Technology StocksDriverless autos, trucks, taxis etc.

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From: Sam10/4/2017 8:26:12 AM
   of 282
Here is Ars Technica's article on Waymo's ambition to launch its taxi service within months:

Fully driverless cars could be months away Google's self-driving car unit prepares to launch a taxi service near Phoenix.
Timothy B. Lee - 10/3/2017, 2:11 PM

Real driverless cars could come to the Phoenix area this year, according to a Monday report from The Information's Amir Efrati. Two anonymous sources have told Efrati that Google's self-driving car unit, Waymo, is preparing to launch "a commercial ride-sharing service powered by self-driving vehicles with no human 'safety' drivers as soon as this fall."

Obviously, there's no guarantee that Waymo will hit this ambitious target. But it's a sign that Waymo believes its technology is very close to being ready for commercial use. And it suggests that Waymo is likely to introduce a fully driverless car network in 2018 if it doesn't do so in the remaining months of 2017.
These are all reasons to doubt whether Waymo will be able to launch a truly driverless taxi service this year as Page would like. However, it's important not to lose sight of the big picture: these are the kinds of problems you worry about when you are months, rather than years, away from launching a commercial product.

Most of Waymo's rivals are aiming to release self-driving cars in 2020, 2021, or later. Even if Waymo's schedule slips a few months and it introduces a self-driving car service in the middle of 2018 instead of late 2017, that will still give the company a multiple-year head start over most of its rivals. And it would confound skeptics who insist that full self-driving technology is still years away.

more at

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From: Sam10/4/2017 8:32:22 AM
   of 282
Seattle investors don’t want you — or any other human — behind the wheel on I-5 by 2040
Originally published October 2, 2017 at 6:00 am Updated October 3, 2017 at 10:02 am

The tech experts who proposed making Interstate 5, from Seattle to Vancouver, B.C., open only to self-driving cars have updated their proposal. Now they’ve got a timeline: no human drivers by 2040.

By David Gutman
Seattle Times staff reporter

The venture-capital guys who proposed limiting Interstate 5 between Seattle and Vancouver, B.C., to just self-driving cars are back with an update, and a timeline for when they’d like to see human drivers booted from the freeway.

The report by the Madrona Venture Group, a Seattle-based firm and an early funder of Amazon, and Craig Mundie, a former Microsoft executive, proposes phased-in changes to the highway, ultimately leading to a ban on human drivers, during peak travel hours, in 2040.

The new report wants carpool lanes opened immediately to autonomous vehicles, two lanes (one north, one south) exclusively for autonomous vehicles by 2025, a majority of I-5’s lanes just for autonomous vehicles by 2030 and no more human drivers on I-5 during peak travel times by 2040.

Human drivers would still be allowed on nights and weekends.

Traffic Lab is a Seattle Times project that digs into the region’s thorny transportation issues, spotlights promising approaches to easing gridlock, and helps readers find the best ways to get around. It is funded with the help of community sponsors Alaska Airlines, CenturyLink, Kemper Development Co., Sabey Corp., Seattle Children’s hospital and Ste. Michelle Wine Estates. Seattle Times editors and reporters operate independently of our funders and maintain editorial control over Traffic Lab content.

Learn more about Traffic Lab »
In last year’s report and this year’s update, the authors write that Seattle and Vancouver can get ahead of the game by embracing and planning for what they say is the inevitable spread of self-driving cars. The pace of progress in the industry led the authors to update their proposal, they said.

Vancouver and Seattle, they write, can serve “as an example for how to proactively and responsibly incorporate this important cultural and technological change into their regional city and transportation planning.”

The proposal was first launched at a cross-border innovation conference in Vancouver last year, partly as a way to distinguish the region from cities hostile to autonomous vehicles, and is being updated for this year’s conference in Seattle.

The authors — along with Mundie, Madrone co-founder Tom Alberg and Madrona associate Daniel Li — predict fully autonomous vehicles, with no human input necessary, will be available in three years.

But even if that’s right — and some experts are skeptical — it doesn’t mean autonomous vehicles are going to be ubiquitous, said Don Mac­Kenzie, a professor of environmental engineering at the University of Washington who studies electric and autonomous vehicles.

