In this intriguing episode of the Artificial Intelligence After Work (AIAW) Podcast, Daniel Langkilde, Co-founder and CEO of Kognic, discusses the intersection of artificial intelligence and autonomous vehicles. The conversation kicks off with the origins of Kognic, focusing on how they gather appropriate data for machine learning tasks. The discussion then shifts to the nuances of developing hardware and software for the automotive industry, with an explanation of what an embedding space is and the contrast between symbolic computation and deep learning. Langkilde elaborates on the workings of self-driving models and predicts when fully autonomous cars might become a reality on our roads. The episode also examines the pros and cons of Tesla's market strategy, Kognic's collaborations, and the moral decision-making of AI systems, specifically referencing the trolley problem. It addresses the broader impact of self-driving vehicles on jobs and society, the future of work, the possibility of communicating with superintelligent aliens, and concerns about technological singularity. Wrapping up, Langkilde shares the next steps for Kognic, his journey, and suggestions for future podcast guests, offering a comprehensive view of AI's role in advancing autonomous vehicle technology.

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