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BEGIN:VEVENT

CATEGORIES:Medicine
CATEGORIES:Engineering
CATEGORIES:Lectures/Conferences
CATEGORIES:Other
CATEGORIES:Utilities
CATEGORIES:Lecture/Talk
CATEGORIES:Research
CATEGORIES:Technology
CATEGORIES:Main
CATEGORIES:Webcast
CONTACT;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf83-00000004:None
CREATED:20250903T152320Z
DESCRIPTION:Abstract:\nDesigning AI systems that are both fast and efficie
 nt has become a cornerstone for scaling modern machine learning to real-w
 orld impact. In this talk\, I will present a unified view of my research 
 contributions that push the limits of training and deploying large-scale 
 AI models efficiently\, without compromising performance.\nI will first i
 ntroduce LARS and LAMB\, two widely adopted optimizers that enable stable
  and scalable training of extremely large neural networks by addressing c
 hallenges in large-batch optimization. Notably\, according to NVIDIA's pu
 blic benchmarks\, LAMB achieves up to 17× speedup over\nstate-of-the-art 
 baselines for large-batch BERT pre-training\, making large-scale training
  practically feasible.\nI will then discuss my work on Sequence Paralleli
 sm and 2D Tensor Parallelism\, which break through memory and communicati
 on bottlenecks by decomposing training workloads in novel ways-making it 
 feasible to train trillion-parameter models on commodity hardware. Notabl
 y\, Sequence Parallelism has been adopted by leading organizations such a
 s NVIDIA and Meta in their large-scale training frameworks\, powering mod
 els like Megatron-LM and OPT.\nNext\, I will share our recent advances in
  Real-Time Video Generation with Pyramid Attention Broadcast (PAB)\, whic
 h demonstrates how efficient architectural design principles can enable h
 igh-quality generative models to operate in real time\, opening new direc
 tions for interactive AI applications. Finally\, I will highlight Colossa
 l-AI\, an open-source system that brings these algorithmic and system-lev
 el innovations together into a unified toolkit. With over 41\,000 GitHub 
 stars\, Colossal-AI has become one of the world's most popular open-sourc
 e projects for large-scale AI system design\, widely adopted by academia 
 and industry alike.\nBy connecting innovations across optimizers\, parall
 elism strategies\, system design\, and generative AI\, I hope to illustra
 te a coherent research vision for building the next generation of fast\, 
 efficient\, and accessible AI systems.
DURATION:PT1H
DTSTAMP:20250903T152320Z
DTSTART;TZID=America/New_York:20251204T090000
LAST-MODIFIED:20250903T152320Z
LOCATION;X-BEDEWORK-UID=00f1fcdb-0f068baf-010f-068baf6e-00000000:None
STATUS:CONFIRMED
SUMMARY:Fast and Efficient AI
UID:CAL-8a00ec8b-979413b9-0199-102ce101-000047c8demobedework@mysite.edu
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 hool_BME,":Biomedical Engineering (BME)
X-BEDEWORK-SPEAKER:Yang You\, Ph.D.\, Presidential Young Professor Nationa
 l University Of Singapore
X-BEDEWORK-DUKE-SERIES:Computational and Digital Health Seminar
X-BEDEWORK-STUDENT-CONTACT;X-BEDEWORK-PARAM-EMAIL=marnie.rhoads@duke.edu:M
 arnie Rhoads
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 orm/SV_1Aj3trWohZJaC7s":Registration Required
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