“There’s really no evidence to indicate that you would have all cars being capable of autonomous operation by 2040, or even the large majority,” MacKenzie said. “There’s still, to me, this huge equity issue where you’re shutting out travel on I-5 to lower-income people who have fewer alternatives.”

Madrona has a financial interest in promoting policy changes geared toward self-driving cars; the group is an investor in at least three local companies — Impinj, Mighty AI and Echodyne — that make components for potential use in autonomous vehicles.

Vehicles with different levels of autonomous control — automated braking or steering, for instance — are already on the road in cities and states across the country, albeit almost always with a driver behind the wheel.

Google began t esting self-driving cars, in small numbers, in Kirkland last year.

In July, Gov. Jay Inslee, hoping to lure tech companies in a growing industry, signed an executive order opening Washington’s roads to testing of self-driving cars, with or without a person behind the wheel.

“We humans are really good at a lot of things,” Inslee said at the time. “Driving cars isn’t necessarily one of them compared to the automated processes that are digital and foolproof.”

Widespread adoption of autonomous vehicles could, in theory, lead to fewer crashes and less traffic congestion — since fleets of self-driving cars could travel closer together and at more uniform speeds than human drivers can safely do.

But it also could lead to increased congestion if, for instance, your autonomous vehicle drives you to work and then drives itself home to avoid the hassle of finding parking. That turns one car trip into two.

Of course, cars last a long time. The average car on the road right now is 11 years old. And people aren’t going to be happy if their 2017 car is banned from parts of Washington’s most traveled highway just eight years from now, and banned entirely during peak driving hours in two decades.

“This final transition will require some tipping point in terms of vehicle availability and public interest,” the authors write, predicting that tipping point in 10 to 20 years.

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To: Sam who wrote (136)10/4/2017 11:15:24 AM
From: Savant
   of 282
Call me a skeptic, but what they want and what happens are 2 different things...IMHO...
Too many people with older cars that don't comply...
And, as the article points out, it would severely hamper lower income people.
Quite possibly, it will happen someday/year, but by 2040?
I doubt it.

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From: Savant10/4/2017 9:42:17 PM
   of 282
Senate bill

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From: Sam10/5/2017 2:02:26 PM
   of 282

Sep 12, 2017

Micron Reveals Critical Technologies for Autonomous Vehicles Micron Outlines Highest-Performance Solution for Fully Autonomous Vehicles with GDDR; Extends Security Solution to Auto Market

SAN FRANCISCO, Sept. 12, 2017 (GLOBE NEWSWIRE) -- MOBILE WORLD CONGRESS (MWC) AMERICAS -- Autonomous vehicles require safe, secure and highly-responsive solutions, relying on split second decisions powered by enormous amounts of data. To quickly analyze the data necessary for future autonomous vehicles, higher bandwidth memory and storage solutions are required.

By 2020, the storage requirements of the connected vehicle could reach 1 terabyte. Memory system bandwidths of 300 gigabytes per second (GB/s) and beyond will be required to power full autonomous driving. As the memory and storage market leader in automotive, Micron (Nasdaq:MU) is uniquely positioned to help accelerate the industry's pace of innovation.

  • Fastest LPDDR4 shipping to auto manufacturers - Micron is already deploying automotive-grade low-power DDR (LPDDR) memories to multiple automotive customers. The company announced today that it has commenced shipping LPDDR4x, running at 4266 megatransfers per second (MT/s) — the highest speed grade permitted by the LPDDR4 specification - to key chipset partners. This technology can enable overall system bandwidths of up to 100GB/s and provides a foundation for the next-generation of autonomous vehicle design.
  • High-performance memories for automotive - Today, Micron is also announcing its commitment to deliver high-bandwidth GDDR6 memory solutions for the automotive market. Graphics memory (GDDR) is a high-performing memory commonly found today in gaming, graphics and virtual reality applications. Micron plans to leverage its strength in graphics memory to provide the highest bandwidth solutions designed to meet stringent auto qualifications. The company is actively engaged with leading automotive partners and customers to enable GDDR technologies that will meet the needs of level 4/5 — full autonomy — and beyond.
  • Autonomous driving, AI and machine learning are rapidly converging in tomorrow's vehicles, which will become the ultimate Internet of Things and edge computing devices. While cloud connectivity in modern vehicles creates new service opportunities, it also creates security management challenges and vulnerability concerns.

