Long-range 4D imaging radar on a chip unveiled

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Developer of affordable imaging radars for the automotive industry, RFISee is unveiling the first Phased Array 4D imaging radar on a chip. RFISee’s all weather radar has proven its ability to detect cars from 500 meters and pedestrians from 200 meters, with an angular resolution greater than 1°.

The company’s engineers have adapted Phased Array antenna technology, used in military systems including the F-35 fighter jet and in air defence systems, while at the same time reducing the price to the current level of automotive sensors. Prototypes of RFISee’s radar are under evaluation by top automotive OEMs and Tier-1s.

Unlike many traditional and new types of radar, RFISee’s patented 4D imaging radar uses a powerful focused beam based on proprietary Phased Array radar technology. The focused beam created by dozens of transmitters rapidly scans the field of view. The receivers ensure a much-improved radar image, a better signal to noise ratio, and a detection range of obstacles such as cars and pedestrians that is six times broader when compared to existing radars. The competitive edge of RFISee’s radar prototype has already been proven in extensive testing.

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Helm.ai pioneers breakthrough…. “Deep Teaching” of neural networks

 

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Helm.ai today announced a breakthrough in unsupervised learning technology. This new methodology, called Deep Teaching, enables Helm.ai to train neural networks without human annotation or simulation for the purpose of advancing AI systems. Deep Teaching offers far-reaching implications for the future of computer vision and autonomous driving, as well as industries including aviation, robotics, manufacturing and even retail.

Artificial intelligence, or AI, is commonly understood as the science of simulating human intelligence processed by machines. Supervised learning refers to the process of training neural networks to perform certain tasks using training examples, typically provided by a human annotator or synthetic simulator to machines to perform certain tasks, while unsupervised learning is the process of enabling AI systems to learn from unlabelled information, infer inputs and produce solutions without the assistance of pre-established input and output patterns.

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Exploring the three elephants in the autonomous vehicle room

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The expression “elephant in the room” refers to an important question that everyone knows about but no one wants to discuss because it makes them uncomfortable.

Today, in the area of Autonomous Vehicles (AVs), there are three elephants in the room which are worth exploring.

Let’s get started.

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World’s first fully self-driving car will be ready this year, Elon Musk claims

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Tesla’s Autopilot software, which relies on various cameras and sensors to operate, can be updated remotely.

‘I’m very confident about full self-driving functionality being complete by the end of this year,’ he says. ‘It’s because I’m literally driving it’

Tesla CEO Elon Musk has said the electric car maker will have fully self-driving vehicles on the road by the end of the year.

During an earnings call with investors on Wednesday, the serial entrepreneur revealed that he is already testing an updated version of the firm’s Autopilot software on his commute to work in Los Angeles.

“It’s almost getting to a point where I can go from my house to work with no interventions, despite going through construction and widely varying situations,” he said.

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The ‘android of self-driving cars’ built a 100,000x cheaper way to train AI for multiple trillion-dollar markets

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Level 5 self-driving means autonomous cars can drive themselves anywhere, at any time, in any conditions.

How do you beat Tesla, Google, Uber and the entire multi-trillion dollar automotive industry with massive brands like Toyota, General Motors, and Volkswagen to a full self-driving car? Just maybe, by finding a way to train your AI systems that is 100,000 times cheaper.

It’s called Deep Teaching.

Perhaps not surprisingly, it works by taking human effort out of the equation.

And Helm.ai says it’s the key to unlocking autonomous driving. Including cars driving themselves on roads they’ve never seen … using just one camera.

Continue reading… “The ‘android of self-driving cars’ built a 100,000x cheaper way to train AI for multiple trillion-dollar markets”

Tesla (TSLA): Elon Musk says ‘very close’ to level 5 autonomy complete

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Tesla (TSLA): Basic functionality for level 5 autonomy is complete this year, says CEO Elon Musk.

Today, Musk virtually attended the World Artificial Intelligence Conference (WAIC) in Shanghai and participated in a Q&A session.

Musk oversees several projects involving AI, but the most prominent one is Tesla’s effort to deliver a full self-driving level 5 system.

At the conference, Musk briefly discussed Tesla’s effort to reach full self-driving and showed great confidence in delivering such a system soon:

I am extremely confident that level or essentially complete autonomy will happen, and I think will happen very quickly. I think at Tesla, I feel like we are very close to level 5 autonomy.

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NEVS unveils autonomous electric shuttle for urban use

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NEVS Sango autonomous electric shuttle, image credit: NEVS

Way last century, Sweden had two global auto manufacturers — Volvo and Saab. Volvo built staid cars that were as solid as the rock of Gibraltar. Saab was the quirky cousin that insisted on mounting its ignition switch in the center console rather than on the dashboard. It also offered styling that was trés avant. If you wanted safety in your Swedish car, you bought a Volvo. If you wanted a little dash of excitement, you bought a Saab.

