Episodit
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Today’s guest is Igal Raichelgauz, CEO at Autobrains. In this episode we discuss how self learning AI allows AVs to improve without labeled data, the limitations of requiring training data to improve AV performance, and Autobrains’ go-to-market approach over the next several years.
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Today’s guest is Eran Shir, Cofounder & CEO at Nexar. In this episode we discuss Nexar’s approach to building a “swarm sensor”, and how this modality will enable AVs with higher fidelity training data. We also explore the go-to-market mechanics of bringing a network sensor to the industry.
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Today’s guests are Christine Moon and Joel Pazhayampallil, Cofounders at BlueSpace.ai. In this episode we discuss 4D predictive perception, how this approach addresses the existing and future challenges of AV development, and BlueSpace’s go to market strategy over the next few years.
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Today’s guests are Koosha Kaveh and Sandip Gangakhedkar, Cofounders at Imperium Drive. In this episode we discuss teleoperations and why it is important for AVs, the challenges in ensuring safe teleoperations regardless of connectivity, and Imperium Drive’s go to market strategy over the next few years.
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Today’s guest is Steven Hong, CEO and Cofounder at Oculii. In this episode we discuss how AI-powered software can improve the resolution of radar by orders of magnitude, the merits of both software only and full stack approaches to radar development, and how the AV and ADAS markets will continue to develop over the next half decade.
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Today’s guest is Shahin Farshchi, Partner at Lux Capital. In this episode we discuss Amazon’s acquisition of Zoox, how the AV market has changed over the last 3 years, and the ripple effects R&D associated with AVs will have on the broader market.
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Today’s guest is Kevin McNamara, Founder and CEO at Parallel Domain. In this episode we discuss synthetic data and how it is used in training AVs, how AV companies are thinking about buying versus building this data moving forward, and whether or not synthetic data will replace real data in the future.
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Today’s guest is Chris Barker, President of CBC. In this episode we discuss the Las Vegas autonomous shuttle project, the current state of connected vehicles, and what the Infrastructure Investment and Jobs Act means for smart cities of the future.
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Today’s guest is Radha Basu, CEO at iMerit Technology Services. In this episode we discuss the data demands of AV companies, how iMerit helps them with complex edge cases, and the biggest challenges that still need to be addressed to further advance autonomous mobility in cities across the US.
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Today’s guest is Eitan Gertel, Founder & Executive Chairman at Opsys Technologies. In this episode we discuss Opsys’s approach to building a solid state LiDAR, how economies of scale will help drive costs down in the near term, and the company’s go to market approach over the next few years.
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Today’s guest is Paul Newman, Founder & CTO at Oxbotica. In this episode we discuss the complexities of developing AV technology that can be retrofitted onto any vehicle, Oxbotica’s go to market strategy and how they approach partnerships, and Paul’s vision for what the path to commercialization looks like for autonomous passenger vehicles.
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Today’s guest is Cibby Pulikkaseril, Founder & CTO at Baraja. In this episode we discuss Baraja’s approach to developing a truly solid state LiDAR, the pathway to building sensors that are cheaper and smaller for mass market adoption, and the company’s go to market strategy over the next few years.
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Today’s guest is Tom Jellicoe, Head of Autonomous Technologies at TTP. In this episode we discuss the various approaches to LiDAR seen in the marketplace, a few companies to watch in today’s competitive landscape, and where Tom sees LiDAR technology going in the future.
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Today’s guest is Bill Grabowski, Head of North America at ADASKY. In this episode we discuss the merits of thermal imaging cameras, the reasons why they haven’t been widely adopted to date, and ADASKY’s approach to bringing thermal cameras to the ADAS and AV markets.
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Today’s guest is John Xin, Co-founder & CEO at Lunewave. In this episode we discuss the entrepreneurial journey and what it’s like to start a company in the AV industry, the pros and cons of various business models within the automotive supplier ecosystem, and how radar fits into the ADAS and AV perception stack.
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Today’s guest is Sunny Lee, COO at StradVision. In this episode we discuss the pros and cons of deep learning based vision software for ADAS and AVs, how a company’s decision to use LiDAR has more to do with their business model than their perception stack, and what it’s like being COO at a growth stage AV company.
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Today’s guest is Mahmoud Saadat, Co-founder and CEO at Zadar Labs. Before Zadar, Mahmoud earned his PhD in Electrical Engineering from Stanford and developed custom hardware solutions for AVs at Lyft, Zoox and Apple. In this episode we discuss common perception approaches across the industry, the benefits of using imaging radar in the perception stack, and what it has been like as a first time founder starting a company in the AV space.
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Today’s guest is Jianxiong Xiao, Founder and CEO at AutoX. Professor X holds a PhD in Computer Science from MIT and was the founding director of the Princeton Computer Vision and Robotics Lab. In this episode we discuss how the AV landscape in the Chinese market differs from Silicon Valley, the pros and cons of different AV business models, and the technological complexity of creating fully hardware/software integrated vehicles for commercial use.
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Today’s guest is Yaser Khalighi, Founder and CEO at Caliber Data Labs. Yaser is a technologist and entrepreneur who holds a Ph.D. in mechanical engineering from Stanford. In this episode we discuss the “needle in a haystack” problem engineers face when developing machine learning models for AVs, and how Caliber helps them cut through the noise to find the most valuable data for training specific scenarios.
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Today’s guest is Chris Heiser, Co-founder and CEO of Renovo. In this episode we discuss the challenges and opportunities associated with the massive datasets created by vehicles today, how this data can and will be commercialized in the coming years, and what this all means for software development in the automotive industry.
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