Menu

Timesdelhi.com

March 23, 2019
Category archive

aurora

Transportation Weekly: Didi woes, how Nuro met Softbank, Amazon’s appetite

in Amazon/Amplify Partners/aurora/Automotive/China/Delhi/didi/India/Lyft/nuro/Politics/Rivian/robotics/rolls-royce/Softbank Vision Fund/Transportation/Transportation Weekly/TuSimple/Uber by

Welcome back to Transportation Weekly; I’m your host Kirsten Korosec, senior transportation reporter at TechCrunch. This is the second edition and seriously people, what happened this week? Too much. Too much!

Never heard of TechCrunch’s Transportation Weekly? Catch up here. As I’ve written before, consider this a soft launch. Follow me on Twitter @kirstenkorosec to ensure you see it each week. (An email subscription is coming).

Off we go … vroom.


ONM …

There are OEMs in the automotive world. And here, (wait for it) there are ONMs — original news manufacturers. (Cymbal clash!) This is where investigative reporting, enterprise pieces and analysis on transportation lives.

This week, we’ve got some insider info on Didi, China’s largest ride-hailing firm. China-based TechCrunch reporter Rita Liao learned from sources that Didi plans to lay off 15 percent of its employees, or about 2,000 people this year. CEO Cheng Wei made the announcement during an internal meeting Friday morning.

Read about it here.

Didi’s troubles with regulators and its backlash from two high-profile passenger murders last year don’t exist in a vacuum. Their struggles are in line with what is happening in the ride-hailing industry, particularly in more mature markets where the novelty has worn off and cities have woken up.

For companies like Didi, Uber, Lyft and other emerging players, this means more resources (capital and people) spent working with cities as well as looking for ways to diversify their businesses. All the while, they must still plug away at the nagging problems of reducing costs and keeping drivers and riders.

Just look at Uber. As Megan Rose Dickey reports, Uber’s stiff losses continued in the fourth quarter. The upshot: Its losses can be attributed to increased competition and significant investment in bigger bets like micro mobility and Elevate. And apparently legal fees. Uber, The Verge reports, sued NYC on Friday to overturn a law that caps drivers.


Dig In

This week, TechCrunch editor Devin Coldewey digs into the development of a system that can estimate not just where a pedestrian is headed, but their pose and gait too.

The University of Michigan, well known for its efforts in self-driving car tech, has been working on an improved algorithm for predicting the movements of pedestrians.

These algorithms can be as simple as identifying a human and seeing how many pixels move over a few frames, then extrapolating from there. But naturally, human movement is a bit more complex than that. Few companies advertise the exact level of detail with which they resolve human shapes and movement. This level of granularity seems beyond what we’ve seen.

UM’s new system uses LiDar and stereo camera systems to estimate not just the trajectory of a person, but their pose and gait. Pose can indicate whether a person is looking towards or away from the car, or using a cane, or stooped over a phone; gait indicates speed and intention.

Is someone glancing over their shoulder? Maybe they’re going to turn around, or walk into traffic. This additional data helps a system predict motion and makes for a more complete set of navigation plans and contingencies.

Importantly, it performs well with only a handful of frames to work with — perhaps comprising a single step and swing of the arm. That’s enough to make a prediction that beats simpler models handily, a critical measure of performance as one cannot assume that a pedestrian will be visible for any more than a few frames between obstructions.

Not too much can be done with this noisy, little-studied data right now, but perceiving and cataloguing it is the first step to making it an integral part of an AV’s vision system.

— Devin Coldewey


A little bird …

We hear a lot. But we’re not selfish. Let’s share.

blinky-cat-bird

Every big funding round has an origin story — that magic moment when planets align and a capitally-flush investor gazes across a room at just the right time and spots the perfect company in need of funds and guidance.

One of this week’s biggest deals — see below — was the $940 million that Softbank Vision Fund invested in autonomous delivery robot Nuro. How (and when) Nuro met Softbank is almost as big a story as the funding round itself. OK, well maybe not AS BIG. But interesting, nonetheless.

It turns out that Cruise, the self-driving unit of GM, was in early talks with Nuro, but the parties couldn’t quite meet in the middle, people familiar with the deal told me. Sources wouldn’t elaborate whether Cruise was seeking to acquire Nuro or take a minority stake in the company.

It all worked out in the end, though. The folks at Cruise introduced Nuro to Softbank. That means Cruise and Nuro now share the same investor. Softbank agreed in May 2018 to invest $2.25 billion in GM Cruise Holdings LLC.

Got a tip or overheard something in the world of transportation? Email me or send a direct message to @kirstenkorosec.


Deal(s) of the week

We have a tie this week, which began with news that Softbank’s Vision Fund invested in autonomous delivery robot Nuro. The week closed with electric automaker Rivian announcing a $700 million funding round led by Amazon.

First Nuro. Michael Ronen, managing partner at SoftBank Investment Advisers, and the same person who was a big part of its investment in Cruise, told TechCrunch that the winners in this market will need to address a diverse mix of technological questions. In his view, that’s Nuro.

“Nuro has built a team of brilliant problem solvers whose combined backgrounds in robotics, machine learning, autonomous driving and consumer electronics give them a compelling advantage,” Ronen said.

Amazon’s investment in Rivian is important, particularly when you step back and take a more holistic and historic view. Consider this: The logistics giant stealthily acquired an urban delivery robot startup called Dispatch in 2017 (a discovery Mark Harris made and reported for us last week). Amazon showed off the fruit of that acquisition — its own delivery robot Scout — in January 2018.

Last week, self-driving vehicle startup Aurora raised more than $530 million in a Series B funding round led by Sequoia and with “significant” investments from Amazon and T. Rowe Price. Now, Amazon is backing Rivian.

Based on the deals that we know about, Amazon’s hands are now deep into autonomous delivery, self-driving vehicle software and electric vehicles. Let that sink in.

Other deals that got our attention this week:


Snapshot

Auto loans data

Sure, TechCrunch focuses on startups. Why auto loans? Because auto loan data can be one of the canaries in the coal mine that is the automotive industry and on a larger scale, the economy.  And, delinquency rates ripple through the rest of the transportation world, affecting public transit and ride-hailing too.

