Joe Speed

With Tesla’s Robotaxi launch now official, are we witnessing another leap in autonomous mobility or is this about generating alternative headlines? As many of you saw in my Waymo post this rapid rise in robotaxis use (27% market share in San Francisco), highlights that it is not just about technology, it is a system design challenge. Autonomous ride-hailing brings clear benefits: increased safety, lower operating costs, and greater accessibility. But robotaxis alone will not solve congestion or urban mobility challenges. If unmanaged, they could make things worse. More vehicles circulating and more fragmented trips could drive up traffic volumes rather than reduce them. This is why investment and policy must prioritise strengthening public transport first. High-capacity, efficient transit delivers far greater societal benefits, moving more people with less congestion, lower emissions, and at lower cost. Autonomous services should complement, not compete with, public transport. Without this focus, robotaxis risk widening mobility divides and adding to congestion. Policy and urban design will be critical: dynamic road pricing, incentives for pooled rides, regulation of empty vehicle running, and better integration with public transit. We must also ask hard questions about jobs, equity, and the best use of public and private investment. Tesla’s vision-only approach is a bold contrast to sensor-rich models like Waymo’s. Time will tell if this enables scale or introduces new risks. As with all breakthrough technologies, robotaxis are neither inherently good nor bad. It depends on how we integrate them into a broader transport ecosystem. The future of mobility must be a thoughtful blend of public transport, active mobility, shared services, and emerging technologies, designed to serve all in society, not just those who can afford it. #TeslaRobotaxi #AutonomousVehicles #UrbanMobility #SmartCities #FutureOfTransport

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At CES 2026, we spoke with Kai Stepper, VP of ADAS and Autonomous Driving at Lucid, about their production-intent robotaxi built on the NVIDIA DRIVE Hyperion platform. He also shared why Alpamayo’s open, reasoning-based approach is an important step forward for the future of autonomous driving.

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Pump out and re-pasting thermal interfaces is unacceptable in the new GPU depreciation economics. OEMs and end users adopting Carbice Pad as their critical thermal interface (TIM) are showing signs already of being able to exceed the 6-year "value cascade" driving competitive value in their balance sheet and business. https://lnkd.in/eumyDepY

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https://lnkd.in/gNwAuW8P Safe and scalable software-defined vehicle (#SDV) architectures rely on advanced software and networking solutions to enable #realtime data communication and deterministic behavior in modern #automotive systems. As the industry moves toward #automation and #electrification, key technologies such as time-sensitive #networking (TSN) and deterministic scheduling play a crucial role in ensuring reliable, high-performance vehicle operation. In an interview with Embedded.com, Dr. Stefan Poledna, CTO and co-founder of TTTech Auto, offered insights into the company’s technologies and its role in SDV development.

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InnovizSMARTer which now includes Nvidia AI chips are enabling different ways to expand Innoviz Technologies LiDAR use in different applications, especially now through cloud based solutions. By integrating our automotive-grade sensors with Vueron's powerful AI development tools, we're enabling our customers to accelerate their development timelines and potentially reduce the complexity of bringing perception systems to market. Veuron® are now working to use this new capability and develop a world of applications through the cloud https://lnkd.in/dH29Zud5

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