Categories
Security

Data leak from Russian delivery app shows dining habits of the secret police

A massive data leak from Russian food delivery service Yandex Food revealed the delivery addresses, phone numbers, names, and delivery instructions belonging to those associated with Russia’s secret police, according to findings from Bellingcat.

Yandex Food, a subsidiary of the larger Russian internet company, Yandex, first reported the data leak on March 1st, blaming it on the “dishonest actions” of one of its employees and noting that the leak doesn’t include users’ login information. Russian communications regulator Roskomnadzor has since threatened to fine the company up to 100,000 rubles (~$1,166 USD) for the leak, which Reuters says exposed the information of about 58,000 users. The Roskomnadzor also blocked access to an online map containing the data — an attempt to conceal the information of ordinary citizens, as well as those with ties to the Russian military and security services.

Researchers at Bellingcat gained access to the trove of information, sifting through it for leads on any people of interest, such as an individual linked to the poisoning of Russian opposition leader Alexey Navalny. By searching the database for phone numbers collected as part of a previous investigation, Bellingcat uncovered the name of the person who was in contact with Russia’s Federal Security Service (FSB) to plan Navalny’s poisoning. Bellingcat says this person also used his work email address to register with Yandex Food, allowing researchers to further ascertain his identity.

Researchers also examined the leaked information for the phone numbers belonging to individuals tied to Russia’s Main Intelligence Directorate (GRU), or the country’s foreign military intelligence agency. They found the name of one of these agents, Yevgeny, and were able to link him to Russia’s Ministry of Foreign Affairs and find his vehicle registration information.

Bellingcat uncovered some valuable information by searching the database for specific addresses as well. When researchers looked for the GRU headquarters in Moscow, they found just four results — a potential sign that workers just don’t use the delivery app, or opt to order from restaurants within walking distance instead. When Bellingcat searched for FSB’s Special Operation Center in a Moscow suburb, however, it yielded 20 results. Several results contained interesting delivery instructions, warning drivers that the delivery location is actually a military base. One user told their driver “Go up to the three boom barriers near the blue booth and call. After the stop for bus 110 up to the end,” while another said “Closed territory. Go up to the checkpoint. Call [number] ten minutes before you arrive!”

In a translated tweet, Russian politician and Navalny supporter, Lyubov Sobol, said the leaked information even led to additional information about Russian President Vladimir Putin’s former mistress and their alleged “secret” daughter. “Thanks to the leaked Yandex database, another apartment of Putin’s ex-mistress Svetlana Krivonogikh was found,” Sobol said. “That’s where their daughter Luiza Rozova ordered her meals. The apartment is 400 m², worth about 170 million rubles [~$1.98 million USD]!”

If researchers were able to uncover this much information based on data from a food delivery app, it’s a bit unnerving to think about the amount of information Uber Eats, DoorDash, Grubhub, and others have on users. In 2019, a DoorDash data breach exposed the names, email addresses, phone numbers, delivery order details, delivery addresses, and the hashed, salted passwords of 4.9 million people — a much larger number than those affected in the Yandex Food leak.



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Categories
Computing

How Nvidia is Using A.I. to Delivery Pizzas Faster

Nvidia announced a new tool that can help deliver your pizzas faster — yes, really — at its fall GTC 2021 event. It’s called ReOpt, and it’s a real-time logistics tool that Domino’s is already using to optimize delivery routes based on time and cost.

ReOpt is a set of logistics-planning algorithms that can find billions of routes to the same location. It utilizes heuristics powered by GPU computing to route vehicles in the most efficient way possible. It’s like Google Maps, just way more complex and designed specifically to meet the needs of last-mile delivery.

Keith Nelson/Digital Trends

Domino’s hasn’t been shy about adopting new technology. The company has been saying for years that it’s a technology company that delivers pizzas, and has adopted everything from driverless cars to in-car delivery apps to help optimize ordering and delivery. ReOpt is the next evolution of that, it seems, and it’s an increasingly important tool for how the world operates today.

Last-mile delivery compromises the final leg of a package arriving to your door. It’s where an Amazon or FedEx driver drops off your package, and it represents the most significant pain point for e-commerce sales today. About 53% of delivery costs come just from last-mile delivery, as distant homes or traffic congestion create inefficiencies in delivery routes.

And with the pandemic boosting e-commerce sales to new highs, last-mile delivery has never been more important. ReOpt is the latest in a long line of Nvidia technologies that eyes GPUs as a solution. Nvidia says it can route 1,000 packages in three seconds on a GPU, work that would normally take a CPU five minutes.

Nvidia says that ReOpt can reduce delivery costs by 15%, which it says represents “billions” in savings. To illustrate this point, Nvidia pointed to Domino’s, which was able to quickly calculate 87 billion ways to visit 14 locations using ReOpt. ReOpt is also dynamic, helping last-mile delivery workers adapt to changing traffic conditions quickly.

Although Domino’s is the first company to adopt ReOpt, this type of tool applies across a wide variety of industries. From Amazon packages to DoorDash drivers, last-mile delivery has been a hurdle for several industries, and hopefully ReOpt will provide some solutions.

