Today we have cars. In 30 years we will have cars. But in the meantime, some cars will will driven by humans and others not, and there will be terms to distinguish them.
Today, most people use the terms Autonomous, Automated, Self-Driving, and Driverless as interchangeable. Even wikipedia does not differentiate. Yet some people in the field make a point of the differences (e.g. Alain Kornhauser). If I understand these differences correctly, a self-driving car is not as advanced as driverless, in that driverless doesn’t have the back-up of a person taking control, and self-driving might. Driverless taxis are not merely self-driving, they pick up passengers and may be personless. In SAE terms, driverless is Level 5, while self-driving is Level 4 or below.
The truck itself appears to be a Peterbilt 579, most likely equipped with an automatic transmission, because why should Waymo make more work for themselves?
The autonomy equipment appears to be primarily mounted on a roof rack, which houses what seems to be a central LIDAR dome and four ultrasonic sensors, two at each side, covering front and rear. A radar emitter appears to be mounted low and center on the front bumper.
Imagine rearranging the seats in your car to watch a movie on a big screen in the dashboard. Or controlling functions like air conditioning by touching the window. Or replacing rearview mirrors with cameras that give you a live-action look at the surrounding traffic.
Those are just some of the ideas car makers and designers are kicking around as they imagine a driverless future. When cars can largely navigate roads on their own, there’s no need for the interior design to rigidly follow the model established in the early days of automobiles. The inside of driverless cars might look more like living rooms or meeting places on wheels, with a focus on flexibility and entertainment.
Industry officials say fully autonomous and shared-mobility vehicles may be a decade or more away, but increasingly high-tech interiors will start showing up in the next few model years. On the latest luxury-car models, information has begun to move from digital instruments behind the wheel to head-up displays projected on the windshield, so drivers can monitor things like speed and turn-signal indicators without looking down. And other amenities are in the works, such as seats that fully recline or rotate 180 degrees, dashboard ice chests and ambient lighting.
Geovanie Rosario signed the lease because it was easy. Tower Auto Mall came recommended by Uber, as one of four dealers the ride-hailing company partnered with in New York City to offer “flexible and affordable” rentals and lease-to-own contracts to drivers. Rosario went to see Tower one morning in May 2016 and started driving a black Lincoln MKS, New York City’s standard car-service vehicle, a week later. His contract included a $3,000 service fee and weekly payments of $495 for 159 weeks, or just over three years. Tower would take the payments directly out of his Uber earnings every Monday.
Rosario had quit his position as an assistant manager at Rent-A-Center, a job with benefits and a 401(k), to drive for Uber in March 2015. Rent-A-Center paid $12.25 an hour, and, based on Uber’s ads, he figured he could double that by becoming a driver. He had tried a couple of car rental options and, by the time he went to Tower, felt confident he could make enough to come out ahead.
Uber made an unusual commitment to the engineer it hired to lead its driverless car project: It would cover the costs of legal actions against him over information stored in his head from his previous job at Waymo.
That promise — buried in the fine print of an otherwise straightforward employment contract for an executive — emerged in documents unsealed last week in San Francisco federal court.
Waymo alleges that in 2015, Anthony Levandowski and Uber Technologies Inc. hatched a plan for him to steal more than 14,000 proprietary files, including the designs for lidar technology that helps driverless cars see their surroundings. Uber, which acquired Levandowski’s startup, Otto, in August for $680 million, has denied Waymo’s allegations.
Will Browne, Mike Swarbrick Jones:
Today, it is relatively simple to experiment with different versions of the same website. There are many technologies and tools that can help e-commerce businesses build and run randomised controlled trials (otherwise known as A/B tests). The amount of data available to large e-commerce sites means that businesses can measure the effect of changing design, messaging and merchandising. Over the last three years, Qubit has been helping these businesses explore which changes are associated with an increase in revenue.
In previous work [7], Qubit showed that many of the practices used in the A/B testing industry at the time were fundamentally flawed. Since its release we have seen a change in both the statistical models used in the industry, and a shift to more robust experimental procedures. In this paper, we would like to move the industry forward again, and answer the question – what kind of changes do our clients make, and how do they impact revenue?
We will present the results of a meta-analysis, conducted in 2017, on Qubit’s large database of experiments. We will describe the effects of 29 treatment types and estimate the cumulative impact of these experiments on site wide revenue. The methodology used in this paper was independently assured by PricewaterhouseCoopers UK LLP (PwC)1. To our knowledge, this is the first published, independently assured quantitative analysis of its type. We hope it will be used to improve the quality of A/B testing, to reset expectations, and to prioritise optimisations to websites.