The New York Federal Reserve this week released a collection of economic data, including auto loans, which have been climbing since 2011. Auto loans increased by $9 billion this year, a figure boosted by historically strong levels of newly originated loans that will put 2018 in the record books. There were $584 billion in new auto loans and leases appearing on credit reports in 2018, the highest level in the 19-year history of the loan origination data.

Why I’m watching this? Because according to the Quarterly Report on Household Debt and Credit:

  • The flow into 90+ day delinquency for auto loan balances has been slowly trending upward since 2012
  • Serious delinquency of auto loans held by borrowers under 30 years old between 2014 and 2016 rose (see chart)
  • Rising overall delinquency rates remain below 2010 peak levels. However, there were more than 7 million Americans with auto loans that were 90 or more days delinquent at the end of 2018

Tiny but mighty micro mobility

It was a bit quiet on the micro-mobility front this week, but here’s what jumped out. Unsurprisingly, San Francisco denied Lime’s appeal to operate electric scooters in the city. This is the same decision the city landed on pertaining to both Uber’s Jump and Ford’s Spin appeals. On the bright side for these companies, there may be hope for them to deploy scooters during phase two of the city’s pilot program, which starts in April.

Also in the SF Bay Area, Lyft donated $700,000 to TransForm, an organization focused on improving access to transportation in underserved areas throughout California. In partnership with Oakland Mayor Libby Schaaf, Lyft and TransForm will invest in a free bike library and community “parklets” in Oakland, Calif.

Meanwhile, over in Tel Aviv, Lime deployed its electric scooters, joining electric scooter startup Bird. Lime also reportedly plans to deploy its scooters throughout the country of Israel. Next up will be cities in the Gush Dan region.

Also in micro mobility …

We read corporate updates to terms of service in our spare time. And this week, Skip sent out an update that included an interesting nugget. It reads:

We’ve updated specific provisions on camera footage. We’ve updated and made more clear that our scooters may be equipped with video camera equipment which we may use to help ensure that our scooters are used properly and in accordance with laws, rules, regulations and policies, to protect against crimes such as theft and vandalism, to help us determine if scooters are being used properly at speeds, locations and on surfaces that are proper and allowed as well as to improve our Services.

In December, Skip unveiled two new scooters — one with a rear-facing camera. The company tested 200 of these scooter in Washington, D.C. (and later rolled out to San Francisco) to monitor whether people were riding on the sidewalk and generally riding safely. At the time, Skip said it wasn’t sure what it would do with the data collected from the cameras.

In other words, Skip’s cameras are on. How they intend to use that data — whether via a warning to the rider, a message after the ride is complete, or remotely slowing the scooter down, isn’t clear.

One startup that is poised to capture this new market of scooter accountability is Fantasmo. The augmented reality mapping startup has a new scooter positioning camera that captures video and then matches that against a map to reliably identify how the scooter is being used. Fantasmo’s camera system is not being used by Skip.


Notable reads

If you’re waiting for the big autonomous vehicle disengagement hot take story from me, you’ll be waiting for awhile. Let me explain.

This week, the California Department of Motor Vehicles released the “disengagement reports” of autonomous vehicle companies with permits to test on public roads in the state. These reports are meant to track each time a self-driving vehicle disengages out of autonomous mode. There are 48 companies that issued reports, which when you combine all the data, drove more than 2 million miles on public roads in autonomous mode between December 2017 and November 2018. That’s a four-fold increase from the year before.

Companies that receive AV testing permits in California, which are issued by the DMV, are required to submit these annually. It’s not that these reports are worthless. They are useful to determine if a company is ramping up its testing on public roads, adding more AVs to its fleet, helpful for spotting trends like ‘why did disengagements suddenly end?’ or to determine if a company is even testing anymore.

And I’ve discovered some interesting information that will become bigger stories or end up as footnotes in the world of AVs. (For instance, Faraday Future says it will begin testing on public roads late this year).

But disengagement reports are not a meaningful way to make comparisons on how companies stack up against each other. Why? Because it’s not an “apples-to-apples” comparison for one, companies report the data in different ways and there is no transparency into the specifics of when and where each disengagement occurred.

Another problem is the miles-per-disengagement figure that we (the media) typically focus on. This data isn’t super useful on its own. This shouldn’t be treated like a report card. As one engineer told me once, you learn only from occasions in which the system does, or wants to do, something different from a good human. The smart AV companies will take the disengagement data and combine it with other information taken from simulation and other forms of offline testing.

The “miles per disengagement” data point doesn’t start to mean anything on its own until a company reaches the validation phase, which is when miles driven are the truest representation of naturalistic driving in the domain and application of interest. How many are at this point? I’m hearing one or two.


Testing and deployments

Much of the talk and marketing materials around flying cars, or eVTOLs, focuses on well-dressed business folks standing on top of skyscrapers, preparing to be whisked away — up and over the terrible traffic below. Other startups have focused on last-mile delivery. But what about long-distance cargo delivery to remote and urban areas?

Elroy Air is one company that is working on this problem. The San Francisco-based startup has been developing an autonomous vertical takeoff and landing cargo transport system that can operate outside of airport infrastructure and carry up to 500 pounds of cargo over 300 miles. Elroy Air just closed a $9.2 million round that included investors Catapult Ventures, Levitate Capital, Lemnos, Precursor Ventures, Haystack, Shasta Ventures, Homebrew, 122West, Amplify Partners, Hemisphere Ventures, the E14 Fund and DiamondStream Partners.

The company said this week it will begin testing its unmanned vertical-takeoff-and-landing drone for commercial deliveries — called the Chaparral — this year and launch a commercial shipping service  in 2020.

These vehicles will be monitored by trained operators at all times during the testing phase, the company said.


On our radar

Let’s not forget that people are using buses and trains everyday. Not in a year. Not in 10. Right now. These transit systems, many of which need expensive upgrades, carry millions of people every day. One of the more interesting examples of the challenges with transit is the L train shutdown in New York.

