Crash Course in AI: Formula E Edition
Introduction
Given the close proximity racing, varying track conditions, and high speeds of electric cars, incidents in Formula E are virtually inevitable. The series’ aggressive, unpredictable nature combined with street circuits often leads to crashes and collisions.
In this gHack we’ll analyze multimodal data to detect crashes and find the drivers that were involved by using Gemini.
We’ll start with semantic search to detect crashes from video footage. Once we have found a crash we’ll correlate that with telemetry data and determine the involved drivers.
Learning Objectives
During the process we’ll learn about
- BigQuery Object tables
- Multimodal embeddings & Vector search in BigQuery
- Retrieval Augmented Generation (RAG)
- BigQuery for analyzing tabular data
Challenges
- Challenge 1: Getting in gear
- Challenge 2: Formula E-mbed
- Challenge 3: Formula E RAG-ing
- Challenge 4: Telemetry to the rescue!
Prerequisites
- Basic knowledge of GCP
- Basic knowledge of Python
- Basic knowledge of SQL
- Access to a GCP environment
Contributors
- Murat Eken
- Michelle Liu
- Deb Lee
- Gino Filicetti