Uploaded September 2024 | Updated September 2026, 6 hours ago
Show notes: braininspired.co/podcast/193
Patreon (full episodes and Discord community):
patreon.com/braininspired
Apple podcasts:
itunes.apple.com/us/podcast/brain-inspired/id1428880766?mt=2
Spotify:
open.spotify.com/show/2UZj8c8Ap5oc2gh2rJxLLe
The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists.
Read more about our partnership: thetransmitter.org/partners
Check out this story:
Monkeys build mental maps to navigate new tasks thetransmitter.org/cognitive-neuroscience/monkeys-build-mental-maps-to-navigate-new-tasks
Sign up for the “Brain Inspired” email alerts to be notified every time a new “Brain Inspired” episode is released: thetransmitter.org/newsletters
To explore more neuroscience news and perspectives, visit thetransmitter.org.
Music by: The New Year:
thenewyear.net
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
Show notes: braininspired.co/podcast/193
Patreon (full episodes and Discord community):
patreon.com/braininspired
Apple podcasts:
itunes.apple.com/us/podcast/brain-inspired/id1428880766?mt=2
Spotify:
open.spotify.com/show/2UZj8c8Ap5oc2gh2rJxLLe
The Transmitter is an online publication that aims to deliver useful information, insights and tools to build bridges across neuroscience and advance research. Visit thetransmitter.org to explore the latest neuroscience news and perspectives, written by journalists and scientists.
Read more about our partnership: thetransmitter.org/partners
Check out this story:
Monkeys build mental maps to navigate new tasks thetransmitter.org/cognitive-neuroscience/monkeys-build-mental-maps-to-navigate-new-tasks
Sign up for the “Brain Inspired” email alerts to be notified every time a new “Brain Inspired” episode is released: thetransmitter.org/newsletters
To explore more neuroscience news and perspectives, visit thetransmitter.org.
Music by: The New Year:
thenewyear.net
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