The Metropolitan Transportation Authority needs to repair a subway tunnel under the East River and initially had planned to shut down the entire tunnel for 15 months, starting in late April. The L train carries 275,000 people between Bedford Avenue in Brooklyn and Eighth Avenue in Manhattan, the effected section, every day.

New York Gov. Andrew Cuomo intervened and now there’s a new plan, which involves running trains through one tunnel tube while repairs are carried out in the other tube. The NYT has the back story.

There’s an upcoming “L Train Shutdown” event this month in Brooklyn that we’re keeping an eye on. URBAN-X, the startup accelerator backed by automotive brand MINI, is hosting a discussion on the future of the L-train and alternative modes of transport. Some interesting folks will be participating, including Lime’s chief program officer Scott Kubly. The event will be held 6:30 pm to 8:30 pm, Feb. 19 at A/D/O, 29 Norman Ave, Brooklyn, NY.

Thanks for reading. There might be content you like or something you hate. Feel free to reach out to me at kirsten.korosec@techcrunch.com to share those thoughts, opinions or tips. 

Nos vemos la próxima vez.

News Source = techcrunch.com

Aurora cofounder and CEO Chris Urmson on the company’s new investor, Amazon, and much more

in Amazon/aurora/Automotive/Delhi/India/Logistics/Politics/robotics/self-driving/sequoia capital/t.rowe price/TC/Transportation/waymo by

You might not think of self-driving technologies and politics having much in common, but at least in one way, they overlap meaningfully: yesterday’s enemy can be tomorrow’s ally.

Such was the message we gleaned Thursday night, at a small industry event in San Francisco, where we had the chance to sit down with Chris Urmson, the cofounder and CEO of Aurora, a company that (among many others) is endeavoring to make self-driving technologies a safer and more widely adopted alternative to human drivers.

It was a big day for Urmson. Earlier the same day, his two-year-old company announced a whopping $530 million in Series B funding, a round that was led by top firm Sequoia Capital and that included “significant investment” from T. Rowe Price and Amazon.

The financing for Aurora — which is building what it calls a “driver” technology that it expects to eventually integrate into cars built by Volkswagen, Hyundai, and China’s Byton, among others —  is highly notable, even in a sea of giant fundings. Not only does it represent Sequoia’s biggest bet yet on any kind of self-driving technology, it’s also an “incredible endorsement” from T. Rowe Price, said Urmson Thursday night, suggesting it demonstrates that the money management giant “thinks long term and strategically [that] we’re the independent option to self-driving cars.”

Even more telling, perhaps, is the participation of Amazon, which is in constant competition to be the world’s most valuable company, and whose involvement could lead to variety of scenarios down the road, from Aurora powering delivery fleets overseen by Amazon, to Amazon acquiring Aurora outright. Amazon has already begun marketing more aggressively to global car companies and Tier 1 suppliers that are focused on building connected products, saying its AWS platform can help them speed their pace of innovation and lower their cost structures. In November, it also debuted a global, autonomous racing league for 1/18th scale, radio-controlled, self-driving four-wheeled race cars that are designed to help developers learn about reinforcement learning, a type of machine learning. Imagine what it could learn from Aurora.

Indeed, at the event, Urmson said that as Aurora had “constructed our funding round, [we were] very much thinking strategically about how to be successful in our mission of building a driver. And one thing that a driver can do is move people, but it can also move goods. And it’s harder to think of a company where moving goods is more important than Amazon.” Added Urmson, “Having the opportunity to have them partner with us in this funding round, and [talk about] what we might build in the future is awesome.” (Aurora’s site also now features language about “transforming the way people and goods move.”)

The interest of Amazon, T. Rowe, Sequoia and Aurora’s other backers isn’t surprising. Urmson was the formal technical lead of Google’s self-driving car program (now Waymo) . One of his cofounders, Drew Bagnell, is a machine learning expert who still teaches at Carnegie Mellon and was formerly the head of Uber’s autonomy and perception team. Aurora’s third cofounder is Sterling Anderson, the former program manager of Tesla’s Autopilot team.

Aurora’s big round seemingly spooked Tesla investors, in fact, with shares in the electric car maker dropping as a media outlets reported on the details. The development seems like just the type of possibility that had Tesla CEO Elon Musk unsettled when Aurora got off the ground a couple of years ago, and Tesla almost immediately filed a lawsuit against it, accusing Urmson and Anderson of trying poach at least a dozen Tesla engineers and accusing Anderson of taking confidential information and destroying the  evidence “in an effort to cover his tracks.”

That suit was dropped two and a half weeks later in a settlement that saw Aurora pay $100,000. Anderson said at the time the amount was meant to cover the cost of an independent auditor to scour Aurora’s systems for confidential Tesla information. Urmson reiterated on Thursday night that it was purely an “economic decision” meant to keep Aurora from getting further embroiled in an expansive spat.

But Urmson, who has previously called the lawsuit “classy,” didn’t take the bait on Thursday when asked about Musk, including whether he has talked in the last two years with Musk (no), and whether Aurora might need Tesla in the future (possibly). Instead of lord Aurora’s momentum over the company, Urmson said that Aurora and Tesla “got off on the wrong foot.” Laughing a bit, he went on to lavish some praise on the self-driving technology that lives inside Tesla cars, adding that “if there’s an opportunity to work them in the future, that’d be great.”

Aurora, which is also competing for now against the likes of Uber, also sees Uber as a potential partner down the line, said Urmson. Asked about the company’s costly self-driving efforts, whose scale has been drastically downsized in the eleven months since one of its vehicles struck and killed a pedestrian in Arizona, Urmson noted simply that Aurora is “in the business of delivering the driver, and Uber needs a lot of drivers, so we think it would be wonder to partner with them, to partner with Lyft, to partner [with companies with similar ambitions] globally. We see those companies as partners in the future.”

He’d added when asked for more specifics that there’s “nothing to talk about right now.”

Before Thursday’s event, Aurora had sent us some more detailed information about the four divisions that currently employ the 200 people that make up the company, a number that will obviously expand with its new round, as will the testing it’s doing, both on California roads and in Pittsburgh, where it also has a sizable presence. We didn’t have a chance to run them during our conversation with Urmson, but we thought they were interesting and that you might think so, too.

