Uploaded November 2024 | Updated September 2026, 47 minutes ago
Tony Zador discusses why he's excited about how neuroscience can help "catalyze" the next generation of artificial intelligence.
Show notes:
braininspired.co/podcast/198
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.
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.
Check out Tony's essays in the Transmitter:
NeuroAI: A field born from the symbiosis between neuroscience, AI: thetransmitter.org/neuroai/neuroai-a-field-born-from-the-symbiosis-between-neuroscience-ai
What the brain can teach artificial neural networks: thetransmitter.org/neuroai/what-the-brain-can-teach-artificial-neural-networks
Tony Zador runs the Zador lab at Cold Spring Harbor Laboratory. You've heard him on Brain Inspired a few times in the past, most recently in a panel discussion I moderated at this past COSYNE conference - a conference Tony co-founded 20 years ago. As you'll hear, Tony's current and past interests and research endeavors are of a wide variety, but today we focus mostly on his thoughts on NeuroAI.
So, we're in a huge AI hype cycle right now, for good reason, and there's a lot of talk in the neuroscience world about whether neuroscience has anything of value to provide AI engineers - and how much value, if any, neuroscience has provided in the past.
Tony is team neuroscience. You'll hear him discuss why in this episode, especially when it comes to ways in which development and evolution might inspire better data efficiency, looking to animals in general to understand how they coordinate numerous objective functions to achieve their intelligent behaviors - something Tony calls alignment - and using spikes in AI models to increase energy efficiency.
If you like written essays, by chance Tony has written two essays, on the past and the future of NeuroAI, which are available on the Transmitter website and I think nicely complement our discussion on this episode. I'll link to those essays in the show notes, where I also link to a couple of the papers we discuss, and Tony's previous BI episodes.
0:00 - Intro
3:28 - "Neuro-AI"
12:48 - Visual cognition history
18:24 - Information theory in neuroscience
20:47 - Necessary steps for progress
24:34 - Neuro-AI models and cognition
35:47 - Animals for inspiring AI
41:48 - What we want AI to do
46:01 - Development and AI
59:03 - Robots
1:25:10 - Catalyzing the next generation of AI
Tony Zador discusses why he's excited about how neuroscience can help "catalyze" the next generation of artificial intelligence.
Show notes:
braininspired.co/podcast/198
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.
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.
Check out Tony's essays in the Transmitter:
NeuroAI: A field born from the symbiosis between neuroscience, AI: thetransmitter.org/neuroai/neuroai-a-field-born-from-the-symbiosis-between-neuroscience-ai
What the brain can teach artificial neural networks: thetransmitter.org/neuroai/what-the-brain-can-teach-artificial-neural-networks
Tony Zador runs the Zador lab at Cold Spring Harbor Laboratory. You've heard him on Brain Inspired a few times in the past, most recently in a panel discussion I moderated at this past COSYNE conference - a conference Tony co-founded 20 years ago. As you'll hear, Tony's current and past interests and research endeavors are of a wide variety, but today we focus mostly on his thoughts on NeuroAI.
So, we're in a huge AI hype cycle right now, for good reason, and there's a lot of talk in the neuroscience world about whether neuroscience has anything of value to provide AI engineers - and how much value, if any, neuroscience has provided in the past.
Tony is team neuroscience. You'll hear him discuss why in this episode, especially when it comes to ways in which development and evolution might inspire better data efficiency, looking to animals in general to understand how they coordinate numerous objective functions to achieve their intelligent behaviors - something Tony calls alignment - and using spikes in AI models to increase energy efficiency.
If you like written essays, by chance Tony has written two essays, on the past and the future of NeuroAI, which are available on the Transmitter website and I think nicely complement our discussion on this episode. I'll link to those essays in the show notes, where I also link to a couple of the papers we discuss, and Tony's previous BI episodes.
0:00 - Intro
3:28 - "Neuro-AI"
12:48 - Visual cognition history
18:24 - Information theory in neuroscience
20:47 - Necessary steps for progress
24:34 - Neuro-AI models and cognition
35:47 - Animals for inspiring AI
41:48 - What we want AI to do
46:01 - Development and AI
59:03 - Robots
1:25:10 - Catalyzing the next generation of AI
