Edwin Chen

Current AI development risks prioritizing engagement and 'flashy' responses over accuracy and meaningful human advancement.

"I'm worried that instead of building AI that will actually advance us as a species, curing cancer, solving poverty, understand the universe, we are optimizing for AI slop instead. But we're optimizing..."

Standard AI benchmarks are often flawed and easily gamed, failing to represent real-world performance and ambiguity.

"I don't trust the benchmarks at all... the benchmarks themselves are often honestly just wrong. They have wrong answers... these benchmarks at the end of the day, they often have well-defined objectiv..."

Deep human evaluation by domain experts is superior to casual user feedback or automated benchmarks for measuring true model progress.

"The way we really care about measuring model progress is by running all these human evaluations... because or searchers or annotators, they are experts at the top of their fields, and they are not jus..."

AI models will become increasingly differentiated based on the specific values and objective functions chosen by their creators.

"I've realized that the values that the companies have will shape the model... Do you want a model that says, 'You're absolutely right. There are definitely 20 more ways to improve this email,' and it..."

Reinforcement learning in simulated environments allows models to learn complex, multi-step tasks that static datasets cannot teach.

"Reinforcement learning is essentially training your model to reach a certain reward. And let me explain what an RL environment is. An RL environment is essentially a simulation of real world... we giv..."

AI training is evolving from simple mimicry (SFT) to preference-based learning (RLHF) and now to detailed, rubric-based grading.

"Originally, the way models started getting post-trained was purely through SFT [Supervised Fine-Tuning]... a lot like mimicking a master and copying what they do. And then RLHF became very dominant......"

Evaluating talent for complex tasks requires granular, data-driven tracking of performance signals rather than just checking boxes.

"we have to build all of this technology in order to measure it, like thousands of signals on all of our workers, thousands of signals on every project, every task. We know at the end of the day, if yo..."

High-performing teams can move significantly faster by remaining small and eliminating the distractions inherent in large organizations.

"I used to work at a bunch of the big tech companies and I always felt that we could fire 90% of the people and we would move faster because the best people wouldn't have all these distractions. So whe..."

A company's culture and decision-making framework should be a direct reflection of the founder's personal values and vision.

"I think one of the things that I didn't think about a couple years ago, but then someone said it to me, it's that companies in a sense are an embodiment of their CEO... when I think about certain big,..."

True innovation comes from a steadfast commitment to a unique insight rather than constant pivoting to find market fit.

"I would say don't pivot. Don't put scale. Don't hire that Stanford grad who simply wants to add a hot company to your resume, just build the one thing only you can build, a thing that wouldn't exist w..."