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Categories
AI

Driverless delivery company Nuro nabs $600M and partners with Google

Autonomous vehicle (AV) company Nuro has raised $600 million in a series D round of funding from high-profile investors, including Tiger Global Management and Google. This brings its valuation to $8.6 billion, according to sources, up significantly from its $5 billion valuation less than a year ago.

Founded in 2016, Nuro is setting out to capitalize on shifting consumer expectations and trends that have been accelerated by the global pandemic, namely how they experience ecommerce. Customers in supported U.S. locales place their online orders directly with Nuro’s partner companies, and Nuro’s so-called “zero-occupant” autonomous delivery vehicles will transport anything from groceries to pharmacy prescriptions.

Alongside Google’s sibling company Waymo, Nuro has emerged as one of the leading players in the commercial driverless car space — last year, it became the first such company to receive a permit from the California Department of Motor Vehicles (DMV) that enabled it to charge money for its driverless delivery service.

“The arrival of ubiquitous on-demand ecommerce is changing the way we access goods,” Tiger Global partner Griffin Schroeder said in a press release. “Nuro is the bridge to an era of sustainable, low cost, autonomous local delivery.”

Above: Nuro in action

The Google factor

In addition to the funding, Nuro also revealed a five year “strategic partnership” with Google Cloud, which it said will support the “massive scale and capacity required to run self-driving simulation workloads,” as well as give Nuro access to machine learning smarts and storage for the vast amount of data generated by its vehicles.

Interestingly, the duo also revealed that they would explore other commercial opportunities together to “strengthen and transform local commerce,” though they provided no further details on what exactly this might entail.

Nuro had previously raised around $1.5 billion, and with another $600 million in the bank, the company is now well-financed to further develop and deploy its autonomous delivery service with some of the biggest brands across the U.S. Indeed, Nuro has amassed a fairly impressive roster of customers including Kroger, Domino’s, Walmart, and CVS.

Aside from lead backer Tiger Global Management and Google, Nuro’s series D round ushered in a slew of notable investors, including Kroger and SoftBank Vision Fund 1.

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Categories
AI

Amazon delivery drivers have to consent to AI surveillance in their vans or lose their jobs

Amazon is well-known for its technological Taylorism: using digital sensors to monitor and control the activity of its workers in the name of efficiency. But after installing machine learning-powered surveillance cameras in its delivery vans earlier this year, the company is now telling employees: agree to be surveilled by AI or lose your job.

As first reported by Vice, Amazon delivery drivers in the US now have to sign “biometric consent” forms to continue working for the retailing giant. Exactly what information is being collected seems to vary based on what surveillance equipment has been installed in any given van, but Amazon’s privacy policy (embedded below) covers a wide range of data.

The data that drivers must consent to be collected includes photographs used to verify their identity; vehicle location and movements (including “miles driven, speed, acceleration, braking, turns, following distance”); “potential traffic violations” (like speeding, failure to stop at stop signs, and undone seatbelts); and “potentially risky driver behavior, such as distracted driving or drowsy driving.”

It’s this last point that seems to be the most contentious. In February, Amazon announced it would start installing AI-powered cameras built by tech firm Netradyne in its delivery vans. These cameras record “100% of the time” and are supposed to identify dangerous behavior, like if a driver is yawning or checking their phone. The systems can then provide real-time feedback, telling a driver to take a break or keep their eyes on the road.

This level of micro-management — and the potential for the AI systems to get it wrong — seems to have angered some drivers. One driver speaking to the Thomson Reuters Foundation earlier this month said the cameras were an “invasion of privacy.” “We are out here working all day, trying our best already,” the driver, 22-year-old Henry Search, told the publication. “The cameras are just another way to control us.”

Other drivers have simply refused to sign, reports Vice. “It’s a heart-breaking conversation when someone tells you that you’re their favorite person they have ever worked for, but Amazon just micromanages them too much,” the owner of one Amazon delivery company told the publication.

When news of the cameras’ installation was announced earlier this year, Amazon defended the technology as a boon for safety. “We are investing in safety across our operations and recently started rolling out industry leading camera-based safety technology across our delivery fleet,” an Amazon spokesperson told The Verge. “This technology will provide drivers real-time alerts to help them stay safe when they are on the road.”

Previously, Amazon’s deployment of this sort of technology has mostly focused on its warehouse workers, where “pickers” have to fulfill orders while being timed by handheld scanners. The company has patented wristbands that even track workers’ hands in real-time, using haptic feedback to nudge them when they reach for an incorrect item. And it recently expanded its use of opt-in “gamification” techniques that hustle workers into ever greater efforts in exchange for digital rewards.

In a statement given to The Verge, Amazon spokesperson Deborah Bass said that the cameras were only there “to help drivers and the communities where we deliver safe.” Bass said that in pilots of the technology from April to October 2020, over more than two million miles of driving, “accidents decreased 48 percent, stop sign violations decreased 20 percent, driving without a seatbelt decreased 60 percent, and distracted driving decreased 45 percent. Don’t believe the self-interested critics who claim these cameras are intended for anything other than safety.”