We have decided to separate this work into three sections to answer three slightly different questions, keeping methodologies and results together where possible. In section 2 we divide our experiments into different treatment categories, and estimate the overall impact of each of them. In section 3 we estimate the overall distribution of all experiment impacts used in this work. In section 4 we look at how A/B testing impacts overall site-wide revenue across sets of web-domains. There are a number of appendices expanding on the results of these sections.
During the hoo-ha, one of the spooks with whom I discussed Snowden’s revelations waxed indignant about our coverage of the story. What bugged him (pardon the pun) was the unfairness of having state agencies pilloried, while firms such as Google and Facebook, which, in his opinion, conducted much more intensive surveillance than the NSA or GCHQ, got off scot free. His argument was that he and his colleagues were at least subject to some degree of democratic oversight, but the companies, whose business model is essentially “surveillance capitalism”, were entirely unregulated.
He was right. “Surveillance”, as the security expert Bruce Schneier has observed, is the business model of the internet and that is true of both the public and private sectors. Given how central the network has become to our lives, that means our societies have embarked on the greatest uncontrolled experiment in history. Without really thinking about it, we have subjected ourselves to relentless, intrusive, comprehensive surveillance of all our activities and much of our most intimate actions and thoughts. And we have no idea what the long-term implications of this will be for our societies – or for us as citizens.
“Desire lines”, or “desire path”, is an expression increasingly used when referring to urban planning. However, we got used to see this “desire path” traced in flowerbed, fields and woods: they are those paths formed as a consequence of vegetation erosion due to the frequent human passage; in fact, they have been chosen as the best way to go from point A to point B. Mapping out bicycle desire lines allows to understand the most used paths in certain urban areas, and to make them real and safe by building a cycle track. It may happen that the desire paths don’t follow precisely already built streets, but rather that they pass through buildings, courtyards, or through squares and other areas that are not reserved for circulation. That happens because a city street grid is often more ancient than the buildings it contains, that may change and offer new paths to travel through.
For consumers, it’s designed to be an easier way to shop. To use the store, called Moby, you download an app and use your phone to open the door. A hologram-like AI greets you, and, as you shop, you scan what you want to buy or place it in a smart basket that tracks your purchases. Then you walk out the door; instead of waiting in line, the store automatically charges your card when you leave (Amazon is testing a similar system). The tiny shop will stock fresh food and other daily supplies, and if you want something else you can order it using the store’s artificial intelligence. The packages will be waiting when you return to shop the next time. When autonomous vehicles are allowed on roads, the store could also show up at your home, and the company is also testing a set of drones to make small deliveries.
The first of the three waves is something most of us have already experienced: the ability to summon a car and a driver with your phone. Millions of people around the world now use ride sharing every day. When the CEO of the world’s biggest ride sharing company behaves like a dick and takes an enforced leave of absence, it makes headline news (incidentally, now that Uber doesn’t have a CEO, COO, CTO or CFO we guess this is the closest it’s ever been to a self-driving car company?)
The second technological wave is the arrival of the electric vehicle. Tesla is now the planet’s 4th most valuable automaker and there are already more than 2 million electric vehicles on the world’s roads. While the falling costs of batteries gets most of the attention here, the truly revolutionary bit in an electric vehicle is actually the drivetrain. That’s because the drivetrain for an internal combustion engine contains about 2,000 parts while an electric one contains about 20. A system with two orders of magnitude fewer parts is way more reliable and saves a lot of money by eliminating around half the cost of traditional car maintenance. It gives electric vehicles much longer lifespans. The average combustion vehicle lasts about 250,000 km, while current estimates for today’s electric vehicles are around 800,000 km.
Finally, CAR has identified three reasons to be pessimistic about auto jobs returning to the US in large numbers:
Current talent shortages (the unemployment rate in the transportation equipment sector was 3.7% in 2016—fully one point lower than the national average); in addition, shortages are especially acute in skilled trades occupations.
Global competitiveness—every auto production region sources from low-cost/best-cost countries; the US auto industry would be less competitive on a global stage without use of “best-cost” parts and components.
The US light vehicle market is near the top of the cycle; manufacturers will be cautious about making greater US investments that could lead to an overcapacity situation as the market eventually slows or begins to contract.
Jonas Rooze & Andreas Gandolfo:
Electric vehicles are an agent of change for not only the vehicle owner but also power generators and the power system. But when, and how will this change take place? This video explores the different scenarios that we will face.
Will supply follow demand or vice versa?
Watch our Summit Short video below to find out more.
This report presents the findings from the Swedish Energy Agency and the Swedish Transport Administration commissioned study on the Life Cycle energy consumption and greenhouse gas emissions from lithium-ion batteries. It does not include the use phase of the batteries.
