BasicAI Will Present the World’s First Open-Source Software for Multisensory Training Data
DVN (Driving Vision News) is hosting its 5th Automotive LiDAR Conference & Expo in Frankfurt, Germany from November 30th to December 1st. Since its first iteration, DVN LiDAR Conference has been the must-go event for all enthusiasts and stakeholders in the automotive LiDAR ecosystem. This year, themed “Applications, Use Cases & Testing, Technology, Eco-System”, is their 5th Conference, and will platform around 250 global participants. These participants include managers, automakers, LiDAR suppliers, tier lighting suppliers, research outfits, and analysts, among other experts including industry leaders such as Dr. Christian Kobetz, Manager LiDAR at Mercedes-Benz AG, Clément Nouvel, CTO at Valeo, Mrinal S., Director of Technical Marketing at AEye Inc, etc. The conference is expected to:
“facilitate reciprocal access, communication, and business opportunities for stakeholders in LiDAR and the vehicle industry, and to continue building a new ecosystem for LiDAR and automotive integration” (DVN).
As an industry-leading AI data service supplier, BasicAI was invited to the conference. Here, BasicAI will present a major release, Xtreme1, the world’s first open-source software for LiDAR data.
BasicAI has a proven track record — over 6 years of AI training data experience. They are also a world leader in ML Data Management Services and Software, and the sole proprietor of the free, open-source Xtreme1 software. Xtreme1 is a Data-centric MLOps infrastructure that can rapidly accelerate the processing and management of LiDAR data. Xtreme1’s tools make cultivating LiDAR datasets faster than ever before by maximizing labeling and processing efficiency.
At the 5th DVN Automotive LiDAR Conference & Expo, BasicAI will be exhibiting at the Y-5 booth (see booth layout image below). BasicAI is looking forward to networking with the conference’s expert attendees to jointly build a promising ecosystem for LiDAR and automotive integration.
Learn more about Xtreme1 on GitHub:
