Autonomous Driving: Innovations and Challenges

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This chapter explores the evolution of autonomous driving technology, focusing on the shift from traditional methods to machine learning-driven approaches. It highlights the successes and shortcomings of major players like Waymo and Tesla, discussing the implications of different technological strategies, including the use of LiDAR and camera systems. The conversation also addresses the economic challenges of operating autonomous vehicles, reflecting on the industry's path towards sustainable practices.

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Todays show:

Comma’s Harald Schäfer joins Jason to discuss the future of autonomous driving, Comma’s open-source approach (7:24), how camera-based systems stack up against lidar (20:52), self-driving technology developments globally (32:55), and more!

Timestamps:

(0:00) Comma’s Harald Schäfer joins Jason

(2:02) Comma's approach to self-driving technology

(4:06) Cost, installation, and car manufacturers' reactions to Comma

(6:38) .Tech Domains - Apply for the Jam Session with JCal contest today at https://jamwithjcal.tech

(7:24) Open source and different approaches in autonomous driving

(13:08) Comparing Waymo, Tesla FSD, and comma AI's strategies

(20:52) Lidar vs. camera-based systems in autonomy and the advantages of camera-based systems over human drivers

(24:05) Vanta - Get $1000 off your SOC 2 at https://www.vanta.com/twist

(24:56) Autonomous vehicle rollout timeline and predictions

(27:33) Open source projects and major car manufacturers' adoption

(31:25) Micro1 - Visit https://www.micro1.ai/twist to open a talent search and get a 2 week free trial per hire.