HAI Weekly Seminar with Thomas Dimson - Algorithms Algorithms Algorithms | Stanford HAI
Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Skip to content
  • About

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

    • Research
    • Fellowship Programs
    • Grants
    • 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

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

Your browser does not support the video tag.
eventSeminar

HAI Weekly Seminar with Thomas Dimson - Algorithms Algorithms Algorithms

Status
Past
Date
Friday, February 28, 2020 11:00 AM - 12:00 PM PST/PDT

Abstract: The biggest challenge with the democratization of content is how to make sense of the scale. In the last decade, curation of content has consolidated into the hands of a few of the largest technology companies. Today, that curation takes the form of machine learning — often dubbed algorithms by the media. Thomas helped build and introduce the most controversial algorithms of Instagram: non-chronological feed and personalized recommendations. He will discuss challenges from the perspective of an engineer in the control room as Instagram scaled to serve over a billion people. Thomas will share a few of his thoughts about future directions as we start to form a dialogue about the responsibilities of platforms operating on a global scale.

Bio: Thomas Dimson is the original author of “The Algorithm” — the recommender systems behind Instagram's feed, stories and discovery surfaces. He joined Instagram as one of its first 50 employees in 2013, working for seven years as a principal engineer and eventually an engineering director. In that time, he also invented products such as the stories polling sticker, Hyperlapse, and engineering and was named one of the top ten most creative people in business by Fast Company. Thomas graduated from the University of Waterloo with a bachelor's of mathematics and received his master's in computer science from Stanford with a specialization in artificial intelligence.

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

Related Events

2026 Conference on Physics and AI (PAI26)
ConferenceJun 10, 2026
June
10
2026

The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced computational methods. 

Event

2026 Conference on Physics and AI (PAI26)

Jun 10, 2026

The Center for Decoding the Universe brings together researchers across scientific disciplines to answer the biggest questions about our Universe by leveraging complex data with the most advanced computational methods. 

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS
WorkshopJul 15, 20262:00 PM - 3:30 PM
July
15
2026

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Event

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS

Jul 15, 20262:00 PM - 3:30 PM

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!