFAR-10 / ImageNet equivalent for post-training/RL algorithms?

Life update: I've recently moved to Boston and started a job @AmazonScience ! I'm excited to explore - please share local recs and let me know if you want to grab coffee! (picture: White Mountains, NH)

The news is out! We're starting Blank Bio to build a computational toolkit assisted with RNA foundation models. If you want to see my flip between being eerily still and overly animated check out the video below! The core hypothesis is that RNA is the most customizable molecule

Giving your models more time to think before prediction, like via smart decoding, chain-of-thoughts reasoning, latent thoughts, etc, turns out to be quite effective for unblocking the next level of intelligence. New post is here :) “Why we think”:

We wrote up what we've learned about using Claude Code internally at Anthropic. Here are the most effective patterns we've found (many apply to coding with LLMs generally):

Some people today are discouraging others from learning programming on the grounds AI will automate it. This advice will be seen as some of the worst career advice ever given. I disagree with the Turing Award and Nobel prize winner who wrote, “It is far more likely that the

The past 18 months have seen the most rapid change in human written communication ever By. September 2024, 18% of financial consumer complaints, 24% of press releases, 15% of job postings & 14% of UN press releases showed signs of LLM writing. And the method undercounts true use

Hot off the Servers 🔥💻 --- we’ve found a new approach for scaling test-time compute! Multi-Agent Verification (MAV) scales the number of verifier models at test-time, which boosts LLM performance without any additional training. Now we can scale along two dimensions: by

One of the things we've been most impressed by internally at Anthropic is Claude 3.7 Sonnet's one-shot code generation ability. Here are a few of my favorite examples I've seen on here over the past day:

87 and 97 both getting golden goals is poetic.

It’s just incredible how much of a home run 4 Nations has been for the NHL and hockey in general. Friends who never watched a hockey game in their lives reaching out asking what the plan is for tonight’s game, what food we’re ordering, etc. Definition of growing the game.