Timothy B. Lee of the Understanding AI newsletter joins Ed Niedermeyer to unpack Tesla’s flashy robotaxi unveil.

In this episode of the Ride AI podcast, host Ed Niedermeyer interviews Anuja Sonalker, CEO of Steer Tech, to discuss a lesser-known success story in mobility technology. Anuja shares how Steer Tech, founded in 2016, specializes in low-speed, autonomous vehicle operations within geofenced areas like parking lots and depots. She explains that while parking automation was initially underestimated, it presents complex challenges requiring high precision and intelligence. Steer Tech developed the first fully autonomous Level 4 parking solution and has since expanded into broader vehicle orchestration systems. Their lean, customer-driven approach allowed them to achieve cashflow positivity by focusing on practical applications in fleet management, emphasizing operational efficiency, safety, and sustainability. Unlike many companies in the autonomous vehicle space, Steer Tech avoided big venture capital funding, choosing instead a more sustainable business model that balances innovation with profitability.

In this episode of Ride AI, recorded live at Micromobility Europe in Amsterdam, we delve into the evolving landscape of EV charging and automation with Crijn Bouman, founder of ROCSYS. Crijn shares his extensive journey in e-mobility, starting from his university days influenced by a friend's self-built electric bike, to founding ROCSYS, a company that develops autonomous EV charging robots for robotaxis, human-driven fleets, and more. He explores the critical advancements in EV fast-charging, the role of robotics in automating EV charging, and the broader implications for mobility and infrastructure.

On the latest episode of the Ride AI podcast, we dive into insurance, risk management, and driving automation with Michael Wagner, CEO of Edge Case Research. With autonomous vehicles poised to revolutionize transportation, understanding the risks and liabilities associated with this technology is paramount. Unlike traditional auto insurance, where policies are based on factors like driver history and vehicle usage, insuring self-driving vehicles requires a deeper understanding of the technology itself. Edge Case Research aims to fill this gap by providing risk assessment technology tailored specifically for autonomous cars and trucks. Michael sheds light on how this nascent industry is developing new insurance solutions that address the unique challenges of AVs, while incentivizing safe practices and fostering trust.

The latest Ride AI podcast episode features Stefan Seltz-Axmacher, the former founder of Starsky Robotics and current founder and CEO of Polymath Robotics, discussing his experiences in the self-driving truck industry. Stefan reflects on the challenges faced by Starsky Robotics, particularly the overconfidence in machine learning and the belief in a one-size-fits-all solution for autonomy, and how this experience informs Polymath Robotics, his new venture focused on building a generalized navigation layer for off-road vehicles. Stefan reflects on the history of self-driving trucks and the challenges faced during his time at Starsky Robotics, including the overconfidence in machine learning and the misconception that data collection alone would lead to successful autonomous driving. He highlights the difficulty in raising funds for a more focused approach compared to competitors' broader promises. Stefan discusses the need for a more grounded understanding of robotics and AI, emphasizing the importance of addressing specific problems rather than chasing general solutions. Polymath Robotics aims to democratize automation by reducing the upfront costs and complexity, allowing smaller players and seed-funded startups to compete effectively. Stefan emphasizes the parallels between the evolution of the automotive and smartphone industries, indicating a similar maturation process in robotics hardware.

On the latest episode of the Ride AI podcast, our host Ed Niedermeyer talks to Tyson Jominy, VP of Data & Analytics for J.D, Power, about the recent dynamics in the car market. They touch on COVID, the EV market, the prospect of another truck/SUV slowdown, and how these are all related. Discussion on the cyclicality of the auto industry and recent turbulence due to COVID-19: undersupply situation, excess savings leading to increased demand, and supply chain disruptions. Pricing dynamics in the EV market: oversupply of EVs in the $50-60k price range leading to price cuts. Fleet sales and their impact on EV market dynamics, including potential risks to resale value and pricing stability (Hertz struggled with high repair bills and consumer dissatisfaction with EV rentals, prompting them to unwind their EV-focused strategy.) Tesla's decision not to pursue a low-cost model raises questions about the industry's focus and the challenges of making EVs profitable. The auto industry seems to be retreating to familiar corners, like focusing on SUVs, hybrids, and high-margin segments, rather than investing heavily in lower-cost EVs. EVs face challenges in consumer perception and understanding of total cost of ownership, compared to hybrids, which have been around for a while but still face low adoption rates. The auto industry's struggle to make EVs profitable raises concerns about the future of EV adoption and the profitability of traditional segments like trucks and SUVs. There's uncertainty about the trajectory of EV adoption and whether there will be a "EV winter" where growth stalls. Regulatory factors still incentivize automakers to invest in EVs despite profitability challenges.