  • Introducing secure boot: Micron is extending the value of its hardware-based Authenta™ security solution by showcasing the capability to secure boot a system based completely on Authenta-enabled memory. The technology will provide a unique level of protection for the lowest layers of device software in automotive ECUs, starting with a secure boot process.
  • New development kits for Authenta security solutions: At MWC, the company announced that it plans to make Authenta™ software and hardware development kits available to general automotive and IoT customers by the end of the year. This will enable customers to begin evaluating how to integrate Authenta-enabled flash in their security architecture, to implement capabilities like secure boot, cloud-based attestation, authentication and provisioning. This will allow customers to increase the defense in depth of their solutions, all without adding additional hardware components into their design.
  • Media panel with industry leaders
    During a press panel on the eve of MWC Americas, Micron and key industry partners discussed the technologies and solutions that will become increasingly critical enablers for the next wave of intelligent vehicles in the automotive sector. Watch the replay here:

  • Jeff Bader, VP of Embedded Business Unit, Micron:
    "The automotive segment presents a unique set of requirements that depend on innovation from Micron. High-performance memories such as Micron's GDDR will help accelerate the overall system capabilities of connected vehicles by providing the raw performance that will initially be needed to achieve full autonomy. With the addition of GDDR to our portfolio, Micron is extending our leadership position and continuing to fuel innovation in the automotive industry."

  • Krish Inbarajan, Global Head of Connected Car, Cisco Jasper:
    "At the center of connected car innovation today is the need to consistently enhance the driver's experience by delivering valuable connected services. Auto makers need to be able to deliver compelling new services that drive recurring revenue, while also making the driving experience safer and more personalized. Cisco Jasper Control Center is the automated connectivity management platform trusted by more than 50 leading car brands to run connected car services reliably, securely, and at a lower cost - globally."

  • Doug Seven, Head of Connected Vehicle Platform, Microsoft Azure:
    "Security lies at the heart of Microsoft's Connected Vehicle Platform. Vehicles will increasingly make autonomous decisions that affect the safety of its passengers and other drivers and pedestrians, and manufacturers need to be confident in the integrity of these systems. Microsoft is one of only a few companies with a global cloud that has enterprise-security built in. Our commitment to compliance and regulation are the top reasons car manufacturers will rely on and trust Microsoft to help them build future connected vehicles."

  • Tim Wong, Director of Technical Program Management for Autonomous Vehicles, NVIDIA:
    "Artificial intelligence for self-driving requires a fresh approach to allow vehicles to make sense of, and act on, huge volumes of data flowing into the vehicle in real time. We're working with automakers and suppliers to meet this major industry shift to autonomous vehicles by enabling them to design cars using the most advanced processor and memory technologies."

  • Sanjay Vishin, Director of Automotive Platforms, Qualcomm:
    "5G/Wireless connectivity to smart vehicles will be a game changer both for enabling vehicle-to-infrastructure and vehicle-to-vehicle communications. It will provide a bridge between the car, its surroundings and the cloud, especially as the car becomes more autonomous. This will enable more efficient machine learning (and hence services) in the Cloud and in the Car, along with more predictive and efficient collaborative control for autonomous cars."
  • About Micron
    Micron Technology is a world leader in innovative memory solutions. Through our global brands — Micron, Crucial® and Ballistix® - our broad portfolio of high-performance memory technologies, including DRAM, NAND, NOR Flash and 3D XPoint™ memory, is transforming how the world uses information. Backed by more than 35 years of technology leadership, Micron's memory solutions enable the world's most innovative computing, consumer, enterprise storage, data center, mobile, embedded, and automotive applications. Micron's common stock is traded on the Nasdaq under the MU symbol. To learn more about Micron Technology, Inc., visit

    Micron and the Micron orbit logo are trademarks of Micron Technology, Inc. All other trademarks are the property of their respective owners.

    Public Relations Contact:
    Marc Musgrove
    +1 (208) 363-2405,

    Investor Relations Contact:
    Shanye Hudson
    +1 (208) 492-1205,

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    From: Sam10/9/2017 7:14:11 AM
       of 282
    A MF piece on Intel's position in the autonomous driving sector. They are clearly committed to compete with NVDA and others.