Below, for example, is the “hub” of the Aurora Driver. This is the computer system that powers, coordinates and fuses signals from all of the vehicle’s sensors, executes the software and controls the vehicle. Aurora says it’s designing the Aurora Driver to seamlessly integrate with a wide variety of vehicle platforms from different makes, models and classes with the goal of delivering the benefits of its technology broadly.

Below is a visual representation of Aurora’s perception system, which the company says is able to understand complex urban environments where vehicles need to safely navigate amid many moving objects, including bikes, scooters, pedestrians, and cars.

It didn’t imagine it would at the outset, but Aurora is building its own mapping system to ensure what it (naturally) calls the highest level of precision and scalability, so vehicles powered by the company can understand where they are and update the maps as the world changes.

We asked Urmson if, when the tech is finally ready to go into cars, they will white-label the technology or else use Aurora’s brand as a selling point. He said the matter hasn’t been decided yet but seemed to suggest that Aurora is leaning in the latter direction. He also said the technology would be installed on the carmakers’ factory floors (with Aurora’s help).

One of the ways that Aurora says it’s able to efficiently develop a robust “driver” is to build its own simulation system. It uses its simulator to test its software with different scenarios that vehicles encounter on the road, which it says enables repeatable testing that’s impossible to achieve by just driving more miles.

Aurora’s motion planning team works closely with the perception team to create a system that both detects the important objects on and around the road, and tries to accurately predict how they will move in the future. The ability to capture, understand, and predict the motion of other objects is critical if the tech is going to navigate real world scenarios in dense urban environments, and Urmson has said in the past that Aurora has crafted its related workflow in a way that’s superior to competitors that send the technology back and forth.

Specifically, he told The Atlantic last year: “The classic way you engineer a system like this is that you have a team working on perception. They go out and make it as good as they can and they get to a plateau and hand it off to the motion-planning people. And they write the thing that figures out where to stop or how to change a lane and it deals with all the noise that’s in the perception system because it’s not seeing the world perfectly. It has errors. Maybe it thinks it’s moving a little faster or slower than it is. Maybe every once in a while it generates a false positive. The motion-planning system has to respond to that.

“So the motion-planning people are lagging behind the perception people, but they get it all dialed in and it’s working well enough—as well as it can with that level of perception—and then the perception people say, ‘Oh, but we’ve got a new push [of code].’ Then the motion-planning people are behind the eight ball again, and their system is breaking when it shouldn’t.”

We also asked Urmson about Google, whose self-driving unit was renamed Waymo as it spun out from the Alphabet umbrella as its own company. He was highly diplomatic, saying only good things about the company and, when asked if they’d ever challenged him on anything since leaving, answering that they had not.

Still, he told as one of the biggest advantage that Aurora enjoys is that it was able to use the learnings of its three founders and to start from scratch, whereas the big companies from which each has come cannot completely start over.

As he told TechCrunch in a separate interview last year when asked how Aurora tests its technology, then it comes to self-driving tech, size matters less than one might imagine. “There’s this really easy metric that everyone is using, which is number of miles driven, and it’s one of those things that was really convenient for me in my old place [Google] because we’re out there and we were doing a hell of a lot more than anybody else was at the time, and so it was an easy number to talk about. What’s lost in that, though, is it’s not really the volume of the miles that you drive.” It’s about the quality of the data, he’d continued, suggesting that, for now, at least, Aurora’s is hard to beat.

News Source = techcrunch.com

Transportation Weekly: Amazon’s secret acquisition and all the AV feels

in Amazon/Anthony Levandowski/Argo AI/aurora/Automotive/carsharing/Chris Urmson/Craft Ventures/Daimler/david sacks/Delhi/Elon Musk/Google/India/Kirsten Korosec/Lead Edge Capital/Maxwell Technologies/Megan Rose Dickey/mike volpi/myTaxi/Politics/self-driving cars/Sequoia/starship technologies/t.rowe price/TC/TechCrunch/Tesla/Transportation/Tusk Ventures/Uber/valor equity partners/waymo by

Welcome to Transportation Weekly; I’m your host Kirsten Korosec, senior transportation reporter at TechCrunch. I cover all the ways people and goods move from Point A to Point B — today and in the future — whether it’s by bike, bus, scooter, car, train, truck, robotaxi or rocket. Sure, let’s include hyperloop and eVTOLs, or air taxis, too.

Yup, another transportation newsletter. But I promise this one will be different. Here’s how.

Newsletters can be great mediums for curated news — a place that rounds up all the important articles a reader might have missed in any given week. We want to do a bit more.

We’re doubling down on the analysis and adding a heaping scoop of original reporting and well, scoops. You can expect Q&As with the most interesting people in transportation, insider tips, and data from that white paper you didn’t have time to read. This isn’t a lone effort either. TechCrunch senior reporter Megan Rose Dickey, who has been writing about micro mobility since before the scooter boom times of 2017, will be weighing in each week in our “Tiny But Mighty Mobility” section below. Follow her @meganrosedickey.

Consider this a soft launch. There might be content you like or something you hate. Feel free to reach out to me at kirsten.korosec@techcrunch.com to share those thoughts, opinions, or tips.

Eventually, we’ll have a way for readers to sign up and have Transportation Weekly delivered each week via email. For now, follow me on Twitter @kirstenkorosec to ensure you see it each week.

Now, let’s get to the good stuff.


ONM …

There are OEMs in the automotive world. And here, (wait for it) there are ONMs — original news manufacturers.


This is where investigative reporting, enterprise pieces and analysis on transportation will live.

We promised scoops in Transportation Weekly and here is one. If you don’t know journalist Mark Harris, you should. He’s an intrepid gumshoeing reporter who TechCrunch has been lucky enough to hire as a freelancer. Follow him @meharris.

