Wayve, a U.K.-based startup that's developing artificial intelligence (AI) that teaches cars to drive autonomously using reinforcement learning, simulation, and computer vision, has raised $20 million in a series A round of funding led by Palo Alto venture capital (VC) firm Eclipse Ventures, with participation from Balderton Capital, Compound Ventures, Fly Ventures, and First Minute Capital. Several notable angel investors also participated in the round, including Uber's chief scientist Zoubin Ghahramani and Pieter Abbeel, a UC Berkeley robotics professor and pioneer of deep reinforcement learning. Founded out of Cambridge, U.K., in 2017, Wayve's core premise is that the big breakthrough in self-driving cars will come from better AI brains rather than more sensors or "hand-coded" rules. The company said that it trains its autonomous driving system using simulated environments and then transfers that knowledge into the real world, where it emulates how humans adapt to conditions in real time. Wayve's systems learn from each safety driver intervention to understand why the driver had to intervene, bypassing HD maps, lidar, and other sensors that have become synonymous with the burgeoning autonomous vehicle movement.
Light cofounder and CEO Dave Grannan raised $121 million for his imaging platform on the promise of its value to robotics, drones, and, especially, self-driving vehicles.Courtesy of Light In February, Dave Grannan, cofounder and CEO of imaging startup Light, flew to Tokyo to meet SoftBank's Masayoshi Son for the first time since beginning conversations with the Japanese billionaire's venture-capital arm. After two more meetings, in Tokyo and Silicon Valley, Son agreed to lead a massive $121 million investment in Light, through his SoftBank Vision Fund. Leica Camera also joined the deal. A big reason that Light was able to attract so much funding is the promise of robots, drones and, especially, self-driving cars. Light uses complex algorithms to combine images from multiple camera modules into a single, high-quality image with depth.
Nvidia CEO Jen-Hsun Huang introducing the Nvidia Spot, a USD 49.95 microphone and speaker that will let owners use Google Assistant anywhere in a home, at the company's CES 2017 keynote (Photo by Ethan Miller/Getty Images) Nvidia continued to see demand for its graphics processors in the emerging world of artificial intelligence in its fourth quarter earnings reported Thursday. In its fourth quarter earnings release, the Santa Clara, Calif.-based company reported revenue of $2.17 billion, up 55% year over year, on earnings per share of $1.13, up 117% a year ago. Wall Street analysts estimated $2.11 billion in revenue on EPS of 83 cents. Traditionally, the company's processors have been mostly used to power the latest gaming graphics, but the chips have become popular to run AI software in the data center and autonomous vehicles. A specific branch of AI, called deep learning, is where Nvidia's processors particularly shine.
New drone footage has revealed the latest look of Tesla's Gigafactory located on Electric Avenue in Sparks, Nevada. Once completed in 2020, the factory is set to become one of the biggest buildings in the world, with a final size of 10 million square feet. With production underway at the Gigafactory, the company is churning out lithium ion battery cells by the masses in hopes to ultimately reduce the cost of sustainable energy. Tesla says the factory will be producing 35 gigawatt hours of batteries by 2018, which is crucial for the company in reaching its production target of 10,000 units per week in 2018 for its new Model 3 car. According to electrek, Tesla's goal is on target as Tesla co-founder Elon Musk said this month that the factory is already the biggest battery producing factory in the world.
StradVision has raised $16.6M in total. We talked with Junhwan Kim, its CEO. How would you describe StradVision in a single tweet? StradVision is a pioneer in deep learning-based vision processing technology, providing the software that will allow Advanced Driver-Assistance Aystems (ADAS) in autonomous vehicles to reach the next level of safety, and usher in the era of the fully autonomous vehicle. How did it all start and why?