Apple Executive Reveals More of Its Self-Driving Technology

A theme emerged when Apple’s director of artificial intelligence research outlined results from several of the company’s recent AI projects on the sidelines of a major conference Friday. Each involved giving software capabilities needed for self-driving cars.

Ruslan Salakhutdinov addressed roughly 200 AI experts who had signed up for a free lunch and peek at how Apple uses machine learning, a technique for analyzing large stockpiles of data. He discussed projects using data from cameras and other sensors to spot cars and pedestrians on urban streets, navigate in unfamiliar spaces, and build detailed 3-D maps of cities.

The talk offered new insight into Apple’s secretive efforts around autonomous-vehicle technology. Apple received a permit from the California DMV to test self-driving vehicles in April, and CEO Tim Cook confirmed his interest in such technology in June.

The scale and scope of any car project at Apple remains unclear. Salakhutdinov didn’t say how the projects he discussed Friday fit into any wider effort in automated driving, and a company spokesman declined to elaborate.

Salakhutdinov showed data from one project previously disclosed in a research paper posted online last month. It trained software to identify pedestrians and cyclists using 3-D scanners called lidars used on most autonomous vehicles.

Other projects Salakhutdinov discussed don’t appear to have been previously disclosed. One created software that identifies cars, pedestrians, and the driveable parts of the road in images from a camera or multiple cameras mounted on a vehicle.

Salakhutdinov showed images demonstrating how the system performed well even when raindrops spattered the lens, and could infer the position of pedestrians on the sidewalk when they were partially screened by parked cars. He cited that last result as an example of recent improvements in machine learning for some tasks. “If you asked me five years ago, I would be very skeptical of saying ‘Yes you could do that,’” he said.

Another project Salakhutdinov discussed involved giving software moving through the world a kind of sense of direction, a technique called SLAM, for simultaneous localization and mapping. SLAM is used on robots and autonomous vehicles, and also has applications in map building and augmented reality. A fourth project used data collected by sensor-laden cars to generate rich 3-D maps with features like traffic lights and road markings. Most prototype autonomous vehicles need detailed digital maps in order to operate. Salakhutdinov also mentioned work on making decisions in dynamic situations, a topic illustrated on his slides with a diagram of a car plotting a path around a pedestrian.

Apple’s event took place toward the end of a week-long conference on machine learning called NIPS. Nearly 8,000 people attended, an increase of almost five times since 2012. There was a strong showing from recruiters—including Elon Musk—hoping to lure machine learning engineers, highly prized employees in short supply.

The AI talent shortage was a primary reason for Apple’s event Friday, which attracted people from top universities such as MIT and Stanford, and companies including Alphabet and Facebook. It also included talks from engineers about how machine learning is used inside Apple products such as the Siri personal assistant. Carlos Guestrin, Apple’s director of machine learning, and a professor at University of Washington, spoke about the powerful computer systems and large datasets available to machine-learning engineers who join the company. He won applause by announcing that Apple is open sourcing software to help app developers use machine learning first developed at his startup Turi, acquired by Apple last summer.

Friday’s event, and Salakhutdinov’s discussion of research results, show how Apple is being forced to relax its famed secrecy as it competes for talent with rivals such as Google. Salakhutdinov joined Apple in October 2016, although he retains a professorship at Carnegie Mellon University. Soon after, at last year’s NIPS conference, he announced that his researchers would be able to publish academic papers, like their counterparts at Facebook and Google. It was a seen as a savvy concession to the academic bent of AI experts even inside industry.

Apple’s AI thaw has proceeded slowly, though. A company spokesman pointed to five academic machine learning papers released since Salakhutdinov joined the company, but said that Apple doesn’t maintain a count of such publications. The company has also started sharing some of its work on a technical blog branded as the Apple Machine Learning Journal. By contrast, Alphabet’s AI research groups contributed to more than 60 accepted papers at NIPS this week alone. To keep pace, or get ahead, of competitors in AI, Apple may need to share more with them.

Yandex, the ‘Google of Russia,’ is now testing self-driving cars in the snow

Hot off its joint venture with Uber, Russian tech giant Yandex is testing its cold-weather capabilities. The company often known as the Google of Russia is exploring many different industries and technologies, including that of the self-driving variety. And now that it’s forming a joint venture with Uber, it’s stepping up its autonomous capabilities even further. Over the November 25-26 weekend, Yandex conducted test drives with its self-driving taxis in a snowy scenario, ensuring that the autonomous vehicle would be able to keep passengers safe in wintry conditions. In total, the Prius prototypes traveled a total of 300 km during the test.

“We have been working to prepare algorithms for winter ‘at garage’ for a while, so last weekend tests in real world was just the first time we got all confirmations,” Dmitry Polishchuk, head of Yandex.Taxi’s self-driving project, told TechCrunch. Yandex certainly isn’t the first company to test its autonomous abilities in the snow. Just last month, Alphabet-owned Waymo announced that it was testing its own Chrysler Pacific hybrid minivans in snowy and icy conditions in Detroit.