Amazon quietly acquired robotics company Dispatch to build Scout

dispatch-amazon-scout
Remember way back in January when Amazon introduced Scout, their autonomous delivery bot? There was speculation at the time that Amazon had bought the Estonian-based company Starship Technologies. Harris did some investigating and discovered some of the intellectual property and technology behind Scout likely came from a small San Francisco startup called Dispatch that Amazon stealthily acquired in 2017.

It’s time to stop thinking about Amazon as just an e-commerce company. It’s a gigantic logistics company, probably the biggest on the planet, with a keen interest — and the cash to pursue those interests — in automation. Think beyond Scout. In fact, wander on down this post to the deal of the week.


Dig In

Each week, transportation weekly will spend a little extra time on an approach, policy, tech or the people behind it in our ‘Dig In” section. We’ll run the occasional column here, too.

This week features a conversation with Dmitri Dolgov, the CTO and VP of engineering at Waymo, the former Google self-driving project that spun out to become a business under Alphabet.

waymo-google-10-years

Ten years ago, right around now, about a dozen engineers started working on Project Chauffeur, which would turn into the Google self-driving project and eventually become an official company called Waymo. Along the way, the project would give rise to a number of high-profile engineers who would go on to create their own companies. It’s a list that includes Aurora co-founder Chris Urmson, Argo AI co-founder Bryan Salesky and Anthony Levandowski, who helped launch Otto and more recently Pronto.ai.

What might be less known is that many of those in the original dozen are still at Waymo, including Dolgov, Andrew Chatham, Dirk Haehnel, Nathaniel Fairfield and Mike Montemerlo.

Dolgov and I talked about the early days, challenges and what’s next. A couple of things that stood out during our chat.

There is a huge difference between having a prototype that can do something once or twice or four times versus building a product that people can start using in their daily lives. And it is, especially in this field, very easy to make progress on these kinds of one-off challenges.

Dolgov’s take on how engineers viewed the potential of the project 10 years ago …

I also use our cars every day to get around, this is how I got to work today. This is how I run errands around here in Mountain View and Palo Alto.


A little bird …

We hear a lot. But we’re not selfish. Let’s share.
blinky-cat-birdAn early investor, or investors, in Bird appear to be selling some of their shares in the scooter company, per a tip backed up by data over at secondary trading platform EquityZen. That’s not crazy considering the company is valued at $2 billion-ish. Seed investors should take some money off the table once a company reaches that valuation.

We’ve heard that David Sacks at Craft Ventures hasn’t sold a single Bird share. We hear Tusk Ventures hasn’t sold, either. That leaves a few others, including Goldcrest Capital, which was the lone seed investor, and then Series A participants Lead Edge Capital, M13, and Valor Equity Partners.

Got a tip or overheard something in the world of transportation? Email me or send a direct message to @kirstenkorosec.

While you’re over at Twitter, check out this cheeky account @SDElevator. We can’t guarantee how much of the content is actually “overheard” and how much is manufactured for the laughs, but it’s a fun account to peruse from time to time.

Another new entrant to the mobility parody genre is @HeardinMobilty.


Deal of the week

There’s so much to choose from this week, but Aurora’s more than $530 million Series B funding round announced Thursday morning is the winner.

The upshot? It’s not just that Aurora is now valued at more than $2.5 billion. The primary investors in the round — Sequoia as lead and “significant” investments from Amazon and T. Rowe Price — suggests Aurora’s full self-driving stack is headed for other uses beyond shuttling people around in autonomous vehicles. Perhaps delivery is next.

And believe it or not, the type of investor in this round tells me that we can expect another capital raise. Yes, Aurora has lots of runway now as well as three publicly named customers. But investors like Sequoia, which led the round and whose partner Carl Eschenbach is joining Aurora’s board, T. Rowe Price and Amazon along with repeaters like Index Ventures (general partner Mike Volpi is also on the board) have patience, access to cash and long-term strategic thinking. Expect more from them.

Other deals that got our attention this week:


Snapshot

Speaking of deals and Tesla … the automaker’s $218 million acquisition this month of Maxwell Technologies got me thinking about companies it has targeted in the past.

So, we went ahead and built a handy chart to provide a snapshot view of some of Tesla’s noteworthy acquisitions. tesla-acquisitions-chart1

One note: Tesla CEO Elon Musk tweeted in 2018 that the company had acquired trucking carrier companies to help improve its delivery logistics. We’ve dug in and have yet to land on the company, or companies, Tesla acquired.

The deals that got away are just as interesting. That list includes a reported $325 million offer to buy Simbol Materials, the startup that was extracting small amounts of lithium near the Salton Sea east of San Diego.


Tiny but mighty mobility

Between Lime’s $310 million Series D round and the seemingly never-ending battle to operate electric scooters in San Francisco, it’s clear that micro mobility is not so micro.

Lime, a shared electric scooter and bikeshare startup, has now raised north of $800 million in total funding, surpassing key competitor Bird’s total funding of $415 million. Thanks to this week’s round of funding, Lime’s micromobility business is now worth $2.4 billion.

Lime currently operates its bikes and scooters in more than 100 cities worldwide. Over in San Francisco, however, Lime has yet to deploy any of its modes of transportation. Since last March, there’s been an ongoing battle among scooter operators to deploy their services in the city. The city ultimately selected Skip and Scoot for the pilot programs, leaving the likes of Lime, Uber’s JUMP and Spin to appeal the decision.

A neutral hearing officer has since determined SF’s process for determining scooter operators was fair, but the silver lining for the likes of JUMP, Spin and most likely, Lime, is that the city may open up its pilot program to allow additional operators beginning in April.


Notable reads

Two recent studies got my attention.

The first is from Bike Pittsburgh, an advocacy group and partner of Uber, that published the findings from its latest AV survey based on responses from local residents. The last time they conducted a similar survey was in 2017.

The takeaway: people there, who are among the most exposed to autonomous vehicles due to all the AV testing on public roads, are getting used to it. A bit more than 48 percent of respondents said they approve of public AV testing in Pittsburgh, down slightly from 49 percent approval rating in 2017. 

