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Wayve rewrites self-driving playbook with deep studying in Azure


LONDON – On a more than typically busy Thursday morning in Soho, the gray December sky spat rain. Traffic was stop-and-go, but mainly stop. Even the sidewalks were congested.

Finally, alongside the imposing British Museum, the flow of cars and trucks regained some momentum. Inside a four-door EV sedan that was driving itself, a safety operator sat passively but alertly behind the wheel, hands resting palm up on his thighs. The car glided forward without any assistance from him, en route to Trafalgar Square.

A few moments later, a harried man stepped into our path from behind a parked car. The AI-guided sedan braked firmly to a halt, giving the four passengers inside a gentle shake; the heedless pedestrian crossed the street without looking back. The safety operator had not touched the pedals; this car was acting independently.

Self-driving cars, powered by AI, roll through a number of big city streets these days, but the company behind our ride, Wayvetook a different route when it was founded in Cambridge, U.K., in 2017.

In essence, Wayve has built an AI-powered driver who could potentially be installed in any new car, no matter the make or model, and drive it, in any country or city, with just a couple weeks of fine-tuning. This approach relies on a form of AI model inspired by the human brain known as a “neural net.” Wayve’s AI Driver mainly uses cameras to safely navigate from point to point.



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