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Blog - Jason Wei

Cognitive reward shapes in sports and career — Jason Wei What's left for humans? — Jason Wei Life lessons from reinforcement learning — Jason Wei Asymmetry of verification and verifier’s rule — Jason Wei AI research is a max-performance domain — Jason Wei Successful language model evals — Jason Wei Six intuitions about large language models — Jason Wei Observations from tracking Twitter — Jason Wei Common arguments regarding emergent abilities — Jason Wei Practicing AI research — Jason Wei Research I enjoy — Jason Wei 137 emergent abilities of large language models — Jason Wei
Dopamine cycles in AI research — Jason Wei
Jan 21 Written By Jason Wei · 2025-01-22 · via Blog - Jason Wei

There is a dopamine cycle in doing AI research that is pretty interesting.

Every day you wake up and you think about what experiment to run. You think thing X matters so you decide to improve it or ablate it. Then you write the code and pay some compute to find out the answer. Then you get dopamine or confusion depending on whether the result matched expectations.

For experiments that are small scale you can get several reward signals quickly and develop your intuition. Other times you make a big bet that is non-obvious or controversial and go through a period of hard work, dopamine starvation, and uncertainty to do it. If it works out it's a immense high but if it fails it's natural to be consumed by helplessness.

Sometimes there is an element of ego. You may believe in X or not, and keep working to find evidence to support it or excuses for why it doesn't apply in that experiment. There can be an underlying urge to either to prove your abilities or to show that you’re still relevant in the quickly changing landscape. Science is supposedly objective but the reality is that there is a huge social aspect to it, and respect of peers is an valuable reward signal to seek.

That’s how I feel about it, at least. Every day is a small journey further into the jungle of human knowledge. Not a bad life at all—one i’m willing to do for a long time.