Softbank, Microsoft, Nvidia and a $1 Billion Autonomous Investment
Last week, Wayve, a UK based startup, secured over $1 billion in series C funding from Softbank, Microsoft, Nvidia and others to develop artificial intelligence technologies that help autonomous vehicles "navigate situations that do not follow strict patterns or rules, such as unexpected actions by drivers, pedestrians, or environmental elements."
Wayve CEO Alex Kendall said "This will enable automakers and fleets to accelerate their transition from assisted to autonomous driving,"
Wayve President Erez Dagan said their technology is "built to generalize its driving knowledge from one scenario to another... because it's nearly impossible to imagine every situation that a self-driving car needs to reliably handle."
Comments from the recent company blog post “The Road to Embodied AI” includes:
“AI often centers around Cognitive AI, like large language models. They are an amazing breakthrough and will have a huge impact on our lives. But they are still limited by the domain they act within — words, data, and knowledge, an abstracted reality. The reality we live in is the physical world, and this is where our most significant interactions take place. This is what Embodied AI enables, bringing the extraordinary impact of AI to the physical world.
“we are creating Embodied AI technology that will enable applications like autonomous vehicles to enhance our daily lives by safely coexisting with humanity and allowing people to concentrate on what truly matters.
"Our technology excels where others have struggled: mastering driving in complex urban environments with camera-only navigation and adapting to cities unseen during training just like how you and I drive. Such achievements require a willingness to disrupt legacy thinking and try brave new solutions."
Note: Wayve's technology is currently integrated into vehicles such as the Jaguar I-PACE and Ford Mustang MachE.
OUR TAKE
Autonomous vehicles require “cross-functional” integration among technologies such as AI, sensors, mapping, and on-board computing - and “Embodied AI” has the opportunity to be critical parts of this ecosystem.
As embodied AI based systems demonstrate their ability to understand, learn, and provided context to phyiscal environments, their use should see significant growth as they evolve from “deep tech” to commercialization.
Continuing advances in autonomous vehicles should improve their reliability, unit economics, manufacturing dynamics and consumer acceptance that can also benefit other robotic markets.