The study consists of a review of available life cycle assessments on lithium-ion batteries for light- duty vehicles, and the results from the review are used to draw conclusions on how the production stage impacts the greenhouse gas emissions. The report also focuses on the emissions from each individual stage of the battery production, including; mining, material refining, refining to battery grade, and assembly of components and battery.
The report is largely structured based on a number of questions. The questions are divided in two parts, one focusing on short-term questions and the second on more long-term questions. To sum up the results of this review of life cycle assessments of lithium-ion batteries we used the questions as base.
When Starwood Capital Group LLC bought Fairlane Town Center in 2014, the investment firm had a lot of work to do.
The Dearborn, Mich., mall was only 72% leased, and among the vacant space was a sprawling former anchor store.
A chance call to Ford Motor Co. to sell some mall advertising turned out to be a game changer. In April, Ford moved its entire engineering and purchasing staff into space once inhabited by department-store chain Lord & Taylor. Ford is now the mall’s largest tenant, with 240,000 square feet of space.
After years toiling away in secret on its car project, Apple Inc. Chief Executive Officer Tim Cook has for the first time laid out exactly what the company is up to in the automotive market: It’s concentrating on self-driving technology.
“We’re focusing on autonomous systems,” Cook said in an interview on Bloomberg Television on June 5. “It’s a core technology that we view as very important.”
“We sort of see it as the mother of all AI projects,” Cook said in his most detailed comments to date on Apple’s plans in the car space. “It’s probably one of the most difficult A.I. projects actually to work on.”
My husband and I share a 492-square-foot apartment in Cambridge, Mass. We inhabit a “micro apartment,” or what is sometimes called a tiny house. This label is usually proudly applied to dwellings under 500 square feet, according to Wikipedia. We are unwittingly on a very small bandwagon, part of a growing international movement.
But deep inside the expensive custom closets and under the New Age Murphy beds, the pro-petite propaganda has hidden some unseemly truths about how the other half lives. No one writes about the little white lies that help sell this new, very small American dream.
Google’s approach contrasts starkly with Apple’s. Apple’s browser, Safari, will use a method called intelligent tracking prevention to prevent tracking by third parties—that is, sites that are rarely visited intentionally but are incorporated on many other sites for advertising purposes—that use cookies and other techniques to track us as we move through the web. Safari will use machine learning in the browser (which means the data never leaves your computer) to learn which cookies represent a tracking threat and disarm them. This approach is similar to that used in EFF’s Privacy Badger, and we are excited to see it in Safari.
Users Can Opt In to Publisher Payments—But Not Out of Tracking
In tandem with their Better Ads enforcement, Google will also launch a companion program, Funding Choices, that will enable CBA-compliant sites to ask Chrome users with content blockers to whitelist their site and unblock their ads. Should the user refuse, they can either pay for an “ad-free experience” or be locked out by a publisher’s adblock wall. Payment is to be made using a Google product called Contributor, first deployed in 2015. Contributor lets people pay sites to avoid being simply shown Google ads, but does not prevent Google, the site, or any other advertisers from continuing to track people who pay into the Contributor program. This approach is consistent with the ad industry’s dogged defense of tracking, and its refusal to honor user signals such as Do Not Track. The industry’s sole response has been to create a system called AdChoices, which offers users a complicated and inefficient opt-out from targeted ads, but not from the data collection and the behavioral tracking behind the targeting. By that logic, it is okay to track and spy on people who opt out—as long as you don’t remind them that they are being tracked!
“Nothing that you will learn in the course of your studies will be of the slightest possible use to you,” the Oxford philosophy professor John Alexander Smith told his students, in 1914, “save only this: if you work hard and intelligently, you should be able to detect when a man is talking rot.” Smith might be pleased to know that this week, at the University of Washington, in Seattle, some hundred and fifty students will complete “Calling Bullshit in the Age of Big Data,” a course less profanely and more prosaically known as INFO 198/BIOL 106B. Taught by Jevin West, an information scientist, and Carl Bergstrom, a biologist, it created something of an online sensation when its syllabus went up, in January, and when registration opened it filled to capacity in less than a minute.
A technology developed by Purdue researchers could provide an “instantly rechargeable” method that is safe, affordable and environmentally friendly for recharging electric and hybrid vehicle batteries through a quick and easy process similar to refueling a car at a gas station.
The innovation could expedite the adoption of electric and hybrid vehicles by eliminating the time needed to stop and re-charge a conventional electric car’s battery and dramatically reducing the need for new infrastructure to support re-charging stations.
The chief executive of General Motors, an automaker synonymous with Detroit, saw the future of driving not in the Motor City but on the streets of San Francisco.
Mary T. Barra, a G.M. lifer who had worked her way from engineer to the top, was in the back seat of a prototype self-driving electric car as it wound its way through the city’s downtown a year ago.
