Uploaded November 2020 | Updated September 2026, 2 hours ago
Patreon support: patreon.com/braininspired
Free Video Series: Open Questions in AI and Neuroscience:
braininspired.co/open
Show notes: braininspired.co/podcast/88
Randy and I discuss his LEABRA cognitive architecture that aims to simulate the human brain, plus his current theory about how a loop between cortical regions and the thalamus could implement predictive learning and thus solve how we learn with so few examples. We also discuss what Randy thinks is the next big thing neuroscience can contribute to AI and much more.
Timestamps:
0:00 - Intro
3:54 - Skip Intro
6:20 - Being in awe
18:57 - How current AI can inform neuro
21:56 - Anna Schapiro question - how current neuro can inform AI.
29:20 - Learned vs. innate cognition
33:43 - LEABRA
38:33 - Developing Leabra
40:30 - Macroscale
42:33 - Thalamus as microscale
43:22 - Thalamocortical circuitry
47:25 - Deep predictive learning
56:18 - Deep predictive learning vs. backrop
1:01:56 - 10 Hz learning cycle
1:04:58 - Better theory vs. more data
1:08:59 - Leabra vs. Spaun
1:13:59 - Biological realism
1:21:54 - Bottom-up inspiration
1:27:26 - Biggest mistake in Leabra
1:32:14 - AI consciousness
1:34:45 - How would Randy begin again?
Patreon support: patreon.com/braininspired
Free Video Series: Open Questions in AI and Neuroscience:
braininspired.co/open
Show notes: braininspired.co/podcast/88
Randy and I discuss his LEABRA cognitive architecture that aims to simulate the human brain, plus his current theory about how a loop between cortical regions and the thalamus could implement predictive learning and thus solve how we learn with so few examples. We also discuss what Randy thinks is the next big thing neuroscience can contribute to AI and much more.
Timestamps:
0:00 - Intro
3:54 - Skip Intro
6:20 - Being in awe
18:57 - How current AI can inform neuro
21:56 - Anna Schapiro question - how current neuro can inform AI.
29:20 - Learned vs. innate cognition
33:43 - LEABRA
38:33 - Developing Leabra
40:30 - Macroscale
42:33 - Thalamus as microscale
43:22 - Thalamocortical circuitry
47:25 - Deep predictive learning
56:18 - Deep predictive learning vs. backrop
1:01:56 - 10 Hz learning cycle
1:04:58 - Better theory vs. more data
1:08:59 - Leabra vs. Spaun
1:13:59 - Biological realism
1:21:54 - Bottom-up inspiration
1:27:26 - Biggest mistake in Leabra
1:32:14 - AI consciousness
1:34:45 - How would Randy begin again?