    3 Reasons Intel Can Win the Self-Driving Car Race
    Intel has rapidly, but strategically, positioned itself to lead the autonomous-car market.

    Harsh Chauhan
    ( TechJunk13)
    Oct 8, 2017 at 12:17PM

    Intel ( NASDAQ:INTC) has definitely come a long way since the March announcement of its acquisition of vision specialist Mobileye for a princely sum of $15.3 billion. This move is now acting as a catalyst for Intel in the self-driving car race, where it was lagging graphics specialist NVIDIA ( NASDAQ:NVDA).

    NVIDIA looked like the go-to investment to tap the autonomous car opportunity, given its impressive product-development moves and partnerships with leading automakers. But the status quo has changed as Intel has moved to cut NVIDIA's lead in this space, giving investors more clarity as to how it plans to monetize this opportunity.

    A closer look at Intel's moves in self-driving cars clearly indicates that the company has built its presence in a rapid and strategic manner.

    Buying strength

    Intel might have paid through the nose for Mobileye, but its outlay looks reasonable in the face of the estimated $77 billion value that the autonomous vehicle market could reach by 2035. Mobileye already has relationships with more than 25 global automakers, 13 of which are engaged in developing autonomous cars.

    What's more, Mobileye claims that its technology is used in over 15 million vehicles across the globe, which further underscores its deep ties with automakers. Mobileye was already working with BMW (NASDAQOTH: BAMXF) when Intel announced its acquisition. The three companies are now engaged in the development of a fully autonomous self-driving car, with the intention of bringing it to market by 2021.

    NVIDIA plans to be involved in a fully autonomous car hitting the market by 2021. So Intel has gained remarkable ground in this space despite a two-year disadvantage to NVIDIA, which released its first vehicle platform in early 2015.

    As it stands, Intel and its partners plan to start testing 40 autonomous vehicles by the end of 2017. This excludes the fleet of 100 fully autonomous cars, based on Mobileye's technology, that the chip giant plans to start testing on its own this year. All this means that Intel is now well-placed to learn more about autonomous-driving technology as it gathers more data from the test cars, which will help it take the fight to NVIDIA.

    A formidable alliance

    Intel's sudden acceleration in autonomous cars has a lot to do with its willingness to partner with a variety of specialized players. Earlier this year, the chip giant brought in Delphi Automotive (NYSE: DLPH) as a systems integration specialist, which was a smart move, as Delphi had already displayed its self-driving prowess by helping an Audi car drive itself through heavy traffic in Silicon Valley.

    Delphi has worked with BMW to develop a prototype of an autonomous-driving platform. More importantly, the addition of Delphi will serve Intel's broader dreams of selling its self-driving technology to other automakers, given the former's expertise in integrating different technologies into a single platform.

    Intel, not relying just on BMW to further its self-driving ambitions, has been receptive to bringing in more automakers into its fold. In August, the chip giant welcomed Fiat Chrysler Automobiles (NYSE: FCAU) to the alliance, to accelerate technology development and also mitigate some of the high costs of self-driving car development.

    The Waymo win

    The biggest gains from the Fiat partnership were revealed in late September when Intel announced that Waymo, the self-driving-car subsidiary of Alphabet ( NASDAQ:GOOGL) ( NASDAQ:GOOG), is using Intel chips to power self-driving minivans.

    For the past few months, Waymo has been using Fiat Chrysler's Pacifica Hybrid minivans to hone its technology on public roads in Phoenix, as a part of its early rider program. But it recently came to light that these new minivans are powered by "Intel-based technologies for sensor processing, general compute and connectivity, enabling real-time decisions for full autonomy in city conditions." This is a big deal for Intel because Alphabet leads the self-driving space by a wide margin.

    What's more, the Fiat-Waymo combine is reportedly planning to offer ride-sharing services, a market that could hit $70 billion in 2021. So the alliance will need a lot more cars to tap the full potential of this market, opening up an opportunity for Intel to move more chips and technology solutions.

    All in all, the Waymo development indicates that Intel's transformation from a laggard to a leading contender in the self-driving race is now complete. The chip giant was quick to turn itself around when it seemed that NVIDIA would run away with the autonomous-driving opportunity.

