Videantis, which provides automotive deep learning, computer vision and video coding solutions, has announced that it will partner with the Fraunhofer Institute for Integrated Circuits IIS, Infineon and other leading companies and universities to develop an artificial intelligence (AI) ASIC and software development tools specifically for intelligent autonomous vehicles. The Videantis AI multi-core processor platform and tool flow has been selected for the KI-Flex autonomous driving chip project. Autonomous driving relies on fast and reliable processing and merging of data from several lidar, camera and radar sensors in the vehicle. This data can provide an accurate picture of the traffic conditions and environment to allow the vehicle to make intelligent decisions when driving. The process of intelligently analysing these volumes of sensor data requires high-performance, efficient, and versatile compute solutions.
John McCarthy was the son of a penniless Irish immigrant from Kerry and maybe the most important Irish American you never heard of. He died in 2011 aged 84. He was an American computer scientist pioneer and inventor and is known as the father of artificial intelligence (AI) after playing the key role in the development of intelligent machines we now call computers. He won the Turing Prize, one step below the Nobel, in 1971. He coined the term artificial intelligence for a 1955 Dartmouth College conference he chiefly organized which was the first-ever AI conference.
The companies racing to deploy autonomous cars on the world's roads took a reality check in the 2010s, but multimillion-dollar development efforts remain ongoing across the automotive and tech industries. German supplier Bosch is notably moving full speed ahead with its quest to make driverless cars a reality. Kay Stepper, Bosch's senior vice president of automated driving, sat down with Digital Trends to talk about the state of autonomous driving in 2020, and what's next for the artificial intelligence technology that powers the prototypes it's testing. Bosch has never made a car, so it brings its innovations to the market through partnerships with automakers. It chose Mercedes-Benz parent company Daimler to test autonomous technology in real-world conditions via a ridesharing pilot program in San Jose, California, close to one of the company's research centers.
AI varies from industry to industry. There are just as many use cases for AI as there are companies. For healthcare organizations, AI is playing a role in monitoring equipment, while retailers see AI as a way to better understand customers. Transportation executives are banking on AI to drive autonomous vehicles. The common denominator across all industry groups is the rate that AI is changing the way things get done.
The Genesis GV80 luxury SUV has a lot riding on its broad shoulders. The BMW X5 and Mercedes-Benz GLE rival carries the future of Hyundai's fledgling luxury offshoot in Australia and beyond. Expected to arrive locally mid-year, it joins the new Genesis G70 and G80 sedan duo to fill an important void for Hyundai's luxury brand. Its bold exterior design cues, including a bluff grille, 22-inch wheels and split LED lights will appear on its more conservative four-door cousins in the near future. The interior brings a choice of five or seven seats in the South Korean home market, along with a whopping 14.5-inch digital display stacked with technology to rival Europe's best.
For VA/VE exercises we generate ideas in very high numbers using our proprietary Machine Learning model. Our ML model is trained after processing teardown BOM generated for 26 Vehicles where the no. of parts range from 1000-6000 per vehicle and from almost all category of vehicles (2W, 4W, 3W & Commercial Vehicles). Based on our past experiences with multiple value engineering workshops, the quality of ideas have been refined such that the model generates good quality ideas that be rejected in the basic feasibility check.
An artificial intelligence system that allows self-driving cars to'see' around corners in real time could help prevent accidents, according to its developers. Researchers from Stanford University in the USA have created a system that bounces a laser beam off a wall to create an'image' of objects hidden from view. The'image' captured won't make sense to a human, but using artificial intelligence technology the system can create a visual reconstruction of the hidden view. The research was funded by US government agency DARPA (Defence Advanced Research Projects Agency), and is one of a number of similar technology programmes being developed. It could also be used by soldiers to see around walls, rescue workers searching for people and even in space travel to examine the interior caves of an asteroid.
"Ambarella is an artificial intelligence ("AI") company," says the first line in a recent Ambarella (AMBA) investor presentation to Morgan Stanley. More than four and a half years ago, we wrote about how Ambarella was seeing very strong revenue growth selling semiconductor processing solutions for video in four primary segments: camera-based advanced driver assistance systems (ADAS), wearable cameras like GoPro, cameras for drones, and home automation cameras. Since that article, shares of Ambarella have fallen -50% compared to a NASDAQ return of 73% over the same time frame. Fortunately, the company is being forthcoming with investors as to why the company's stock has performed so poorly. We had previously remarked how a lack of transparency into the company's financials prevented investors from seeing which of these areas were contributing to all that strong revenue growth.
Researchers at US universities have created an imaging system powered by artificial intelligence that could help self-driving cars "see" around corners in minute detail to identify hazards. The imaging system uses a conventional camera sensor and a laser beam that can be "bounced" off walls and onto objects to create a pattern – visually similar to the static on an old untuned television to the naked eye. The image is then reconstructed by an AI algorithm, eliminating the'noise' and able to produce images of even 1cm tall letters. Deep-learning is a form of artificial intelligence that mimics the working of the human brain to process data and create patterns. It is a particularly powerful subset of machine learning AI, able to learn unsupervised with unstructured data.
Tesla's customers are also test drivers amassing an unprecedented dataset that the company hopes to use to design its self-driving cars. And it hopes to do this before other car companies test their own self-driving technology with paying customers. So far, the strategy seems to be working. Sterling Anderson, director of Tesla's Autopilot program, told MIT Technology Review's EmTech Digital conference this week that the company had recorded data from Tesla drivers who covered 780 million miles in the last 18 months. The company's Autopilot program, launched in 2014, is not fully autonomous, but it uses a suite of ultrasonic sensors, radar and cameras to steer, change lanes and avoid collisions, and has been described as the predecessor to the full automation Tesla says it will release in 2018.