Ep.30-SPECIAL REPORT: The State Of Autonomous Vehicles With Chris Piche of Smarter AI
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Want to add strategic pricing to your marketing tool box? Go to InteliChek or call 877-827-7273 and ask about our InteliShare Series! InteliShare contains all of our promotional tools that you can use to promote your favorable prices, including our InteliAds, the printable flyers that you can show off in easel displays, InteliMedia, for your Digital Media Boards AND InteliWidgets, so you can show off price comparisons on your website and even let your customers schedule from the widget. With one look at Chris Piche's résumé, it becomes apparent that his thoughts on this technology should be heard. He has developed and patented foundational technologies, products, and standards for AT&T, BlackBerry, Polycom, and the Open Connectivity Foundation, earning recognition as Best of Internet World, Canada’s Top Young Leader, and Top 40 under 40. Chris Piche, the founder and CEO of Smarter AI, discusses the current state of autonomous vehicles and addresses misconceptions about their safety. He explains that autonomous vehicles are approximately 10 times safer than human-driven vehicles and emphasizes the importance of understanding the limitations of current driver assistance systems. Chris also discusses the challenges and future prospects of autonomous vehicles, including the need for government regulation and the potential for widespread adoption. He compares the benefits of autonomous vehicles to electric vehicles and shares his background in developing communication technologies. Takeaways
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- Autonomous vehicles are approximately 10 times safer than human-driven vehicles.
- Current autonomous systems are advanced driver assistance systems and require responsible use.
- The acceptance of autonomous vehicles by the public is a sociological issue that depends on factors such as perceived safety and trust.
- The future of transportation will involve connected autonomous vehicles that communicate with each other and traffic infrastructure.
- The safety and effectiveness of autonomous systems depend on the quality and diversity of the training data used for machine learning models.
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