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    From: Sam10/10/2017 8:08:28 AM
       of 282
    Why GM is vertically integrating as it moves deeper into making self-driving cars
    Its latest move: Buying 11-person sensor startup Strobe.
    by Johana Bhuiyan @JMBooyah Oct 9, 2017, 2:49pm EDT
    Johana Bhuiyan is the senior transportation editor at Recode and can be reached at or on Signal, Confide, WeChat or Telegram at 516-233-8877. You can also find her on Twitter at @JmBooyah.

    General Motors has made another splashy deal in the hope of accelerating its path to producing and deploying fully self-driving cars. The automaker announced today that it bought 11-person sensor startup Strobe, which specializes in developing laser-based sensors called lidars.

    The acquisition gives General Motors control over the production and development of a sensor that many believe is critical to the development of autonomous vehicles. And GM is now one of the only carmakers or autonomous vehicle developers that owns a good portion of the major components of the self-driving supply chain: The car itself, the self-driving “brain” ( via its 2016 acquisition of Cruise), a key part of the “eyes,” as well as the service layer, a proprietary ride-hail network.

    The company wouldn’t divulge any of the financial details and there’s little that’s public about the startup. However, GM had already been cultivating a relationship via an investment from its venture arm, GM Ventures.

    Bringing lidar production in-house has become especially important as self-driving players scramble to meet impending deadlines to publicly deploy autonomous vehicles. Today, while there are many companies attempting to meet the demand of the nascent self-driving space, there are few that are mass producing lidars quickly enough and affordably.

    As a result, the industry largely relies on one firm, Velodyne. However, paired with the high cost of lidar, Velodyne has also sometimes been slow to meet that high demand, some sources say, leaving companies waiting for the sensors for months.

    “Existing commercially available solutions cost tens of thousands of dollars, are bulky and mechanically complex, and lack the performance needed to unlock self-driving operation at higher speeds and in more challenging weather,” Cruise CEO Kyle Vogt wrote in a blog post announcing and explaining the deal. “Strobe’s new chip-scale LIDAR technology will significantly enhance the capabilities of our self-driving cars. But perhaps more importantly, by collapsing the entire sensor down to a single chip, we’ll reduce the cost of each LIDAR on our self-driving cars by 99%.”

    Bigger picture: GM is closer to becoming a vertically integrated autonomous vehicle manufacturer, which could help it move faster and build a better self-driving experience and business.

    First there was its acquisition of self-driving startup Cruise in 2016. Then the company began experimenting with its own ride-hail network called Cruise Anywhere. And now the company owns the production and development of a critical sensor. (GM also has a partnership with no. 2 U.S. ride-hail player Lyft, but it’s clear the company is keeping its options open.)

    The benefits of being vertically integrated are clear:
      Owning the major parts of the supply chain frees GM from relying too heavily on the production cycles of suppliers.
      It allows the company to develop the technology to its own custom specs.
      And it gives GM full control over the revenue that each of those parts bring in — say, for example, if GM decides to license its lidar technology to other companies instead of keeping it proprietary. (For now, GM’s acquisition takes this lidar tech off the market for its rivals.)
    Additionally, there are benefits to having each of these components working side by side under one roof. A good example from another industry is how Apple has used its vertical integration of hardware, software and services to make the iPhone a much more cohesive product experience than smartphones running Android software from Google.

    GM wouldn’t give any more details on how long it would take to start building the lidar sensors and outfitting its cars with them. But as it recently announced its factories were ready to manufacture cars equipped with the hardware to drive completely autonomously, it appears confident that it will be able to integrate the lidar into those production lines quickly.

    There are technological advantages to moving quickly. While being the first to market with a fully self-driving car isn’t the end-all, be-all to competition within the space, it does give whoever is first the ability to test and validate its technology far longer and then update its software based on those learnings. That means, by the time the second player rolls out its fully self-driving cars onto public roads, the first one’s technology could already be far better.

    GM is hardly the only company increasingly pushing to own more of its supply chain. Alphabet’s self-driving arm Waymo also announced it was bringing lidar development in house. Lyft, too, decided to begin developing its own autonomous software. In both cases, this could reduce how much the companies rely on external suppliers, while increasing their value to potential partners.