This week’s episode of the Ride AI podcast is a mind-meld between automotive analyst Ed Niedermeyer and tech-innovation scholar Horace Dediu about why the car industry is ripe for disruption. Their conversation is a reflection on the transformative power of past innovations like computers and phones, and the need to imagine a better future for mobility.  Together they discuss:  The concept of unbundling the car for different trip types and purposes, similar to computing devices Observation that the world seeks to improve cars, but they are already highly optimized Critique of current approaches by companies like Tesla and Apple, which aim to fit new technologies into the existing car model Emphasis on the need for truly disruptive innovation in mobility, either through cheaper, more accessible options or new directions of competition Discussion on the potential for self-driving technology to transform mobility by enabling new experiences and connections Examinations of the challenges of building an EV that is both cheap and has extensive battery range Why investors are over-focused on cars as a platform at the expense of other autonomous driving use-cases, like agriculture, defense, and transit.  ⌲ Subscribe to our free newsletter to stay on the forefront of the intersection of AI and mobility 👉 https://rideai.beehiiv.com/

For the inaugural episode of the new Ride AI podcast, author and analyst Ed Niedermeyer discusses the hype and disillusionment surrounding several new mobility technologies—namely autonomous vehicles—with Mike Ramsey, a vice president at Gartner. Ramsey explains the five parts of a hype cycle, including the innovation trigger and the trough of disillusionment, and provides historical analysis for where he believes autonomy is today on the road to mass adoption. Ed and Mike discuss the concept of the five-part "hype cycle" in technology adoption: innovation trigger, peak of inflated expectations, trough of disillusionment, slope of enlightenment, and plateau of productivity. The "slope of enlightenment" is explained as the phase where technologies become useful and start to see real-world applications. Autonomy in vehicles, while not profitable yet, is advancing (especially in robotaxis) Meanwhile autonomous technology is diffusing into other industries like agriculture, mining, and construction, where simple design domains allow for easier implementation. Despite challenges, significant investment in autonomy has advanced technologies like vision systems and edge AI. The hype surrounding autonomy is similar to that of other emerging technologies like generative AI, which may have significant impacts but will likely manifest in smaller, more practical applications initially. Media attention tends to focus on hype, but the most significant advancements often occur quietly, requiring deliberate effort to discover and understand. ⌲ Subscribe to our free newsletter to stay on the forefront of the intersection of AI and mobility 👉 https://rideai.beehiiv.com/

Prabin and Augustin discuss the Tier and Dott merger in the micromobility industry. Augustin predicts more consolidation with companies like Bold, Lime, and Voi. They explore software-defined vehicles and AVs in Europe, noting the lag behind the US and China. The potential for government support to advance AVs and shared mobility.

Apple is reportedly exiting the car industry to focus on software and mobility services. The company's strengths in software and user experience may be better applied to smart accessories and micromobility. The growing demand for sustainable transportation and urbanization trends align with Apple's transition. Smartphones are already integrated with cars through Apple CarPlay, and AI could enhance mobility experiences. Apple's secretive innovation and embrace of AI technology promise personalized, artificial worlds through the retina. The importance of accident prevention in wearable technology, such as Apple's devices, is emphasized for cyclist safety. The potential features of Apple's upcoming product, Apple Vision Pro, could revolutionize driving experiences with advanced sensors and navigation overlays.