Cover Image for AI x Hardware Engineering Dinner
Cover Image for AI x Hardware Engineering Dinner
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Simr Events
Empowering Rapid, Data-Driven Decisions Across the Product Lifecycle

AI x Hardware Engineering Dinner

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About Event

AI x Hardware Engineering Dinner

Building Robust Data Pipelines for Physical Product Development


About the Dinner Event

AI in hardware engineering is notoriously hard to execute well. 

We’re bringing together Bay Area CAE engineers and hardware leaders to move past the hype and discuss the critical infrastructure that makes AI for physics actually work.

Still treating simulation data like a collection of files? We’ll be discussing the specific data governance, lineage, and reusability frameworks that separate AI-curious teams from AI-enabled competitors.

The Schedule

  • 5:00 PM: Welcome & Casual Networking

  • Open discussion topics:

    • Building Robust Data Pipelines

    • Breaking the "File Server Trap"

    • Overcoming the "Data Janitor" Trap

    • Scaling Beyond Proof-of-Concepts

  • 7:00 PM: Event Wrap-up

No product pitches or demonstrations.

Why Attend?

In the engineering world, "bad data" is rarely obvious; it’s sneakier—simulation results separated from setup details or historical data locked in closed formats. This workshop focuses on topics such as:

  • Breaking the "File Server Trap": Moving from fragile folder paths to queryable metadata.

  • Scaling Beyond Proof-of-Concepts: How to build production-grade pipelines that don't collapse when they leave a laptop.

The format of the meeting is casual and we talk over a nice dinner. The number of participants is capped at 10 to keep the discussion organized and to provide a valuable networking opportunity. 


Details

  • Location: Il Fornaio, Burlingame, California

  • Food: Dinner and beverages provided by our hosts at Simr

  • Capacity: Limited to maintain high-signal conversations. 

Location
Il Fornaio
327 Lorton Ave, Burlingame, CA 94010, USA
Avatar for Simr Events
Presented by
Simr Events
Empowering Rapid, Data-Driven Decisions Across the Product Lifecycle