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People think that automating jobs will be easy, but they're wrong. You can’t just ask the AI to do things. You need to understand what your employee is doing - instructions, evals, monitoring. You have to make the role legible. Only then can you know AI will do the job well.

Give LLMs access to free entropy, and they will kinda make use of it. 💭

another installment of non-determinism evals with Justin Zhao ! we ran an experiment with claude, making 100 API calls per query to test consistency with numerical data like population figures, GDP, and measurements. results below were interesting

Feel bad for all the people who actually write with em dashes — only to get accused of AI slop.

🚨🚨🚨 Justin Zhao just presented our paper and is around #NAACL2025 if you want to have a chat!!

"RL with only one training example" and "Test-Time RL" are two recent papers that I found fascinating. In the "One Training example" paper the authors find one question and ask the model to solve it again and again. Every time, the model tries 8 times (the Group in GRPO), and

Love the idea of presenting your work as someone else's as a way of getting past sycophancy, which seems to be getting worse these days. I suppose most LLM-as-a-Judge setups embody this inherently, presenting outputs for rating as those written by anonymous third parties.

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"AI as Normal Technology" knightcolumbia.org/content/ai-as-… also advocates the idea that the impact of superintelligence will be extremely gradual because knowing how to improve requires 1) implementing and 2) getting feedback from the real world, both of which are slow.

Editing your reward function is like publishing an amendment to your model's constitution.

Big sister energy. Congratulations!

Kimi-K2 just took top spot on both EQ-Bench3 and Creative Writing! Another win for open models. Incredible job Kimi.ai

In a world with AI, doing isn’t the hard part anymore. The hard part is trusting. Reviewing. Verifying. Embracing. Deciding what matters. These are the bottlenecks now, and they are deeply human. We talk about AI agents accelerating science and automating research, and they