  • 21.21% somewhat approve
  • 11.62% neutral
  • 10.73% somewhat disapprove
  • 8.73% disapprove

One standout result was surrounding responses about the fatal accident in Tempe, Arizona involving a self-driving Uber that struck and killed pedestrian Elaine Herzberg in March 2018. Survey participants were asked “As a pedestrian or a bicyclist how did this change event and it’s outcome change your opinion about sharing the road with AVs?”

Some 60 percent of respondents claimed no change in their opinion, with another 37 percent claiming that it negatively changed their opinion. Nearly 3 percent claimed their opinion changed positively toward the technology.

Bike Pittsburgh noted that the survey elicited passionate open-ended responses. 

“The incident did not turn too many people off of AV technology in general,” according to Bike Pittsburgh. “Rather it did lead to a growing distrust of the companies themselves, specifically with Uber and how they handled the fatality.”

The other study, Securing the Modern Vehicle: A Study of Automotive Industry Cybersecurity Practices, was released by Synopsys, Inc.and SAE International.

The results, based on a survey of global automotive manufacturers and suppliers conducted by Ponemon Institute, doesn’t assuage my concerns. If anything, it puts me on alert.

  • 84% of automotive professionals have concerns that their organizations’ cybersecurity practices are not keeping pace with evolving technologies
  • 30% of organizations don’t have an established cybersecurity program or team
  • 63% test less than half of the automotive technology they develop for security vulnerabilities.

Testing and deployments

Pilots, pilots everywhere. A couple of interesting mobility pilots and deployments stand out.

Optimus Ride, the Boston-based MIT spinoff, has made a deal with Brookfield Properties to provide rides in its small self-driving vehicles at Halley Rise – a new $1.4 billion mixed-use development in Virginia. 

This is an example of where we see self-driving vehicles headed — for now. Small deployments that are narrowly focused in geography with a predictable customer base are the emerging trend of 2019. Expect more of them.

And there’s a reason why, these are the kinds of pilots that will deliver the data needed to improve their technology, as well as test out business models —gotta figure out how to money with AVs eventually — hone in fleet operational efficiency, placate existing investors while attracting new ones, and recruit talent.

Another deployment in the more conventional ride-hailing side of mobility is with Beat, the startup that has focused its efforts on Latin America.

Beat was founded by Nikos Drandakis in 2011 initially as Taxibeat. The startup acquired by Daimler’s mytaxi in February 2017 and Drandakis still runs the show. The company was focused on Europe but shifted to Latin America, and it’s made all the difference. (Beat is still available in Athens, Greece.) Beat has launched in Lima, Peru, Santiago, Chile and Bogota, Colombia and now boasts 200,000 registered drivers. 

Now it’s moving into Mexico, where more competitors exist. The company just started registering and screening drivers in Mexico City as it prepares to offer rides for passengers this month. 

TechCrunch spoke at length with Drandakis. Look out for a deeper dive soon.

Until next week, nos vemos.

News Source = techcrunch.com

Waymo CTO on the company’s past, present and what comes next

in Anthony Levandowski/Argo AI/Artificial Intelligence/aurora/Automotive/avs/Chris Urmson/Delhi/Google/India/Larry Page/Politics/sebastian thrun/self-driving car/TC/TechCrunch/Transportation/waymo by

A decade ago, about a dozen or so engineers gathered at Google’s main Mountain View campus on Charleston Road to work on Project Chauffeur, a secret endeavor housed under the tech giant’s moonshot factory X.

Project Chauffeur — popularly know as the “Google self-driving car project” — kicked off in January 2009. It would eventually graduate from its project status to become a standalone company called Waymo in 2016.

The project, originally led by Sebastian Thrun, would help spark an entire ecosystem that is still developing today. Venture capitalists took notice and stampeded in, auto analysts shifted gears, regulators, urban planners and policy wonks started collecting data and considering the impact of AVs on cities.

The project would also become a springboard for a number of engineers who would go on to create their own companies. It’s a list that includes Aurora  co-founder Chris Urmson,  Argo AI co-founder Bryan Salesky as well as Anthony Levandowski, who helped launch Otto and more recently Pronto.ai.

What might be less known is that many who joined in those first weeks are still at Waymo, including Andrew Chatham, Dmitri Dolgov, Dirk Haehnel, Nathaniel Fairfield and Mike Montemerlo. Depending on how one defines “early days,” there are others like Hy Murveit, Phil Nemec, and Dan Egnor, who have been there for eight or nine years.

Dolgov, Waymo’s CTO and VP of engineering, chatted recently with TechCrunch about the early days, its 10-year anniversary, and what’s next.

Below is an excerpt of an interview with Dolgov, which has been edited for clarity and length.

TC: Let’s go back to the beginning of how you got started. Take me to those first days at the Google self-driving project.

DOLGOV: When I think about what drew me to this field, it’s always been three main things: the impact of the technology, the technology itself, and the challenges as well as the people you get to work with. It’s pretty obvious, at this point, that it can have huge implications on safety, but beyond that, it can impact efficiency and remove friction from transportation for people and things.

There is this sense of excitement that never seems to die off. I remember the first time I got to work on a self-driving car. And it was the first time when the car drove itself using software that I had written, you know, just earlier in the day. So this was back in 2007. And that completely blew my mind. (Dolgov participated in the DARPA Urban Challenge in November 2007 before the Google project launched)

TC: What were these 10, 100-mile challenges that (Google co-founder) Larry Page came up with? Can you describe that to me a little bit?

DOLGOV: This was probably the main milestone that we created for ourselves when we started this project at Google in 2009. And the challenge was to drive 10 routes, each one was 100 miles long. And you had to drive each one from beginning to end without any human intervention.

These were really well defined very clearly, crisply defined routes. So in the beginning, you’d engage the self driving mode of a car, and then had to finish the whole 100 miles on its own.

The routes were intentionally chosen to sample the full complexity of the task. In those early days, for us, it was all about understanding the complexity of the problem. All of the routes were in the Bay Area. We had some driving in urban environments, around Palo Alto,  we had one that spent a lot of time on the freeways and went to all of the bridges in the Bay Area. We had one that went from Mountain View to San Francisco, including driving through Lombard Street. We had one that went around Lake Tahoe.

