The founder of a startup that helps cars drive themselves just became a billionaire — and he’s barely old enough to rent a car on his own.
Luminar Technologies CEO Austin Russell, 25, secured a hefty fortune after his company’s stock market debut this week. The Florida-based firm — which he founded when he was just 17 — makes so-called lidar scanners that use lasers to give autonomous cars a three-dimensional view of the road and what’s around them.
Luminar’s share price surged nearly 28 percent on its Thursday debut to close at $22.98, giving the company a market value of about $7.8 billion, the Wall Street Journal reported.
A 15-year-old Colorado high school student and young scientist who has used artificial intelligence and created apps to tackle contaminated drinking water, cyberbullying, opioid addiction and other social problems has been named Time Magazine’s first-ever “Kid of the Year.”
Gitanjali Rao, a sophomore at STEM School Highlands Ranch in suburban Denver who lives in the city of Lone Tree, was selected from more than 5,000 nominees in a process that culminated with a finalists’ committee of children, drinking water crisis in Flint, Michigan, inspired her work to develop a way to detect contaminants and send those results to a mobile phone, she said.
“I was like 10 when I told my parents that I wanted to research carbon nanotube sensor technology at the Denver Water quality research lab, and my mom was like, ” A what?” Rao told Jolie. She said that work ” is going to be in our generation’s hands pretty soon. So if no one else is gonna do it, I’m gonna do it.”
There is a renaissance occurring in the field of artificial intelligence. For some drawn-out specialists in the field, it isn’t excessively self-evident. Many are making against the advancements of Deep Learning is anyway an amazingly radical departure from classical methods.
Old style A.I. procedures has zeroed in generally on the legitimate premise of cognition, Deep Learning by contrast works in the territory of cognitive intuition. Deep learning frameworks display behavior that seems biological despite not being founded on biological material. It so happens that humankind has fortunately discovered Artificial Intuition as Deep Learning.
Artificial intuition is a simple term to misconstrue since it seems like artificial emotion and artificial empathy. In any case, it contrasts fundamentally. Scientists are dealing with artificial intuition so that machines can impersonate human behavior all the more precisely. Artificial intuition plans to distinguish a human’s perspective in real-time. Along these lines, for instance, chatbots, virtual assistants and care robots can react to people all the more appropriately in context. Artificial intuition is more similar to human intuition since it can quickly evaluate the totality of a situation, including subtle indicators of a specific activity.
Over the past decade or so, roboticists and computer scientists have tried to use reinforcement learning (RL) approaches to train robots to efficiently navigate their environment and complete a variety of basic tasks. Building affordable robots that can support and manage the exploratory controls associated with RL algorithms, however, has so far proved to be fairly challenging.
Researchers at Aalto University and Ote Robotics have recently created RealAnt, a low-cost, four-legged robot that can effectively be used to test and implement RL algorithms. The new robotics platform, presented in a paper pre-published on arXiv, is a minimalistic and affordable real-world version of the ‘Ant’ robot simulation environment, which is often used in RL research.
“The initial inspirations for our work were RL studies that successfully demonstrated learning to walk from scratch on ant-like quadruped and humanoid robot simulations,” Jussi Sainio, co-founder of Ote Robotics, told Tech Xplore. “The underlying premise with RL algorithms is that programming a robot to do tasks becomes much easier and more ‘natural’—one just needs to define the available sensor measurements, motor actions, then set a target goal and plug them all into a reinforcement learning algorithm, which figures out the rest.”
Remember when the idea of a robotic hand was a clunky mitt that could do little more than crush things in its iron grip? Well, such clichés should be banished for good based on some impressive work coming out of the WMG department at the U.K.’s University of Warwick.
If the research lives up to its potential, robot hands could pretty soon be every bit as nimble as their flesh-and-blood counterparts. And it’s all thanks to some impressive simulation-based training, new A.I. algorithms, and the Shadow Robot Dexterous Hand created by the U.K.-based Shadow Robot Company (which Digital Trends has covered in detail before.)
Researchers at WMG Warwick have developed algorithms that can imbue the Dexterous Hand with impressive manipulation capabilities, enabling two robot hands to throw objects to one another or spin a pen around between their fingers.
Google is betting big on artificial intelligence (AI), and it’s clearly paying off. Apart from offering up collections of code that best the world’s board game champions, they’ve also managed to create an AI that, in effect, designs its own AI – and its creations have gone from analyzing words to disseminating complex imagery in a matter of months.
On a company blog post from May of this year, engineers explain how their AutoML system (Automated Machine Learning) gets a controller AI – which we can perhaps call the “parent” in a colloquial sense – that proposes designs for what the team call a “child” AI architecture.
The child is then given a task, and feedback is sent to the parent. This allows the parent to improve how it designs a second child, and so on and so forth, thousands of times over. This self-reinforcing learning mechanism allows it to develop AI children that ultimately are better than anything human engineers can make.
Elon Musk’s Boring Company has released the first images teasing the first passenger station of the Las Vegas Loop ahead of its launch.
A Boring Company Loop system consists of tunnels in which Tesla autonomous electric vehicles travel at high speeds between stations to transport people within a city.
The first system is being deployed at the Las Vegas Convention Center (LVCVA), which is paying $50 million for the system, but we recently learned that the Boring Company plans to connect the convention center’s Loop to casinos on the strip in order to eventually create a city-wide Loop in Las Vegas.
