AI/ML, Deep Learning Tech Talks

Important note: Register on AICamp website is REQUIRED for admission.

Description:
Welcome to the 'AI Dev Showcase Night SF' series, co-hosted with Workato. This series bring the Workato and AICamp communities together for an evening dedicated to deep-dive tech talks, hands-on labs, and high-impact technical networking. Expect the best innovative AI demos and conversations built for technical audiences.

At this September Edition, we team up with Coder to dive deep into coding agents and AI-native development.

Agenda:
- 5:30pm~6:00pm: Checkin, food and networking
- 6:00pm~6:15pm: Welcome and Community update
- 6:15pm~7:30pm: Tech talks and Q&A
- 7:30pm~8:30pm: Open discussion, Mixer and Closing.

Speakers/Topics:
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors:
We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 50,000+ AI developers in San Francisco and 500K+ in global.

Important Note: register on the external event website is required for admission

Description:
Welcome to the AI meetup in Silicon Valley. Join us for deep dive tech talks on AI, GenAI, LLMs and Agent, hands-on experiences on code labs, workshops, and networking with speakers and fellow developers.

Agenda:
- 5:30pm~6:00pm: Checkin, food and networking
- 6:00pm~6:10pm: Welcome, Community update
- 6:10pm~8:00pm: Tech talks and Q&A
- 8:00pm~8:30pm: Open discussion, Mixer and Closing.

Tech Talk: Stop Writing Text-to-SQL: Give the LLM the Job It's Actually Good At
Speaker: Ashish Shubham, Engineering Fellow at ThoughtSpot
Abstract: Most agentic analytics projects start by asking an LLM to write SQL. It demos well and fails in production. The problem isn't broken syntax; it's queries that run, return a number, and are quietly wrong. Fan traps. Unvalidated join paths. Same question, different answer.
We'll present the right way to build instead: a semantic/context layer where metrics, join paths, and permissions are defined once and enforced deterministically, exposed to the agent as a narrow tool surface rather than a SQL field. We'll close with a real working solution built on this architecture and its trade-offs.

Speakers/Topics:
Stay tuned as we are updating more speakers and topics.
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics

Sponsors:
We are actively seeking sponsors to support AI developers community. Whether it is by offering venue spaces, providing food, or cash sponsorship. Sponsors will not only speak at the meetups, receive prominent recognition, but also gain exposure to our extensive membership base of 50,000+ AI developers in San Francisco Bay Area and 500K+ worldwide.

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.