She wanted to see for herself whether automation was ready to take over from a driver — safely, and on a mass scale. How would it react, for example, when it reached an intersection as a light turned yellow?
Driving in a situation like that, “you have to make a decision,” she recalled in a recent interview. “Generally if you decide to go, you decide to speed up. Or you stop.” If the technology works, she said, it will make the right decision: “The car knows.”
Consumer adoption of peer-to-peer and ride-hailing services such as Uber and Lyft points toward a generational sea change in how consumers and businesses view transportation. These changing behaviors are combining with rising urbanization, pervasive high-speed mobile broadband, and rapid technological leaps in computing power and data center capacity to enable these new business models to drive and accelerate the development and use of autonomous mobility solutions.
Ironically, carmakers have turned to offering these same car-sharing and ad hoc use applications to drive up utilization rates. The global nature and scale of this change has major implications for the adoption and use of autonomous “Mobility-as-a-Service” among consumers and businesses alike. “Being driven” by intelligent, pilotless vehicles will represent the essential nature of future transportation.
Strategy Analytics expects that, as we move toward SAE level five1 vehicle autonomy, these megatrends will combine and enable Mobility-as-a-Service to open the door to an emerging new market that we refer to as the “Passenger Economy.” This Passenger Economy represents the value of the products and services derived from the use of fully autonomous, pilotless vehicles, including the indirect savings in both time and resources generated by the use of pilotless vehicles.
We do not see this only in desktop (including laptop) computing. The tablet probably blasted to form factor sufficiency faster than any broad consumer computing device we have ever seen. Actually, a broader perspective would say that is untrue. We were struggling with weight, battery life, processing capability, input modes and overall responsiveness in different incarnations of the tablet for decades. But when the iPad arrived on the scene with its combination of screen size, weight, battery life, touch input, processing power and instant-on we had turned through an inflection point of sufficiency. Changes since then have been merely incremental — which drives crazy the engineers working on these things and expending great energy and creativity to have it described this way. The engineers at Maytag working on the next iteration of the washing machine probably feel the same way.
Germany’s powerful car industry said Europe would need to reassess its environmental standards to remain competitive after the United States said it would withdraw from the Paris climate pact.
President Donald Trump said on Thursday he would withdraw the United States from the landmark 2015 global agreement to fight climate change, drawing anger and condemnation from world leaders and heads of industry.
BigchainDB is proud to announce that a live prototype for sharing of autonomous vehicle data has been built in collaboration with the Toyota Research Institute (TRI) and the MIT Media Lab. The Autonomous Vehicle Data Exchange – AVDEX – allows researchers to buy datasets from data producers, for improving the artificial intelligence (AI) and machine learning (ML) algorithms for autonomous vehicles. The prototype was presented at Consensus 2017 in New York.
Autonomous vehicles offer the promise to radically reduce the over one million annual road deaths around the world, because they never text while driving, get distracted or get tired – like humans do. Before autonomous vehicles can be fully safe for all road conditions, the Rand Corp and McKinsey estimated that one trillion road miles worth of data needs to be collected.
No single entity will be able to reach one trillion miles in the near future individually, but the sharing of data within the mobility ecosystem could bring autonomous cars to reality faster.
There are more ways to trade the autonomous driving and electric car trends than you think.
Morgan Stanley shared its favorite 30 stock picks for the emerging technologies with clients that not only include the direct auto-related supplier winners, but consumer and retail names that may benefit from the freed up time and responsibilities.
The firm’s “US Research team settled on 30 US stocks, all rated either overweight or equal-weight, across 14 industries, that the analysts believe are favorably exposed to growth opportunities in the execution of a shared, autonomous, electric ecosystem, or are favorably positioned to the adjacent data and content opportunities,” analyst Adam Jonas wrote in a report to clients Thursday entitled “The Shared Autonomous 30.”
CARMAKERS like to talk about autonomous vehicles (AVs) as if they will be in showrooms in three or four years’ time. The rosy scenarios suggest people will soon be whisked from place to place by road-going robots, with little input from those on board. AVs will end the drudgery of driving, we are told. With their lightning reactions, tireless attention to traffic, better all-round vision and respect for the law, AVs will be safer drivers than most motorists. They won’t get tired, drunk, have fits of road rage, or become distracted by texting, chatting, eating or fiddling with the entertainment system.
The family AV will ferry children to school; adults to work, malls, movies, bars and restaurants; the elderly to the doctor’s office and back. For some, car ownership will be a thing of the past, as the cost of ride-hailing services like Uber and Lyft tumbles once human drivers are no longer needed. Going driverless could cut hailing costs by as much as 80%, say optimists. Welcome to the brave new world of mobility-on-demand.