Autonomous Vehicles

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Shield AI, Waabi, and General Motors on Building AI When Failure Is Not an Option at TechCrunch Disrupt 2026

Shield AI CTO Nathan Michael, Waabi CEO Raquel Urtasun and GM robotics strategy director Mikell Taylor share the Real World AI Stage at TechCrunch Disrupt 2026 (13-15 October, Moscone West) for “Building AI Systems When Failure Is Not an Option”. This article covers the session, each company’s record on validation, RAND’s miles-to-safety arithmetic, the standards behind a release decision and the questions founders should ask about safety-critical AI.

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gatik live tracking videos autonomous truck operations a box delivery truck side

Gatik Launches Live Tracking and Videos for Autonomous Truck Operations

Gatik has rebuilt gatik.ai around a live operations board that lists every driverless trip in a rolling twenty-four hour window — truck label, start and end times, driving hours, stop progress and status — refreshed every three hours, with the old marketing site moved wholesale to an archive domain. This breakdown reads one complete snapshot of the feed: 132 trips, 265.2 hours of driving, 607 stops, 475 published legs covering 4,846 miles, and exactly one row flagged delayed. It also covers what the board deliberately withholds — no customer names, no coordinates, no route geometry, no vehicle identities — how that compares with Waymo’s safety hub and NHTSA’s crash reporting, and what publishing an operational number you cannot retract actually costs the company that tries it.

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Heterogeneous Computing and AI Integration in Clusters

Unleashing the Power of Diversity: Heterogeneous Computing and AI Integration in Clusters

In the ever-evolving landscape of computing, the integration of heterogeneous technologies has emerged as a powerful strategy to optimize performance for specific workloads. The marriage of CPUs, GPUs, and FPGAs in cluster configurations has become a cornerstone in the realm of high-performance computing (HPC). Concurrently, the integration of machine learning (ML) and artificial intelligence (AI) into cluster servers has fueled groundbreaking advancements across various industries. In this article, we delve into the symbiotic relationship between heterogeneous computing and machine learning integration, exploring how this convergence is shaping the future of scientific simulations, AI applications, and beyond.

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