Generally Intelligent Episode 25: Nicklas Hansen, UCSD, on long-horizon planning and why algorithms don't drive research progress
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Dec 16, 2022 AI Snips
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Early AI Curiosity
- Nicklas Hansen's childhood curiosity about AI stemmed from playing video games against surprisingly competent computers.
- He couldn't grasp how simple programming statements could create such complex AI behaviors.
Stumbling into Research
- Nicklas Hansen stumbled into research during college after initially not knowing it was a paid opportunity.
- He was drawn to research by the prospect of contributing impactful work beyond coursework and hobbies.
Generalization Issues
- Computer vision models trained on ImageNet struggled with generalization to similar datasets, a problem also faced by RL models.
- RL research at the time focused on single-task mastery with minimal randomization.