American AI startups need open source models to survive and profit. They also don't care that they are made by Chinese labs, because if you control where you deploy the model and set up guardrails (aka you know what you are doing), the risk is minimal
This report by Fireworks AI and Harvey building legal AI agents using GLM, Kimi, and Opus is just one of many many examples.
No startup can afford to pay the Opus/GPT tax. Not sustainble.
https://t.co/YIc0xYsSFo
We're adopting the Linux Foundation’s OpenMDW framework across our open model families.
This helps make open model licensing simpler and more consistent at scale.
A single legal framework across models, code, documentation, and data helps reduce friction for developers and enterprises building with open source.
COLM 2026 will host 16(!) workshops:
https://t.co/Lf90oZTfiT
CFPs are all online, and deadlines are coming up, so check the CFP of your workshops of interest
I was in China a couple of weeks ago with @natolambert , @xeophon, the @readsail team including @caithrin, @azeem, @jasminewsun, @kevinsxu, and other wonderful humans.
Over dinner in Shanghai, a friend asked:
“Are these robot dogs and humanoids actually running large language models? How does a language model… move a leg?”
That question became the starting point for my new piece as I processed how Chinese and US robotics industries are progressing and where they are excelling.
The cure for our collective anxieties about data centers is a Stardew Valley-style game where one gets proposed in town.
People freak out, but in the end the Alpine Lake does not dry up, Pierre gets into Claude Code, and Pam gets a better job. Token Valley would fix us.
Such a great episode on China’s AI labs with @natolambert.
Highly recommend @Gracemzshao’s Differentiated Understanding podcast for anyone interested in AI in China! https://t.co/5eQXPx5Rbg
Every Chinese lab is obsessed with Claude. Zero Chinese labs have an Amanda Askell. Why not? My search for Amanda Askell with Chinese characteristics. Link below.
For a long time, academic researchers being at the cutting edge of new technologies has been a great social equilibrium. Neutral, unbiased technologists have been the people to spread new ideas to the world.
As AI research takes off in velocity, it is also going behind closed doors. The tech industry has sewed distrust, and now they are the ones trying to tell the world about incredible changes coming. It's a big loss to a form of social contract in America.
There's been a history of scientists helping society understand new technologies. There is a public service in the culture of science that I want to see continue.
It's being exacerbated by feelings of FOMO, especially finically driven, where I'm seeing many people who previously wanted to be professors -- and likely still do deep down -- feel a need to conform and chase money, in a pocket of industry. I get it, I grapple with this.
For those with a safety net, there will be great returns to some who choose to zag, and try to build something good, for people who need something different. For me, this is building interesting, fully-open models, to show what you can do with a variety of open weight sizes.
Yes, AI's immediate future is dictated by the frontier, but it's long-term trajectory still deeply includes academic institutions and open science. Knowledge will always diffuse, but to whom?
As of today, I think China is positioned to be the global home of AI research in a few years. The home of research is where ideas are accessible, spread rapdily, and are nurtured. The U.S. seems to be unwinding many institutions and relationships.
The largest returns go to people who build something differentiated, at least in reputation, and a lot of people are not being shown that this path exists.
ai ceos on twitter two minutes before college speech: YOU ARE THE MUSELIN WEAVERS AND MY AI THE SPINNING JENNY YOU WILL ALL BE AT THE SOUP KITCHEN, MEATBAGS!
ai ceos during speech: why are they booing my ai