Uploaded July 2023 | Updated September 2026, 1 day ago
Show notes:
braininspired.co/podcast/171
Patreon for full episodes and Discord community:
patreon.com/braininspired
Video Series: Open Questions in AI and Neuroscience:
braininspired.co/open
Apple podcasts:
itunes.apple.com/us/podcast/brain-inspired/id1428880766?mt=2
Spotify:
open.spotify.com/show/2UZj8c8Ap5oc2gh2rJxLLe
Music by: The New Year:
thenewyear.net
My guest is Michael C. Frank, better known as Mike Frank, who runs the Language and Cognition lab at Stanford. Mike's main interests center on how children learn language - in particular he focuses a lot on early word learning, and what that tells us about our other cognitive functions, like concept formation and social cognition.
We discuss that, his love for developing open data sets that anyone can use,
The dance he dances between bottom-up data-driven approaches in this big data era, traditional experimental approaches, and top-down theory-driven approaches
How early language learning in children differs from LLM learning
Mike's rational speech act model of language use, which considers the intentions or pragmatics of speakers and listeners in dialogue.
0:00 - Intro
5:14 - Mike's early language research
10:14 - Building data tools and repositories
14:15 - Theory versus data approach
17:15 - Nature of early language data
20:38 - Current state of understanding early language learning
34:20 - Function(s) of language
39:52 - Development vs development of language
46:36 - Early language learning vs. LLMs
54:03 - Pragmatic inference
59:56 - Rational speech act model
1:09:04 -RSA vs LLMs
1:13:51 - Large vision vs. language models and the brain
Show notes:
braininspired.co/podcast/171
Patreon for full episodes and Discord community:
patreon.com/braininspired
Video Series: Open Questions in AI and Neuroscience:
braininspired.co/open
Apple podcasts:
itunes.apple.com/us/podcast/brain-inspired/id1428880766?mt=2
Spotify:
open.spotify.com/show/2UZj8c8Ap5oc2gh2rJxLLe
Music by: The New Year:
thenewyear.net
My guest is Michael C. Frank, better known as Mike Frank, who runs the Language and Cognition lab at Stanford. Mike's main interests center on how children learn language - in particular he focuses a lot on early word learning, and what that tells us about our other cognitive functions, like concept formation and social cognition.
We discuss that, his love for developing open data sets that anyone can use,
The dance he dances between bottom-up data-driven approaches in this big data era, traditional experimental approaches, and top-down theory-driven approaches
How early language learning in children differs from LLM learning
Mike's rational speech act model of language use, which considers the intentions or pragmatics of speakers and listeners in dialogue.
0:00 - Intro
5:14 - Mike's early language research
10:14 - Building data tools and repositories
14:15 - Theory versus data approach
17:15 - Nature of early language data
20:38 - Current state of understanding early language learning
34:20 - Function(s) of language
39:52 - Development vs development of language
46:36 - Early language learning vs. LLMs
54:03 - Pragmatic inference
59:56 - Rational speech act model
1:09:04 -RSA vs LLMs
1:13:51 - Large vision vs. language models and the brain