We tried to cover as much of the complexity of the environment as possible. And what’s really great about that task is that it really helped us very quickly understand the core complexity of the space.

TC: How long did it take to complete these challenges?

DMITRI: It took us until the fall of 2010.

TC: It’s kind of amazing to think that the project was able to complete these challenges in 2010, and yet, there still seems to be so much more work to complete on this task.

DOLGOV: Right. But I think this is the nature of the problem. There is a huge difference between having a prototype that can do something once or twice or a handful of times versus building a product that people can start using in their daily lives. And it is, especially in this field, when we started, it’s very easy to make progress on these kinds of one-off challenges.

But what really makes it hard is an incredible level of performance that you need from your system in order to make it into a product. And that’s number one. And number two, is the very long tail of complexity of the types of problems that you encounter. Maybe you don’t see them 99% of the time, but you still have to be ready for that 1% or 1.1%.

TC:  When you think back to those early days — or maybe even more recently — was there ever a moment when where there was a software problem, or even a hardware problem that seemed insurmountable and that maybe the tech just wasn’t quite there yet?

DOLGOV: In the early days, we had all kinds of problems that we faced. In the early history of this project, we only set out to solve some problems without really knowing how we were going to get there.

You start working on the problem, and you make progress towards this. Thinking back to how these past few years have felt to me: It’s been much less of a here’s one problem, or a small number of really hard problems and we kind of hit a wall.

Instead, it’s been more like hundreds of really hard problems. None of them feel like a brick wall because, you know, the team is amazing, the technology is really powerful, and you make progress on them.

But you’re always juggling like, hundreds of these types of really complex problems, where the further you get into solving each one of them, the more you realize just how hard it really is.

So it’s been a really interesting mix: on one hand, the problem getting more difficult, the more you learn about it. But on the other hand, technology making more rapid progress and breakthroughs happening at a higher rate than you would have originally anticipated.

TC: When did you realize that this project had changed (beyond the official announcements)? When did you realize it could be a business, that it was something that could be a lot more than just solving this problem?

DOLGOV: I would describe it as more of an evolution of our thinking and investing more effort into more clearly defining the product and commercial applications of this technology.

When we started, in that very first phase, the question was, “is this even feasible? Is technology going to work?” I think it was pretty clear to everybody that if the technology succeeded then there was going to be tremendous impact.

It wasn’t exactly clear what commercial application or what product would deliver that impact. But there was just so many ways that this technology would transform the world that we didn’t spend much time worrying about that aspect of it.

When you think about it, what we’re building here is a driver: our software, our hardware —the software that runs in the car, the software that runs in the cloud. We look at the entirety of our technology stack as a driver.

There are about 3 trillion miles in the U.S. that are driven by people. In some cases, they drive themselves, in some cases, they drive other people, in some cases, they drive goods. Once you have the technology that is “the driver,” you can deploy it in all these situations. But they have their pros and cons.

Over time, our thinking on ‘what are the most attractive ones?’ and ‘in what order do we tackle them?’ has matured.

This is what they’re doing today as a result of all of that work. Ride hailing is the first commercial application that we’re pursuing. Beyond that we are working on long-haul trucking, long range deliveries. We’re interested, at some point, deploying the technology in personally owned cars, local deliveries, public transportation, so forth and so on.

TC: What application are you most excited about? The one that you think maybe is overlooked or one you’re personally the most excited about?

DOLGOV: I’m super excited about seeing the technology and the driver being deployed in, you know, across the globe and across different commercial applications. But I think the one that I am the most excited about is the one we’re pursuing as our number one target right now, which is ride hailing.

I think it has the potential to affect positively the highest number of people in the shortest amount of time.

I also use our cars every day to get around, this is how I got to work today. This is how I run errands around here in Mountain View and Palo Alto. It’s wonderful to be able to experience these cars and it just removes a lot of the friction out of transportation.

TC: So you you take a self driving car to work every day right now?

DOLGOV: Yes, but in California, they still have people in them. 

TC: How long have you been doing that?

DOLGOV: Awhile. Actually, it seems like forever.

I’ve always spent time in the cars. I think it’s really important to experience the product that you’re building and have direct experience with the technology. This was obviously the case in the early days of the project when there was a small group of us doing everything.

As the team grew, I would still make sure I would experience the technology and go on test rides at least weekly, if not more frequently.

When we started pursuing the ride-hailing application, and we build an app for it, and we built out infrastructure to make it into a user-facing product, I was one of the earlier testers.

That must have been three years ago.

TC: Did you expect it to be at this point that you are right now, 10 years ago, did you expect like 10 years from now, this is where we’re going to be? Or did it happen faster or slower than you anticipated?

DOLGOV: So for me, I think on one hand, I would not have predicted some of the breakthroughs in the technology on the hardware front, on the software and AI and machine learning back in 2009. I think the technology today is much more powerful than I would have probably said in 2009.

On the another hand, the challenge of actually building a real product and deploying it so that people can use it has turned out to be more difficult than I expected. So it’s kind of a mix.

TC: What were some of those technological breakthroughs?

DOLGOV: There were a number of things. LiDARs and radars became much more powerful.

And by powerful, I mean longer range, higher resolution and more features, if you will, in terms of the things that they can measure — richer returns of the properties of the environment. So that’s on the sensing side.

Compute, especially in the hardware-accelerated parallel computation, that’s been very powerful for the advancement of neural networks. That has been a huge boost.

Then there’s deep learning and the neural nets themselves have led to a number of breakthroughs.

TC: Yeah, with the last two examples you gave, I think of those as being breakthroughs more recently, in just the last few years. Is that about the timeframe?

DOLGOV: We’ve always used machine learning on this project, but it was a different kind of machine learning then today.

I think in 2012 is probably when, on our project, there was meaningful effort and when we were working together with Google on both the self-driving technology and deep learning.

Arguably, at the time Google was the only company in the world seriously investing in both the self driving and deep learning.

At that point, we didn’t have the hardware to be able to run those nets on the car, in real time. But there were very interesting things you could do in the cloud.

