Waabi and Volvo announce partnership integrating Waabi Driver AI technology with Volvo VNL Autonomous trucks, marking major milestone in autonomous freight.

For many years, researchers have been working to build devices that can mimic photosynthesis--the process by which plants use sunlight and carbon dioxide to make their fuel. These artificial leaves use sunlight to separate water into oxygen and hydrogen, which could then be used to fuel cars or generate electricity. Now a research team from the University of Cambridge has taken aim at creating more energy-dense fuels. The group's device produces ethylene and ethane, proving that artificial leaves can create hydrocarbons. The development could offer a cheaper, cleaner way to make fuels, chemicals, and plastics--with the ultimate goal of creating fuels that don't leave a harmful carbon footprint after they're burned.

"It brings accountability to the industry," says Raquel Urtasun, Waabi's firebrand founder and CEO (who is also a professor at the University of Toronto). "There are no more excuses." After quitting Uber, where she led the ride-sharing firm's driverless-car division, Urtasun founded Waabi in 2021 with a different vision for how autonomous vehicles should be made. The firm, which has partnerships with Uber Freight and Volvo, has been running real trucks on real roads in Texas since 2023, but it carries out the majority of its development inside a simulation called Waabi World. Waabi is now taking its sim-first approach to the next level, using Waabi World not only to train and test its driving models but to prove their real-world safety.

While autonomous driving has long relied on machine learning to plan routes and detect objects, some companies and researchers are now betting that generative AI -- models that take in data of their surroundings and generate predictions -- will help bring autonomy to the next stage. Wayve, a Waabi competitor, released a comparable model last year that is trained on the video that its vehicles collect. Waabi's model works in a similar way to image or video generators like OpenAI's DALL-E and Sora. It takes point clouds of lidar data, which visualize a 3D map of the car's surroundings, and breaks them into chunks, similar to how image generators break photos into pixels. Based on its training data, Copilot4D then predicts how all points of lidar data will move.

Imagine if it were possible to produce infinite amounts of the world's most valuable resource, cheaply and quickly. What dramatic economic transformations and opportunities would result? This is a reality today. It is called synthetic data. Synthetic data is not a new idea, but it is now approaching a critical inflection point in terms of real-world impact. It is poised to upend the entire value chain and technology stack for artificial intelligence, with immense economic implications. Data is the lifeblood of modern artificial intelligence. Getting the right data is both the most important and the most challenging part of building powerful AI.

The self-driving era is here, just not the one that was promised. Instead of sleek pods without steering wheels ready to chauffeur buyers off the lot, there are mostly driverless Chevy compacts, Chrysler minivans, and Ford box trucks with bolted-on hardware trundling around bits of the U.S. southwest and, as of August, a short loop of roads in Ontario. But while the current reality has fallen far short of automaker predictions, it's worth stopping to acknowledge that there are trucks driving around public Canadian roads making deliveries, without a soul inside. The technological achievement of the feat has huge implications for business, and society, but the latest industry outlook, humbled by past failures, points to a more gradual rollout. "People think there will be a magic day where suddenly everything will be autonomous, but that's not how this is going to work," said Raquel Urtasun, a leading artificial intelligence researcher and chief executive of Toronto-based autonomous outfit Waabi Innovation Inc. "You will have certain areas where this technology is going to deploy, and then those areas will expand under more and more difficult situations."

If you are interested in the self-driving car market, you may know Waabi. This startup, founded by Raquel Urtasun, former Chief Scientist of Uber's Advanced Technology Groupcreated a surprise in June 2021 by raising no less than $83.5 million. Among the supporters of the young company, we find big names like Uber, Aurora Innovation, Radical Ventures, 8VC and OMERS Ventures. The founder of Waabi is a artificial intelligence specialist who once led the autonomous vehicle division of the famous ride-hailing company. And after this highlighting, the startup has just announced this Wednesday, November 16, 2022 the launch of a new "turnkey" solution for semi-trailer manufacturers who wish to make their fleet autonomous.

These people do not exist. These faces were artificially generated using a form of deep learning ... [ ] known as generative adversarial networks (GANs). Synthetic data like this is becoming increasingly indistinguishable from real-world data. Imagine if it were possible to produce infinite amounts of the world's most valuable resource, cheaply and quickly. What dramatic economic transformations and opportunities would result? This is a reality today. It is called synthetic data. Synthetic data is not a new idea, but it is now approaching a critical inflection point in terms of real-world impact.

Raquel Urtasun founded Waabi in 2021 after spending nearly three years as Uber's R&D head of Advanced Technology Group (ATG). Waabi's mission is to develop an AI-first approach to speed up the commercial deployment of autonomous vehicles, starting with long-haul trucks. To do so, her company raised an $83.5 million Series A with Khosla Venture's Sven Strohband leading the round. Both will speak to Urtasun's unique (and commanding) perspective, and what allowed the company to raise the massive Series A. This event opens on May 11 at 11:30 am PT / 2:30 pm ET with networking and pitch practice submissions. The interview begins at 12 pm PT followed by the TCL Pitch Practice at 12:30 pm PT.

Testing autonomous vehicles on public roads is an expensive and time-consuming endeavor, and one that Raquel Urtasun, former chief scientist at Uber ATG, doesn't think is the most expedient route to market. Waabi, Urtasun's self-driving truck technology startup that launched last June, has come out with a key component of its strategy to scale its tech – Waabi World, a high-fidelity closed-loop simulator that doesn't just virtually test Waabi's self-driving software, but also teaches it in real time.