Both companies got caught up in a game of “mine’s bigger than yours” that played out between Ford and General Motors at the end of the last century. Ford started things off by buying Jaguar and Land Rover as it put together what it called its Premium Auto Group. Then it bought Volvo in 1999. Not to be outdone, General Motors then purchased Saab. Less than 10 years later, both once proud Swedish manufacturers were toast and teetering on the edge of bankruptcy as the Great White Fathers in Detroit bled both companies dry.

Volvo was rescued by Geely but Saab slowly sank between the waves. Its car manufacturing assets were purchased out of bankruptcy by a new corporation somewhat grandly known as National Electric Vehicle Sweden, which set about converting the last generation Saab 9-3 to electric power. In 2015, the company signed a strategic collaboration agreement with Panda New Energy Company of China to deliver 150,000 9-3 electric vehicles by the end of 2020.

Evergrande Group of China acquired 51% of the shares in NEVS in January 2019. Evergrande has since then increased its holdings to 68%. National Energy Holding, owned by Kai Johan Jiang, owns the remaining shares. The company is still peddling the converted 9-3 battery electric car to a largely uninterested audience.

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Didi Chuxing: Apple-backed firm aims for one million robotaxis

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Chinese ride-hailing firm Didi Chuxing says it plans to operate more than a million self-driving vehicles by 2030.

The robotaxis are to be deployed in places where ride-hailing drivers are less available, according to Meng Xing, Didi’s chief operating officer.

Mr Meng was speaking at an online conference hosted by the Hong Kong-based South China Morning Post newspaper.

One analyst suggested it was a very ambitious aim.

“I’ll be surprised if we see a million by 2030,” a spokesman for market research firm Canalys said.

“I hope that happens but there’s a lot to take place in meantime.”

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Chinese automaker plans satellite network to support autonomous vehicles

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Geely’s constellation will provide connectivity to its next-gen autos.

 One of the most important components in an autonomous vehicle is its communications technology—which allows it to access the data needed to navigate its route. Chinese automobile company Geely has developed a solution to maintain a reliable data feed for its products: making its own satellite constellation.

The giant automaker—which sold 2.18 million vehicles in 2019 and also owns Volvo and a stake in Daimler-Benz—is investing $326 million in a new satellite manufacturing plant in Taizhou, close to its existing assembly lines. The plant will manufacture 500 satellites a year by 2025—with its first launches scheduled for later this year—and will have the capability of producing different satellite models. It will feature modular satellite manufacturing lines, research and testing centers and a cloud computing facility. The facility will be the first private satellite factory in China.

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Chinese ride-hailing giant Didi Chuxing launches pilot self-driving robotaxi service in Shanghai

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Didi has raised US$500 million from Japan’s SoftBank for its autonomous driving subsidiary.

 Didi’s launch of robotaxis in Shanghai comes just days after it announced plans to deploy more than one million self-driving vehicles through its platform by 2030

Globally, the market is projected to be worth US$65.3 billion by 2027, according to a report from Market Research Future

Commuters in Shanghai can now book self-driving taxis through Didi Chuxing after the Chinese ride-hailing giant launched its on-demand robotaxi service on the weekend.

Using the new app, passengers can take free rides in autonomous vehicles within designated open-traffic areas in Shanghai’s Jiading District as part of the pilot phase of the project.

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U.S. will unveil data-sharing platform for autonomous vehicle testing

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(Reuters) — On Monday, U.S. auto safety regulators will unveil a voluntary effort to collect and make available nationwide data on existing autonomous vehicle testing.

 U.S. states have a variety of regulations governing self-driving testing and data disclosure, and there is currently no centralized listing of all automated vehicle testing.

California, for example, requires public disclosure of all crashes involving self-driving vehicles, while other states do not.

The National Highway Traffic Safety Administration (NHTSA) is unveiling the Automated Vehicle Transparency and Engagement for Safe Testing (AV TEST) initiative to provide “an online, public-facing platform for sharing automated driving system on-road testing activities.”

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Autonomous car makers dispute insurance study’s low estimate of crashes

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Companies working on self-driving vehicles have criticized an insurance industry study suggesting that only a third of all U.S. road crashes could be prevented by driverless cars, arguing that the study has underestimated the technology’s capabilities.

The study by the Insurance Institute for Highway Safety (IIHS), released on Thursday, analyzed 5,000 U.S. crashes and concluded that likely only those caused by driver perception errors and incapacitation could be prevented by self-driving cars.

The autonomous vehicle industry quickly responded that its cars were programmed to prevent a vastly higher number of potential crash causes, including more complex errors caused by drivers making inadequate or incorrect evasive maneuvers.

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