The reason behind such tests is simple — while self-driving vehicles know what to do in ideal road conditions, understanding how to adapt to less than perfect roadways is key to being a good driver (human or otherwise). Snow is often seen as a particular challenge for motorists, as it not only creates a slick roadway, but can also hide road markings and signs. As such, guaranteeing autonomous vehicles’ safe operations in these situations is of the utmost importance.

Yandex has yet to test the self-driving cars on public roads, which means that they haven’t actually driven alongside humans. This, of course, will be a key step in bringing these autonomous vehicles to market. The company hopes to begin these trails in 2018, but this would require some legislation to be passed — as it stands, Russia forbids using self-driving cars on public roads.

For the time being, however, Polishchuk is pleased with the current tests. “There was nothing unexpected,” he said of the recent snow tests. “Computer vision algorithms should be specially tuned to work properly when the snow is falling and covering road surface, and driving technology should count slick surface when choosing speed mode. We will continue tests during the whole winter to make sure our technology for driverless car is reliable for such conditions.”

Visteon gives self-driving car test site near Ypsilanti $5 million

YPSILANTI TOWNSHIP, MI – The American Center for Mobility has secured another $5 million in funding and its first Tier 1 automotive supplier to sponsor the connected and autonomous vehicle testing facility under construction in Ypsilanti Township.

Visteon Corp. is joining Toyota North America and its Research Institute, Ford Motor Co., AT&T and Hyundai America Technical Center as founding sponsors of The American Center for Mobility, which is being developed at a former General Motors factory located between Detroit and Ann Arbor.

Hyundai joins Ford, Toyota as sponsor of autonomous vehicle testing center

Visteon, headquartered in Van Buren Township, is an automotive cockpit electronics supplier currently developing smart technologies for connected and autonomous vehicles like its SmartCore domain controller.

The company is planning to test its DriveCore artificial intelligence-based autonomous driving platform at The American Center for Mobility, or ACM.

It is rolling out the new technology to the public at the Consumer Electronics Show in Las Vegas next year.

Visteon will focus on four areas of testing and validation at ACM, according to the statement:

  • Autonomous driving algorithms
  • Vehicle-to-vehicle and vehicle-to-infrastructure technology and functionality, integrated with autonomous driving
  • Sensor technology
  • Security protocols

Visteon’s goals include creating fail-safe domain controller hardware that integrates data across connected and autonomous vehicles and using artificial intelligence to educate autonomous vehicles on how to detect objects and make decisions.

Sachin Lawande, president and CEO of Visteon, said in a statement the company is proud to be associated with ACM.

“The Center is ideally positioned to fulfill the need to further develop, test and validate new connected and automated vehicle technologies that offer great promise for the nation’s transportation system,” Lawande said in the statement. “Teaming with ACM will help advance our own autonomous driving platform while bringing significant benefits to consumers, transportation users and transportation operators.”

ACM’s site near the Willow Run Airport is designated as a national proving ground for autonomous vehicles, where work is being done to develop standards and education programs like the recently-announced Academic Consortium made up of 15 Michigan colleges and universities.

15 Michigan colleges and universities join self-driving vehicle program

Construction began in June on ACM’s multimillion dollar testing facility, about 10 miles outside of Ann Arbor, near the Willow Run Airport and the Yankee Air Museum.

Old bomber factory celebrated as new test site for automated vehicles

It is the former site of Willow Run, a manufacturing facility that first produced airplane bombers during World War II and later built vehicles for Ford Motor Co. and General Motors Co.

ACM is a joint initiative with the State of Michigan founded in partnership with the Michigan Department of Transportation, the Michigan Economic Development Corp., University of Michigan, Business Leaders for Michigan and Ann Arbor SPARK.

The $5 million sponsorship provided by Visteon will go toward funding the construction of the site, which started earlier this year, with the first part of Phase One expected to be complete by December 2017, ACM officials said.

Visteon’s contribution brings its fundraising total to around $106 million to continue developing the facility. Future phases of construction are planned to start next year.

Construction of autonomous vehicle-testing facility underway at old Willow Run site

Uber prepares next generation of self-driving cars

Uber’s next generation of self-driving cars could be on the road as early as the end of this year.

The second generation of its autonomous vehicles is being developed on Uber’s test track, an Uber spokeswoman told Fox News.

Uber’s self-driving vehicles made their debut in Pittsburgh in 2016 and have been picking up passengers ever since.

Current models require one or two vehicle operators, Uber Hardware Engineer Brian Zajac told Fox News. An Uber employee sits in the driver’s seat and is ready to take over the vehicle when the computer system tells the opertator it needs to go off self-driving mode. Another employee sits in the passenger seat monitoring a map that displays what the vehicle’s sensors see in real-time, including bikers, pedestrians and other vehicles. Customers can see what the car “sees” through an iPad provided in the back seat.

The next generation is a step closer to having no vehicle operators, Zajac said.

“In the far future, there won’t be any vehicle operator,” Zajac said. “The car rolls up, there’s no human inside at all, and the customer gets in and takes a ride.”