    But the company that comes closest to mirroring GM’s integration is rival electric vehicle manufacturer Tesla — despite that Tesla CEO Elon Musk does not subscribe to the larger industry belief that lidar is a necessary technology for autonomous cars. Tesla’s scale is much smaller than GM’s, but it is manufacturing its own cars and building its autonomous software in-house. Musk has also talked about eventually creating an on-demand network of self-driving Teslas.

    Lastly, this acquisition will likely have the same effect on the lidar and sensor industry that GM’s Cruise acquisition did. Backed by Spark Capital, Maven Ventures and others, Cruise’s exit was followed by a flurry of investments into and acquisitions of autonomous software companies. (See: Ford and Argo AI, Uber and Otto.) Since then, investors have been turning their focus toward the other components of autonomous cars, such as sensors.


    Lyft wants more leverage in the self-driving ecosystem so it’s building its own tech Carmakers have regained some of the upper hand in self-driving Famed hackers Charlie Miller and Chris Valasek are joining Cruise after leaving Didi and Uber General Motors is starting to build cars that can eventually drive without a human The complete timeline to self-driving cars Click around the complex web of relationships as Detroit and Silicon Valley try to reinvent the car

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    From: Sam10/11/2017 5:17:11 AM
       of 282
    NVIDIA just unveiled a chip to power fully self-driving trucks and robot taxis
    Eric Auchard, Reuters

    Silicon Valley graphics chipmaker NVIDIA unveiled on Tuesday the first computer chips for developing fully autonomous vehicles and said it had more than 25 customers working to build a new class of driverless cars, robotaxis and long-haul trucks.

    Deutsche Post DHL Group, the world’s largest mail and logistics company, and ZF, a top automotive parts supplier, plan to deploy a fleet of autonomous delivery trucks based on the new chips, starting in 2019, NVIDIA said.

    The third generation of NVIDIA’s Drive PX automotive line, code-named Pegasus, are chips the size of car license plates with datacenter-class processing power.

    They can handle 320 trillion operations per second, representing roughly a 13-fold increase over the calculating power of the current PX 2 class.

    This dramatic improvement is a pre-condition for developing and testing future autonomous cars, experts said.

    "NVIDIA is one step ahead. But you can be sure you can expect (rival chipmakers) Intel, NXP and Bosch not to be too far behind," said Luca De Ambroggi, principal automotive electronics analyst with industry market research firm IHS Markit.

    Computer chip giant Intel and its Mobileye automotive unit are working with German carmaker BMW and U.S. auto supplier Delphi on their own autonomous driving platform due out in 2021. NXP has agreed to be acquired by Qualcomm to form the world's largest auto electronics supplier, while Bosch, the industry's top auto supplier, is working with carmaker Daimler

    NVIDIA's automotive director Danny Shapiro said in an interview that many of the first 25 customers using Pegasus chips would focus on robotaxis, which will be built without steering wheels or brakes and used only on dedicated routes. Bigger name automakers will announce vehicles running on Pegasus at their own product launches in coming months, he said.

    Missing piece in the driverless puzzleThe Pegasus line will be available by the middle of 2018 for automakers to begin developing vehicles and testing software algorithms needed to control future driverless cars, NVIDIA executives told a developers' conference in Munich on Tuesday.

    A level 5 vehicle is capable of navigating roads without any driver input and in its purest form would have no steering wheel or brakes. A level 3 car still needs a steering wheel and a driver who can take over if the car encounters a problem, while level 4 promises driverless features in dedicated lanes.

    The deal between Deutsche Post, ZF and NVIDIA will include future Deutsche Post StreetScooter delivery trucks. In Munich, the three partners are showcasing a prototype StreetScooter running NVIDIA Drive PX chips used to control sensors including six cameras, one radar and one lidar, or 3D laser camera.

    Initial use cases will be for logistics vehicles on private roads within freight centers or for long-haul trucking in dedicated lanes, Shapiro said: "They are not replacing the drivers, but making the drivers more efficient and safer".

    For its current generation Drive PX2, NVIDIA has said it has 225 customers, including car and truck makers, Tier 1 auto suppliers, high-definition mapping companies, start-ups and research institutions. These customers can make use of PX2-class software when they upgrade to Pegasus chips, NVIDIA said.

