Unleash the power of Generative AI! This track dives into the latest advancements, exploring how to translate groundbreaking research into real-world applications across various industries. Discover how to navigate the challenges and unlock the potential of AI-generated content, data, and code.
From this track
Scaling Large Language Model Serving Infrastructure at Meta
Tuesday Nov 19 / 10:35AM PST
Running LLMs requires significant computational power, which scales with model size and context length. We will discuss strategies for fitting models to various hardware configurations and share techniques for optimizing inference latency and throughput at Meta.
Ye (Charlotte) Qi
Senior Staff Engineer @Meta
GenAI for Productivity
Tuesday Nov 19 / 11:45AM PST
At Wealthsimple, we leverage Generative AI internally to improve operational efficiency and streamline monotonous tasks. Our GenAI stack is a blend of tools we developed in house and third party solutions.
Mandy Gu
Senior Software Development Manager @Wealthsimple
Navigating LLM Deployment: Tips, Tricks, and Techniques
Tuesday Nov 19 / 01:35PM PST
Self-hosted Language Models are going to power the next generation of applications in critical industries like financial services, healthcare, and defense.
Meryem Arik
Co-Founder @TitanML, Recognized as a Technology Leader in Forbes 30 Under 30, Recovering Physicist
Search: from Linear to Multiverse
Tuesday Nov 19 / 02:45PM PST
The future of search is undergoing a revolutionary transformation, shifting from traditional linear queries to a rich multiverse of possibilities powered by AI.
Faye Zhang
Staff Software Engineer @Pinterest, Tech Lead on GenAI Search Traffic Projects, Speaker, Expert in AI/ML with a Strong Background in Large Distributed System
10 Reasons Your Multi-Agent Workflows Fail and What You Can Do About It
Tuesday Nov 19 / 03:55PM PST
Multi-agent systems – a setup where multiple agents (generative AI models with access to tools) collaborate to solve complex tasks – are an emerging paradigm for building applications.
Victor Dibia
Principal Research Software Engineer @Microsoft Research, Core Contributor to AutoGen, Author of "Multi-Agent Systems with AutoGen" book. Previously @Cloudera, @IBMResearch
A Framework for Building Micro Metrics for LLM System Evaluation
Tuesday Nov 19 / 05:05PM PST
LLM accuracy is a challenging topic to address and is much more multi dimensional than a simple accuracy score. In this talk we’ll dive deeper into how to measure LLM related metrics, going through examples, case studies and techniques beyond just a single accuracy and score.
Denys Linkov
Head of ML @Voiceflow, LinkedIn Learning Instructor, ML Advisor and Instructor, Previously @LinkedIn