For deep learning, 2013 was a pretty big year. I think this is when ImageNet won a big competition and it was a breakthrough for deep learning. It outperformed all the other approaches in the computer vision competition.

TC: In 2009, could you imagine a world in 2019, where numerous self-driving vehicle companies would be testing on roads in California? Was that something that seemed plausible?

DOLGOV: No, no that’s not the picture I had in mind in 2009 or 2010.

In those early days of the project, people kind of laughed at us. I think the industry made fun of this project and there were multiple funny spoofs on the Google self-driving car project.

It’s been pretty amazing to go from, ‘oh there is small, group of crazy folks trying to do this science fiction thing at Google’ to this becoming a major industry that we have today with dozens, if not hundreds, of companies pursuing this.

Google’s self-driving Lexus RX 450h

TC: What will be the tipping point that will get folks on board with self driving vehicles in their city? Is it a matter of just pure saturation? Or is it something else that that all the companies, Waymo included, are responsible of helping usher in?

DOLGOV: It seems like there’s always a spectrum of people’s attitudes towards new technology and change. Some of the negative ones are more visible. But actually, my experience over the last 10 years, the positive attitude and the excitement has been overwhelmingly stronger.

What I what I have seen over and over again, in this project that really is very powerful, and that is powerful and changes people’s attitudes from, uncertainty and anxiety to excitement and comfort and trust is being able to experience the technology.

You get people into one of our cars and then go for a ride. Even people who are anxious about getting into a car with nobody behind the wheel, once they experience it and once they understand how useful of a product it is, and how well the car behaves, and they starting trusting it, that really leads to change.

As the technology rolls out and more people get to experience it firsthand, that will help.

TC: Are the biggest challenges in 2009 the same as today? What are the final cruxes that remain?

DOLGOV: In 2009, all the challenges were all about one-off problems we needed to solve and today it’s all about turning it into a product.

It’s about the presentation of this self-driving stack and about building the tools and the framework for evaluation and deployment of the technology. You know, what has stayed true is that it’s all about the speed of iteration and the ability to learn new things and solve new technical problems as we discover them.

News Source = techcrunch.com

Startups Weekly: Will Trump ruin the unicorn IPOs of our dreams?

in aurora/BlackRock/Delhi/Facebook/First Round Capital/funding/goodwater capital/India/Insight Venture Partners/Lyft/Magic Leap/money/Mr Jeff/Pinterest/Politics/Postmates/romain dillet/sequoia capital/SoftBank/Startups/U.S. Securities and Exchange Commission/Uber/Valentin Stalf/Venture Capital by

The government shutdown entered its 21st day on Friday, upping concerns of potentially long-lasting impacts on the U.S. stock market. Private market investors around the country applauded when Uber finally filed documents with the SEC to go public. Others were giddy to hear Lyft, Pinterest, Postmates and Slack (via a direct listing, according to the latest reports) were likely to IPO in 2019, too.

Unfortunately, floats that seemed imminent may not actually surface until the second half of 2019 — that is unless President Donald Trump and other political leaders are able to reach an agreement on the federal budget ASAP.  This week, we explored the government’s shutdown’s connection to tech IPOs, recounted the demise of a well-funded AR project and introduced readers to an AI-enabled self-checkout shopping cart.

1. Postmates gets pre-IPO cash

The company, an early entrant to the billion-dollar food delivery wars, raised what will likely be its last round of private capital. The $100 million cash infusion was led by BlackRock and valued Postmates at $1.85 billion, up from the $1.2 billion valuation it garnered with its unicorn round in 2018.

2. Uber’s IPO may not be as eye-popping as we expected

To be fair, I don’t think many of us really believed the ride-hailing giant could debut with a $120 billion initial market cap. And can speculate on Uber’s valuation for days (the latest reports estimate a $90 billion IPO), but ultimately Wall Street will determine just how high Uber will fly. For now, all we can do is sit and wait for the company to relinquish its S-1 to the masses.

3. Deal of the week

N26, a German fintech startup, raised $300 million in a round led by Insight Venture Partners at a $2.7 billion valuation. TechCrunch’s Romain Dillet spoke with co-founder and CEO Valentin Stalf about the company’s global investors, financials and what the future holds for N26.

4. On the market

Bird is in the process of raising an additional $300 million on a flat pre-money valuation of $2 billion. The e-scooter startup has already raised a ton of capital in a very short time and a fresh financing would come at a time when many investors are losing faith in scooter startups’ claims to be the solution to the problem of last-mile transportation, as companies in the space display poor unit economics, faulty batteries and a general air of undependability. Plus, Aurora, the developer of a full-stack self-driving software system for automobile manufacturers, is raising at least $500 million in equity funding at more than a $2 billion valuation in a round expected to be led by new investor Sequoia Capital.


Here’s your weekly reminder to send me tips, suggestions and more to kate.clark@techcrunch.com or @KateClarkTweets


5. A unicorn’s deal downsizes

WeWork, a co-working giant backed with billions, had planned on securing a $16 billion investment from existing backer SoftBank . Well, that’s not exactly what happened. And, oh yeah, they rebranded.

6. A startup collapses

After 20 long years, augmented reality glasses pioneer ODG has been left with just a skeleton crew after acquisition deals from Facebook and Magic Leap fell through. Here’s a story of a startup with $58 million in venture capital backing that failed to deliver on its promises.

7. Data point

Seed activity for U.S. startups has declined for the fourth straight year, as median deal sizes increased at every stage of venture capital.

8. Meanwhile, in startup land…

This week edtech startup Emeritus, a U.S.-Indian company that partners with universities to offer digital courses, landed a $40 million Series C round led by Sequoia India. Badi, which uses an algorithm to help millennials find roommates, brought in a $30 million Series B led by Goodwater Capital. And Mr Jeff, an on-demand laundry service startup, bagged a $12 million Series A.

9. Finally, Meet Caper, the AI self-checkout shopping cart

The startup, which makes a shopping cart with a built-in barcode scanner and credit card swiper, has revealed a total of $3 million, including a $2.15 million seed round led by First Round Capital .

Want more TechCrunch newsletters? Sign up here.

News Source = techcrunch.com

Go to Top