About us
Join us to learn and practice AI, LLMs, GenAI, Agentic AI, Machine learning, Deep learning and Data Science technology together with like-minded developers.
Our goal is to congregate with AI enthusiasts from all over South Bay area to learn and practice AI tech, through tech talks, workshops, code labs etc.. we regularly invite tech leads from innovated companies, successful startups to share their practice experiences and practices in the world of AI, LLMs, GenAI, Agents, ML and Data.
If you’d like to speak at future meetups, co-promote your meetup or inquire about partnership opportunities, please feel free to reach out to us (info AT aicamp DOT ai)
Upcoming events
2
Agentic AI Meetup with Google Snowflake
Silicon Valley AI Hub, 135 Constitution Dr, 8th Floor, Menlo Park, CA, USImportant: 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: Demystifying Agentic Data Cloud and Data Agent Kit
Speaker: Sireesha Pulipati (Shopify, Google Developer Expert)
Abstract: Google's Agentic Data Cloud and Data Agent Kit have generated a lot of buzz, but what do they actually do? This talk cuts through the announcements to explain what these tools are, how they work together, and what they genuinely enable for data teams today.. Includes a live demo of Data Agent Kit in VS Code/Antigravity.Tech Talk: Building a Data Native Agent: Cortex Code
Speaker: Umesh Unnikrishnan, Snowflake
Abstract: Most coding agents treat the data platform as a black box — passing queries in and results out without understanding what's underneath. This talk explains how Snowflake built Cortex Code differently: directly wiring the agent to Snowflake's metadata, compute, and governance layers so it reasons about your actual environment instead of guessing. We'll walk through the architecture behind that context-aware loop, show how open standards like MCP and agent skills make it extensible, and share what we learned benchmarking it against both public and internal data engineering tasks.Tech Talk: Building Data Products with AI
Speaker: Ayanna Wade (AI4ALL)
Abstract: AI is transforming how data products are built by accelerating discovery, coding, and communication, but not replacing fundamentals. This talk explores what is changing, including rapid iteration and AI-assisted workflows, and what still matters, including problem definitions, data evaluation, and human judgment, along with some common failure modes and practical adoption patterns.Speakers/Topics:
If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit TopicsSponsors:
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.19 attendees
Scaling agentic AI systems in production for financial services
Silicon Valley AI Hub, 135 Constitution Dr, 8th Floor, Menlo Park, CA, USImportant: register on the external event website is required for admission.
In this Silicon Valley edition, Nu’s AI Core team, the centralized AI research and engineering organization, will pull back the curtain on how machine learning systems are operationalized at scale. The speakers will bypass surface-level concepts to dive deep into real production code, infrastructure trade-offs, and architectural constraints. Designed to be intimate and conversational, the evening prioritizes deep technical dialogue, peer connection, and high-density networking.
The session will cover:
- The infrastructure, data engineering, backend orchestration, and intelligence layer behind production-grade systems;
- Spanning predictive models trained on proprietary financial data;
- Autonomous agentic tool-calling pipelines;
- Custom simulation environments used for offline policy evaluation.
Who should attend:
This event is curated for ML Engineers, Senior Software Engineers, Tech Leads, and Systems Architects with a minimum of 5+ years of hands-on experience in core ML systems, large-scale backend, or distributed infrastructure. The session is specifically tailored for practitioners focused on model optimization, training efficiency, high-throughput cloud architecture, and the data pipelines required to deploy and orchestrate predictive and generative frameworks at scale. This space is designed for seasoned builders looking for deep architectural discussions on AI systems and peer-to-peer networking rather than surface-level product pitches.Agenda:
- 5:00 PM – Welcome Reception & Networking (Food and soft drinks served)
- 5:30 PM – Opening Remarks/Intro
- 5:40 PM – Tech Talk 1, by Aman Gupta (AI Core, Nu)
- 6:10 PM – Tech Talk 2: Effective quantization of Muon optimizer states, by Shao Tang (AI Core, Nu)
- 6:40 PM – Panel Discussion + Audience Q&A
- 7:30 PM – Happy Hour & Open Mixer (Beer, wine, and refreshments)
- 8:30 PM – Event Conclusion
5 attendees
Past events
219
