Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
NVIDIA & Marlowe: Scaling Code Agents for 100M+ LOC | 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

Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
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
Your browser does not support the video tag.
eventWorkshop

NVIDIA & Marlowe: Scaling Code Agents for 100M+ LOC

Status
Past
Date
Wednesday, June 03, 2026 2:00 PM - 3:30 PM PST/PDT
Location
CoDa Building, Room W101, 1st floor, 389 Jane Stanford Way, Stanford, CA 94305
Attend Virtually
Share
Link copied to clipboard!
Event Contact
sophican@stanford.edu

Related Events

Serena Wang: From Metric Selection to Metric Discovery in AI Evaluation
SeminarOct 16, 20261:00 PM - 2:15 PM
October
16
2026
Seminar
Your browser does not support the video tag.

Serena Wang: From Metric Selection to Metric Discovery in AI Evaluation

Oct 16, 20261:00 PM - 2:15 PM
Carina Hong | AI That Can Prove It: From Mathematical Discovery to Verified Software
Oct 19, 202612:00 PM - 1:00 PM
October
19
2026

A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.

Event

Carina Hong | AI That Can Prove It: From Mathematical Discovery to Verified Software

Oct 19, 202612:00 PM - 1:00 PM

A eureka moment is a two-step process: discovering something new and surprising, and establishing that it is correct. Drawing on her work at Axiom, Carina will discuss the transition from solving mathematical benchmarks to contributing to research, and from proving individual theorems to formalizing mathematical theories in Lean.

Nicholas Branigan | Non-ergodicity and Simpson’s paradox in neural correlates
SeminarOct 19, 20264:00 PM - 5:00 PM
October
19
2026

A Center for Neural Data Science Seminar Series

Event

Nicholas Branigan | Non-ergodicity and Simpson’s paradox in neural correlates

Oct 19, 20264:00 PM - 5:00 PM

A Center for Neural Data Science Seminar Series

Abstract

This talk will cover how to use NVIDIA GPUs and GPU-accelerated techniques to efficiently index, update and search massive code-bases with over 100M lines of code. Building an index slashes tokens by nearly 70% without compromising speed or accuracy in vibe coding.

Special Speakers | Rohan & James

Rohan is a Senior Solutions Architect at NVIDIA, working with enterprise partners on Generative AI adoption. In his previous role, he worked on the autonomous vehicles team at NVIDIA and prior to that, founded a startup working on advanced driver assistance systems (ADAS) for trucking fleets. Rohan earned a Master's degree in Robotic Systems Development from Carnegie Mellon University.

James is a Senior Solutions Architect on the NVIDIA Media and Entertainment SA team focused on the intersection of AI and video games. James earned his Master's degree in Data Analytics from Pennsylvania State University. Outside of work, he is a passionate snowboarder and gamer.