Some of the more immediate changes, which will be incorporated into the third generation of autonomous vehicles, are not easily visible.

“From the outside, a lot looks the same, but under the hood, we’ve made a whole bunch of improvements,” Zajac said.

One of those improvements is a higher resolution set of cameras.

“That extra resolution allows the sensors to see a little bit farther which allows the system to drive a little bit faster,” Zajac said.

The cameras will also have a better cleaning system for inclement weather.

“It’s been redesigned to handle heavier rain and to handle other types of contamination that gets on our cameras,” Zajac said.

The camera system will also have fewer parts to assemble, which would make it easier to mass produce in the future.

Current models have limited trunk space that’s shared with computer equipment. The new version will give passengers the full trunk space of the vehicle.

“You’ll see it’s a nice big open trunk that you can throw all of your luggage, jump in the car and go to the airport or wherever you might be headed,” Zajac said.

For now, Uber’s newest release will not change the passenger experience too much, a spokeswoman said.

Zajac said the engineers will keep pushing toward the goal of full autonomy.

“This is kind of uncharted territory for a lot of companies but there’s a lot of really good other industries we can draw from such as aerospace and the automotive industry,” he said.

Michelle Chavez is a Fox News multimedia reporter based in Pittsburgh.

Can NVIDIA Count on Its Latest Chip to Win Big in Self-Driving Cars? | Business Markets and Stocks News

Just when it looked like NVIDIA (NASDAQ: NVDA) was falling behind Intel (NASDAQ: INTC) in the self-driving car race, it announced a new autonomous driving platform that could swing the momentum in its favor once again. The graphics specialist’s latest innovation brings fully autonomous, driverless cars a step closer to reality.

More importantly, it could potentially set the company on its way to make a big splash in one of the most lucrative applications for self-driving technology: ride-hailing. Let’s take a look at what this latest product could do for NVIDIA, and the potential bumps in the road that it could face.

Introducing the DRIVE PX Pegasus

The DRIVE PX Pegasus — the latest generation of NVIDIA’s artificial-intelligence-enabled autonomous driving platform — should help the company turn a new page in self-driving car development as it is 10 times more powerful than the existing DRIVE PX2 chip.

This makes the chip capable of powering Level 5 autonomy, which means that a vehicle equipped with the DRIVE PX Pegasus could drive completely on its own, removing the need for a steering wheel or pedals. NVIDIA has already decided a roadmap for this new chip, believing that it could be the key to developing autonomous taxis.

The good news is that this Pegasus has already gotten off the ground. NVIDIA has gotten 25 of its partners to start testing this new chip. Looking ahead, it won’t be surprising if more companies join the team as NVIDIA has built a solid ecosystem of 225 partners who use DRIVE PX for self-driving car development.

More importantly, NVIDIA has a clear vision for the new chip. The company’s ride-hailing service partners, such as NuTonomy and Optimus Ride, are already working on Level 5 self-driving taxis, and they believe that DRIVE PX Pegasus will accelerate their time to market. This sets the chipmaker on its way to attack a rapidly growing ride-hailing services market that’s part of what some call the mobility-as-a-service market, or MaaS.

Goldman Sachs analysts forecast that the global ride-hailing industry will grow eight-fold by 2030, mainly driven by the deployment of autonomous fleets by participants such as Uber, Lyft, and others. More specifically, the daily average of ride-hailing trips could jump to 97 million in 2030 from just 15 million at present since autonomous fleet deployment would allow service providers to enhance efficiency and complete more trips.

NVIDIA could win big from this space provided its execution remains top-notch. But it won’t have a free hand as rival chipmaker Intel has also trained its sights on the ride-hailing market.

NVIDIA will run into Intel’s automotive alliance

Intel has rapidly brought its autonomous driving technology up to speed after lagging NVIDIA initially. In fact, Intel’s chips are powering self-driving cars from Alphabet subsidiary Waymo.

This is a huge win for Chipzilla as Waymo has established a substantial lead in autonomous cars, giving Intel’s self-driving technology a ringing endorsement that could help it attract automakers. But more importantly, Intel is now a part of Alphabet’s ambition of targeting the ride-hailing market.

Recent reports indicate that Alphabet is set to launch an autonomous ride-hailing service once it irons out glitches. This means that Intel could have the early mover advantage in the ride-hailing space as it will be able to display the capability of its chips commercially, while NVIDIA’s Pegasus platform is still under testing.

However, the ride-hailing industry is too big to be dominated by just one player. This is where NVIDIA’s numerous partnerships could come into play, allowing it to carve a slice of this potentially big market that could boost its business in the long run.

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Suzanne Frey, an executive at Alphabet, is a member of The Motley Fool’s board of directors. Harsh Chauhan has no position in any of the stocks mentioned. The Motley Fool owns shares of and recommends Alphabet (A shares), Alphabet (C shares), and Nvidia. The Motley Fool recommends Intel. The Motley Fool has a disclosure policy.