Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
HAI Weekly Seminar with Michael Frank | Stanford HAI

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Research Programs
    • Grants
    • Marlowe (opens in new tab)
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
Your browser does not support the video tag.
eventSeminar

HAI Weekly Seminar with Michael Frank

Status
Past
Date
Wednesday, May 19, 2021 10:00 AM - 11:00 AM PST/PDT
Topics
Education, Skills
Overview
Watch Event Recording

Bigger Data About Smaller People: Investigating Children's Language Learning at Scale

Overview
Watch Event Recording
Share
Link copied to clipboard!
Event Contact
Celia Clark
celia.clark@stanford.edu

Related Events

Marcos Santiago Rojas Pino & Thomas Caruso | Building an International AI Platform for Health Professions Education and the Learning Sciences
SeminarNov 04, 202612:00 PM - 1:15 PM
November
04
2026

Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.

Seminar

Marcos Santiago Rojas Pino & Thomas Caruso | Building an International AI Platform for Health Professions Education and the Learning Sciences

Nov 04, 202612:00 PM - 1:15 PM

Clinical Mind AI is a Stanford-developed, international collaborative platform designed to strengthen clinical reasoning education through AI-simulated patient encounters across health professions.

Neil Thompson: Forecasting AI’s Impact on Human Expertise and the Future of Work
Oct 12, 202612:00 PM - 1:00 PM
October
12
2026

AI is advancing rapidly at the cognitive tasks that make up knowledge work, raising fears among firms, policymakers, and, not least, workers of a “China shock” for white-collar jobs. Neil Thompson will present new research on whether those fears are warranted.

Event

Neil Thompson: Forecasting AI’s Impact on Human Expertise and the Future of Work

Oct 12, 202612:00 PM - 1:00 PM

AI is advancing rapidly at the cognitive tasks that make up knowledge work, raising fears among firms, policymakers, and, not least, workers of a “China shock” for white-collar jobs. Neil Thompson will present new research on whether those fears are warranted.

Marlowe | AI + Data for Science with Curtis Langlotz
SeminarOct 14, 2026
October
14
2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Event

Marlowe | AI + Data for Science with Curtis Langlotz

Oct 14, 2026

Sessions run Wednesdays from 4:30–5:30 PM in CoDa E160. Each session features a different Stanford speaker; talk titles are announced by the organizers.

Every typically developing child learns to talk, but children vary tremendously in how and when they do so. What predicts this variability? And which aspects of early language learning are consistent across the world’s languages and cultures? We use data from tens of thousands of children learning dozens of different languages to create a framework for building and evaluating predictive models of language development. 

Michael Frank
David and Lucile Packard Professor of Human Biology, and Director, Symbolic Systems Program.