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
LLM Powered Search Recommendations and Growth Strategy
Tuesday Nov 19 / 10:35AM PST
In this deep exploration of employing Large Language Models (LLMs) for enhancing search recommendation systems, we will conduct a technical deep dive into the integral aspects of developing, fine-tuning, and deploying these advanced models.
Faye Zhang
Senior Software Engineer @Pinterest, Lead on GenAI Search Traffic Projects, Speaker, Expert in AI/ML with a Strong Background in Full-Stack Development
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
Unconference: GenAI
Tuesday Nov 19 / 02:45PM PST
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
