AI/ML, Deep Learning Tech Talks

Important note: Register on the AICamp Event Website is REQUIRED for admission.

From Code to Production - Building Production-Ready AI Agents on AWS

The AWS Agentic AI Partner Showcase features experts from AWS, TiDB, Fireworks AI, LaunchPad, Grafana Lab, CrowdStrike, who will demonstrate how to build production-ready agentic AI systems from code to deployment. This focused session presents a complete development stack through live demonstrations, technical deep dives, and interactive discussions.

In addition to main stage tech talks and demos, partner booths will be available onsite throughout the event for attendees to visit, engage in Q&A, and deep dive into each partner's solution. The speakers will share practical insights into building, monitoring, and validating agentic AI applications that enhance your business processes and drive innovation.

What You Will Learn:
✔ Production-Ready Agentic AI – See live demonstrations of the complete development stack for building agentic AI systems, from coding environments through deployment and monitoring.
✔ Technical Implementation Strategies – Gain insights from AWS and partner experts on deploying agentic AI solutions with real-world use cases and AWS integration patterns.
✔ Expert Q&A & Networking – Engage directly with technical leaders from AWS and partner companies at dedicated booth stations, plus connect with fellow developers and practitioners building agentic AI applications.

Agenda

• 4:30PM - 5:30PM Check-In, Food and Booth Visiting
• 5:30PM - 7:45PM Kick-off, Tech talks, Live Demo
• 7:45PM - 8:30PM Networking, Q&A over Booths

Featured Speakers:

• Srinivas Kesanapally, Sr PSA Manager, AWS
• Chris Hofmann, Senior Product Manager, TiDB
• Tim Miranda, Tech Fellow, LaunchPad
• Shawn Pitts, Senior Technical Manager, Grafana Lab
• Chad Lumsden-Dolence, Sr Solution Engineer, CrowdStrike
• Scott Gee, Lead Applied AI Engineer, Fireworks AI

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Important note: Register on the AICamp Event Website is REQUIRED for admission.

From Code to Production - Building Production-Ready AI Agents on AWS

The AWS Agentic AI Showcase features experts from AWS, MongoDB and LangChain, who will demonstrate how to build production-ready agentic AI systems from code to deployment. This focused session presents a complete development stack through live demonstrations, technical deep dives, and interactive discussions.

In addition to main stage tech talks and demos, partner booths will be available onsite throughout the event for attendees to visit, engage in Q&A, and deep dive into each partner's solution. The speakers will share practical insights into building, monitoring, and validating agentic AI applications that enhance your business processes and drive innovation.

What You Will Learn:
✔ Production-Ready Agentic AI – See live demonstrations of the complete development stack for building agentic AI systems, from coding environments through deployment and monitoring.
✔ Technical Implementation Strategies – Gain insights from AWS and partner experts on deploying agentic AI solutions with real-world use cases and AWS integration patterns.
✔ Expert Q&A & Networking – Engage directly with technical leaders from AWS and partner companies at dedicated booth stations, plus connect with fellow developers and practitioners building agentic AI applications.

Agenda

• 4:30PM - 5:30PM Check-In, Food and Booth Visiting
• 5:30PM - 7:45PM Kick-off, Tech talks, Live Demo
• 7:45PM - 8:30PM Networking, Q&A over Booths

Featured Speakers:

• Abhijit Chakraborty, Senior Partner Solutions Architect, MongoDB
• Andrew Selden, Deployed Engineer, LangChain
• Doug Mbaya, Sr Partner Solutions Architect - Data and AI, AWS
• Karan Singh, Head of Partnerships, LangChain

Sep 17, 2026
9:00 AM - 11:00 AM PST
Online. Register for the Zoom!

AI for Autonomous Driving: From Data to Decisions

Building reliable automated driving systems is as much a data and engineering challenge as a modeling one. In this talk, Tin will share perspectives from his work at Porsche AG on applying modern AI methods across the autonomous driving development process, from making sense of large-scale driving data to understanding and evaluating how AI-based systems behave on the road. He'll discuss lessons learned from real-world development, where today's approaches shine, and where hard problems remain for the ADAS and AV community.

About the Speaker

Tin Stribor Sohn is a PhD Student at Porsche AG and Karlsruhe Institute of Technology in the area of Foundation Models for Scenario Understanding and Decision Making in Autonomous Robotics, Tech Lead at Data Driven Engineering for Autonomous Driving, Prior: Master in CS at University of Tuebingen with focus on Computer Vision and Deep Learning and co-founder of a software company for smart EV charging

Advancing ADAS and Autonomous Vehicle Development with Multimodal Data

ADAS and autonomous vehicle systems rely on increasingly complex data from cameras, video, LiDAR, radar, and other sensor streams. In this session, Murilo will introduce Voxel51 and explore how the latest multimodal capabilities in FiftyOne help teams bring these data sources together to better understand their datasets and model behavior. He’ll discuss how unified workflows for visualization, search, curation, and evaluation can help ADAS and AV teams uncover challenging scenarios, investigate model failures, and build safer, more reliable autonomous systems.

About the Speaker

Murilo Gustineli is a Machine Learning Engineer at Voxel51 working at the intersection of representation learning and computer vision. He holds an M.S. in Computer Science from Georgia Tech, where he co-leads the DS@GT Applied Research & Competitions group, advancing machine learning research through competitive challenges and peer-reviewed publications.

From Survey-Grade Maps to Physical AI: Scaling Real-World Data for Training and Simulation

Physical AI systems are increasingly constrained not by model architectures, but by the availability of scalable, high-fidelity real-world data. This talk explores how Dynamic Map Platform transforms survey-grade road assets collected across 1.8 million km of roads worldwide into training- and simulation-ready datasets, including point clouds, imagery, HD maps, road surface models, and 3D Gaussian Splatting representations.

We will discuss why geometric accuracy, semantic understanding, and real-world diversity are critical to building robust autonomous driving systems. Attendees will learn how real-world geospatial data can be structured and scaled for AI training and simulation workflows.

About the Speaker

Ryoto Miyake is a Software Engineer at Dynamic Map Platform, where he works on transforming large-scale geospatial data into AI-ready datasets for training, simulation, and validation, such as HD maps and 3D Gaussian Splatting. With a background in transportation engineering, he works closely with automotive manufacturers and industry partners to bridge large-scale real-world mapping data with next-generation AI and mobility systems.

Sep 22, 2026
9:00 AM - 10:00 AM Pacific
Online. Register for the Zoom!

Ask it to find and remove duplicate images, run object detection and surface low-confidence predictions, or evaluate a model and summarize where it fails, and the agent handles execution end to end.

We will also walk through the newest capabilities shipping with this release, including code generation and plugin generation. You will see how to go from a conversational prompt to a custom dashboard, visualization, or full FiftyOne application, and how to package multi-step workflows as reusable skills the agent can call on demand.

Because the agent runs inside FiftyOne's secure guardrails, teams keep full control. Connect your preferred models from over 100 LLM providers, route requests through your own enterprise gateway, and maintain audit logging and user attribution for every action the agent takes.