"At one point a blue car (with a human at the wheel) sticks its nose into the stream of traffic just ahead of us. Urban drivers know this can go two ways: Hesitate and it’s a cue for the other car to pull out; push ahead and you’re telling it to wait its turn. Wayve’s car pushes ahead." Will Douglas Heaven discussed his experience riding with Wayve for MIT Technology Review. A data-learned, end-to-end AI Driver creates a more human-like driving experience, instead of a prescribed one. In this article, he chats with Wayve's VP of Software Silvius Rus and looks at why our expansion to the US is significant to delivering EmbodiedAI at scale.
🇺🇸Hello Bay Area 👋🚨We’re growing!🏢 🚘 We are expanding our presence in the US with a new office and launching on-road testing in the Bay Area. We are developing AI software for assisted and automated driving that works globally. This expansion marks the first on-road testing of our technology outside the UK and is an important milestone in our growth strategy.
"We know that OEMs don't deploy their vehicles in just one market or one city, they deploy these vehicle platforms globally. So we think about scalability as inherent to how we develop our technology." In this episode of Conversations in the Park podcast, Wayve's VP of Commercial and Fleet, Kaity Fischer, joins Timothy Papandreou to deep dive the AV industry and the challenges when commercializing this technology. Listen here: https://lnkd.in/exGJ9fB8
The UK has a strong opportunity to lead in Embodied AI, especially in automated vehicles. Today, Wayve's CEO Alex Kendall will be speaking at the International Investment Summit to share his views on the opportunity Embodied AI offers us and how the government can support founders to scale their business and technology globally. 🔉Tune into BBC Radio 4 from 1PM to catch up with Alex on his takeaways so far.
🚲 London is a cycling city - and no two cyclists are the same! The line between what classifies as a bike vs. something else is often blurred. Instead of prescribing labels to these road users (like traditional rules-based automated driving systems) we take a learned approach. Through our AV2.0 approach, our AI learns a representation of cyclists, and how to safely navigate around them, whatever shape or size.
