As I’m starting my lab, I’m already working close with @stri_panama to study their flexible decision making. And looking to hire postdocs with experience in neuroscience develop system and help pioneer neuroscience in the animals natural ecosystems. 🎩 @TrackingActions #zeroshot.

Ken Harris’ Thoughts on Using AI in Neuroscience Ken Harris, a well-known neuroscientist, acknowledged AI's utility, especially for tasks like video analysis using tools like DeepLabCut. However, he expressed caution about over-relying on deep learning, as these models can predict data well without providing clear understanding. Harris prefers classical machine learning techniques, like kernel methods and Bayesian inference, because they offer more interpretability. He believes understanding AI models might always remain challenging, just as understanding the brain’s complex neural circuits is. He argued that classical approaches still have a place, serving as a benchmark for assessing how much more predictive AI models really are. Comparing traditional and AI-driven methods can reveal how much we truly understand about brain function.