    These could encompass existing customers Tesla, including its latest Model 3. Others include Volkswagen's Audi A8, the first car to use Level 3 semi-autonomous driving features, Toyota Motor's next-generation autonomous cars and Geely's Volvo business.

    De Ambroggi said NVIDIA's Pegasus automotive chips were the first chips with the processing power for automakers to begin developing truly autonomous vehicles, which could be upgraded with software improvements ahead of actual roadway deployments.

    But the analyst stressed that while such chips could find their way into mass-produced robotaxis running in defined lanes, these early fully-autonomous chips would likely only allow carmakers to develop prototypes ready for the driverless era.

    Regulations, road-testing, nagging safety concerns - and questions about how power-intensive the new data-hungry chips will be - are likely to mean truly driverless cars for personal use won't arrive until at least 2025, he said.

    (Reporting by Eric Auchard; Editing by Mark Potter)

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    To: Sam who wrote (142)10/11/2017 5:29:41 AM
    From: Sam
       of 282
    What AI And Autonomous Driving Mean For Nvidia Investors
    Wayne Duggan , Benzinga Staff Writer
    October 10, 2017 12:13pm

    Nvidia's stock jumped 3.2 percent on Tuesday after the company issued two press releases related to Nvidia’s role in two of the highest-growth technology fields in the world — artificial intelligence and autonomous vehicles. First, Nvidia announced that Deutsche Post DHL Group and ZF will be launching a test fleet of autonomous delivery trucks equipped with the ZF ProAI self-driving system, which is based on NVIDIA DRIVE PX technology. DPDHL already utilizes the NVIDIA DGX-1 AI supercomputer in its data centers.

    In a separate release, Nvidia announced the release of Pegasus, the world’s first AI computer designed specifically to control autonomous taxis. Pegasus is capable of managing the workload of a Level 5 driverless vehicle and delivering over 320 trillion operations per second.

    Supercomputing’s Role In AV Technology Nvidia has secured more than 200 partnerships with auto companies around the world in an effort to gain supercomputing market share in the driverless auto era. Driverless test vehicles are equipped with as many as 16 cameras, six light detection and ranging devices and a handful of other sensors. Self-driving cars require real-time processing of massive amounts of sensory data, and the capacity to handle that data means the machines need to be able to replicate the type of quick decision-making processes that human drivers do.

    Related Link: What Is Machine Learning? Deep Learning? Here's Your AI Glossary

    In addition to the massive amounts of data and speed required of these AV systems, they also need to be as small, light and inexpensive as possible. Nvidia isn’t the only chipmaker pushing hard for market share in the AV market. Rival Intel Corporation INTC has also made driverless vehicle technology a priority.

    Nvidia’s Auto Tech Nvidia has a number of auto products available or in development, including the following technologies:

    • NVIDIA DRIVE PX, the AI computer that enables automakers to scale from a single processor capable of delivering AutoCruise capabilities to a combination of multiple processors capable of handling the processing loads of fully autonomous robotaxis.
    • NVIDIA DGX-1, a deep learning system that Nvidia says is an essential part of effectively integrating AI technology into a business or product.
    • NVIDIA DRIVE IX, an AI software assistant that coupes with DRIVE PX to leverage the power of sensor data.
    • HD mapping systems, a critical part of the data collection process for companies developing self-driving cars.
    • Advanced driver assistance systems, the type of classification technology that can differentiate a police car from a taxi, an ambulance from a delivery truck or a parked car from a moving one. These systems also aid in identifying pedestrians and cyclists.
    A Major Opportunity There is certainly plenty of money at stake in the driverless vehicle market. HIS Automotive estimates that there may be 21 million self-driving cars on the road by 2035. This shift to AVs could provide $1 trillion in social and consumer benefits as well. Research and Markets estimates that the autonomous vehicle market revenue will grow at a compound annual rate of nearly 40 percent over the next decade, reaching $126.8 billion by 2027.

