AI/ML

Session AI/ML

Finetuning Your Embedding Model for Better Search: Learning from Agentic Search at Dell

Tuesday Jun 2 / 02:30PM EDT

Embedding models are a foundational component of modern ML systems, enabling clustering, ranking, and large-scale information retrieval.

Speaker image - Rachel Shalom

Rachel Shalom

AI Applied Scientist & Distinguished Engineer @Dell, 7+ Years Experience Turning Cutting Edge AI into Real World Impact

Session Architecture

Architecting the Data Layer for AI Agents: From Transactional Systems to MCP and Semantic Models

Monday Jun 1 / 02:30PM EDT

Most conversations about production AI agents focus on the agent itself — the prompts, the orchestration, the framework. But the moment you put an agent in front of real enterprise data, a different problem dominates: the data layer wasn't designed for this consumer.

Speaker image - Fabiane Nardon

Fabiane Nardon

Data Expert, Java Champion & Data Platform Director @totvs

Session AI/ML

Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP

Monday Jun 1 / 11:30AM EDT

AI coding agents are powerful out of the box, but they don't know your company. They can't navigate your services, understand your frameworks, query your data systems, or follow your organizational processes.

Speaker image - Ajay Prakash

Ajay Prakash

Senior Staff Software Engineer @LinkedIn

Session AI/ML

From Fab To Token - The State Of The Market

Tuesday Jun 2 / 10:20AM EDT

This talk delivers a data-driven summary on the physical and economic bottlenecks in the AI infrastructure market today. We will cover the diverging strategies between traditional hyperscalers and specialized "Neoclouds," supported by deep supply chain data.

Speaker image - Jordan Nanos

Jordan Nanos

Member of Technical Staff @SemiAnalysis, Previously Distinguished Technologist @HPE

Session Extensibility

There's a Mod for That: Opening Up AI Agent Development

Monday Jun 1 / 01:20PM EDT

AI agents are moving amazingly fast — but they could be moving even faster. Today's agents are monolithic: one vendor controls the model, the tools, and the context pipeline. That works, but it leaves an enormous amount of potential on the table.

Speaker image - Niko Matsakis

Niko Matsakis

Senior Principal Engineer @Amazon, One of the Lead Designers of the Rust Programming Language, Creator of Symposium (symposium.dev), Project Director on the Rust Foundation Board

Session AI/ML

From Models to Agents: Building Context-Aware Consumer AI at Scale at DoorDash

Monday Jun 1 / 03:40PM EDT

Consumer AI is rapidly evolving beyond one-shot predictions toward systems that reason, plan, and adapt in real time.

Speaker image - Sudeep Das

Sudeep Das

Head of Machine Learning and Artificial Intelligence, New Business Verticals @DoorDash, Previously Machine Learning Lead @Netflix, 15+ Years in Machine Learning