BI 193 Kim Stachenfeld: Enhancing Neuroscience and AI

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Kim Stachenfeld embodies the original core focus of this podcast, the exploration of the intersection between neuroscience and AI, now commonly known as Neuro-AI. That's because she walks both lines. Kim is a Senior Research Scientist at Google DeepMind, the AI company that sprang from neuroscience principles, and also does research at the Center for Theoretical Neuroscience at Columbia University. She's been using her expertise in modeling, and reinforcement learning, and cognitive maps, for example, to help understand brains and to help improve AI. I've been wanting to have her on for a long time to get her broad perspective on AI and neuroscience.
ble learned simulators.

0:00 - Intro
4:31 - Deepmind's original and current vision
9:53 - AI as tools and models
12:53 - Has AI hindered neuroscience?
17:05 - Deepmind vs academic work balance
20:47 - Is industry better suited to understand brains?
24?42 - Trajectory of Deepmind
27:41 - Kim's trajectory
33:35 - Is the brain a ML entity?
36:12 - Hippocampus
44:12 - Reinforcement learning
51:32 - What does neuroscience need more and less of?
1:02:53 - Neuroscience in a weird place?
1:06:41 - How Kim's questions have changed
1:16:31 - Intelligence and LLMs
1:25:34 - Challenges

[raginaldmars]

Mind Opiates to get you ever more Addicted to Mind Toys

[johannesbergcrantz]

Well... I as a "correct", empathetic and competent individual didnt exactly see any benefits to this AI revolution. And yet now (as were being told) its uninevitable . Megalomanical idiots will be able to use AI to mimick empathy, and carefullness (especially if theyre rich), and its feeding it back into ourselves? Im not exactly sure why im not excited tbh. Give it some tasks, let it fulfill them and stop making it into a philosophical matter, as its a tool :) Its not AI per se that is the problem, it would be the over-reliance on digital systems for access and moreover, denial of acces for arbitrary reasons (imo)