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    From: Sam10/16/2017 11:23:30 AM
       of 282
    The Future of Autos and Trucks Is Electric
    October 13, 2017

    This is an executive summary of ARK Invest’s electric vehicles white paper: The Future of Autos and Trucks Is Electric

    ARK Expects Global EV Sales To Exceed Current Forecasts, Substantially
    ARK expects global sales of Electric Vehicles (EVs) to reach 17 million units by 2022, while agencies like the EIA are forecasting only two to four million units. Given the declining cost curve of lithium-ion battery cells, juxtaposed against the rising cost of internal combustion engines (ICE), EV sales growth is accelerating rapidly. Growth could be curbed by battery supply constraints in the next two to three years, but capital spending in this space should accelerate as battery supplies rise to meet the demand for EVs.

    The Internal Combustion Engine Should Give Way to Battery Technology
    ARK expects that the superior economics associated with electric vehicles will cause a wholesale shift from the internal combustion engine to battery technology. Two form factors dominate battery technology today: cylindrical cells and pouch cells. Evolving with the consumer electronics industry during the past 30 to 40 years, cylindrical cells are more mature and cheaper than pouch cells. That said, pouch cells are at an earlier stage of development and, while more expensive than cylindrical batteries today, their costs are declining more rapidly. ARK expects pouch cells to reach price parity with cylindrical cells by the end of 2019, though the two cell forms will not be like-for-like at that time, as cylindrical cells are likely to maintain their specific energy advantage through 2020. ARK’s analysis demonstrates that overall system efficiency, which is battery form-factor agnostic, will have an out-sized impact on EV range and performance.

    Traditional Long-Haul Diesel Trucks Should Give Way to Electric Semi Trucks
    While automakers are waking up to the realization that electric drivetrains are the future of passenger vehicles, many manufacturers remain skeptical that heavy-duty hauling vehicles will succumb to electrification. They continue to assert that batteries are too expensive, too slow to charge, and too heavy to be incorporated into long-haul fleets. According to ARK’s research, conventional wisdom is miplaced: while EV Semis will incur higher upfront costs, total lifetime costs will be significantly lower than those for traditional semi trucks. In fact, during a 15 year life span, the total cost of ownership of an EV Semi should be roughly $500,000 lower than that of traditional diesel models.

    ARK Expects That Lithium Will Not Fall Short of the Demand From Electric Vehicles
    Just as the outsized demand for and rising price of copper spurred mining companies to explore and discover more of it, ARK expects lithium reserves to grow even as lithium production rises to meet the demand for EVs. Given the exponential ramp in demand for EVs that ARK is anticipating, lithium prices should continue to rise to the marginal cost of extracting it, giving mining companies with access to large reserves an opportunity to benefit disproportionately.

    ARK Expects Peak Oil Will Be More A Function Of Demand Than Of Supply
    While BP’s most recent Energy Outlook forecasts that global oil demand will rise from roughly 94 million barrels per day (Mb/d) today to 110 Mb/d by 2035, ARK’s research suggests that it will peak below 100 Mb/d before the end of this decade and decline to 90 Mb/d by 2035. Even if autonomous technology does not commercialize as rapidly as ARK anticipates, EV adoption alone should cause peak oil demand by 2025. Though personal cars account for less than 30% of total oil demand, diesel trucks help to explain why transportation makes up 56% of total oil demand. EV Semi trucks could be the real spoiler in the outlook for oil prices.

    ARK Expects That Batteries Will Outlive Their Vehicles
    Battery degradation is one of the biggest concerns that potential buyers express as they evaluate an EV purchase. According to ARK’s research, not only will EV batteries retain substantial value after the end of their in-vehicle life, but electric utilities probably will bid to buy them as they curb capital spending associated with peak power capacity needs. By our calculations, the value of a ten year old battery from a Tesla Model S could command as much as $13,000, more than that for an entire internal combustion engine vehicle sold originally at a similar price-point.

    The Auto Sector Is Ripe For Significant Consolidation
    After Ford introduced the moving assembly line, the horse-drawn carriage industry consolidated by more than 96% and the automotive market by roughly 80%. ARK’s research suggests that the introduction of autonomous technology and manufacturing efficiencies will cause similar levels of consolidation: autonomous vehicle networks should benefit from the network effects now enjoyed by companies like Facebook, Google, and Amazon, all of which have capitalized on “winner take most” data aggregation strategies. Data-driven industries tend to be much more concentrated than hardware-centric industries.


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