Update, Wednesday March 24th, 12:00PM ET: Story updated with statement from Amazon.

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Categories
AI

How AI is helping Nvidia improve U.S. Postal Service delivery

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Nvidia this week detailed a partnership with the U.S. Postal Service to transform the latter’s mail operations with AI. According to Nvidia, its machine learning resources and tools enabled the Postal Service to process over 20 terabytes of images a day from more than 1,000 mail processing machines using 195 edge servers.

In 2019, the Postal Service had a requirement to identify and track items in its over 100 million pieces of daily mail. Data scientists at the organization thought they could expand an image analysis system developed internally into something broader, with edge AI servers strategically located at the Post Office’s processing centers. The hope was that the system would enable the Postal Service to analyze billions of images of mail and share the insights quickly over the network.

Recruiting half a dozen architects at Nvidia and other companies, the Postal Service arrived at the deep learning models it needed after a three-week sprint. The work was the genesis of the Edge Compute Infrastructure Program, a distributed edge AI system that’s running on the NVIDIA EGX platform at the Postal Service today.

Open source software from Nvidia, the Triton Inference Server, acts as a sort of digital mailperson between the edge servers, delivering the necessary AI models on demand. According to the Postal Service’s analysis, a computer vision task that would have required two weeks on a network of servers with 800 processors can now be accomplished in 20 minutes on the four NVIDIA V100 Tensor Core GPUs in one of the edge servers, HPE Apollo 6500s.

Model serving

Triton automates the delivery of AI models to different Postal Service systems that may have unique configurations of GPUs and CPUs supporting deep learning frameworks. An app that checks for mail items alone requires coordinating the work of more than half a dozen deep learning models, each checking for specific features.

Nvidia USPS

Above: Cameras mounted on the sorting machines capture addresses, barcodes, and other data, such as hazardous materials symbols.

Image Credit: U.S. Postal Service

Departments across the Postal Service, from enterprise analytics to finance and marketing, have spawned ideas for as many as 30 apps for ECIP, Nvidia says. One would determine if a package carries the right postage for its size, weight, and destination. Another would decipher a barcode, even in the presence of damage.

The plan is to get several new AI-powered apps up and running this year. Nvidia and the Postal Service say the barcode model could be on ECIP as soon as this summer.

Next-gen OCR

Seeking further improvements to its mail processing pipeline, the Postal Service put out a request for what could be the next app for ECIP — one that uses optical character recognition (OCR). In the past, the agency would have bought expensive new hardware and software or used a public cloud service, which takes a lot of bandwidth and has significant costs. This time, leaning on Nvidia expertise, the company deployed an AI-based OCR system in a container on ECIP managed by Kubernetes and served by Triton.

In the early weeks of the pandemic, operators rolled out containers to get the first systems running as others were being delivered, updating them as the full network was installed. Nvidia was awarded the contract in September 2019, started deploying systems last February, and finished most of the hardware by August.

Nvidia USPS

Above: AI algorithms were developed on NVIDIA DGX servers at a U.S. Postal Service Engineering facility.

Image Credit: Nvidia

The new solutions could help the Postal Service improve delivery standards, which have fallen over the past year. In mid-December, during the last holiday season, the agency delivered as little as 62% of first-class mail on time — the lowest level in years. The rate rebounded to 84% by the week of March 6 but remained below the agency’s target of about 96%.

The Postal Service has blamed the pandemic and record peak periods for much of the poor service performance.

“The models we have deployed so far help manage the mail and the Postal Service — it helps us maintain our mission,” Todd Schimmel — the manager who oversees Postal Service systems, including ECIP — said in a press release. “It used to take eight or 10 people several days to track down items, now it takes one or two people a couple of hours. This has a benefit for us and our customers, letting us know where a specific parcel is at — it’s not a silver bullet, but it will fill a gap and boost our performance … We’re at the very beginning of our journey with edge AI.”

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Categories
Tech News

Amazon may start asking even more of its delivery drivers

Amazon is reportedly set to trial a new home assembly service for larger items, where delivery drivers would also put together furniture, appliances, or other larger items. The move, which is said to be planned for just a handful of markets as the online retail behemoth gauges popularity and feasibility, could make home shopping even easier, though there are concerns that delivery drivers themselves may face impractical expectations.

Online shopping has surged during the pandemic, and Amazon has seen a considerable share of that extra business. Its subscription plan Amazon Prime, for example, surged by 50 million members in the space of a year, bringing the total to 200 million.

The retailer’s ambitions, however, go beyond dropping items off at the doorstep. While you can currently schedule the delivery of a particularly large item, and even have it left in a specific room, Amazon is said to be preparing an even more hands-on service. The assembly option would see the delivery person actually put the item together in the home, Bloomberg reports.

According to people familiar with the plans, they say, Amazon is looking to trial the premium service in Virginia and two other unnamed markets. Unlike Amazon Home Services – which offers recommended local contractors booked through Amazon’s system – assembly and installation of the purchases would be handled by the company’s own delivery staff.

Still, there’d be a limit to what could be offered. Amazon Home Services, for example, includes options for tasks like installing electric car chargers, something which would be beyond the remit of a delivery driver. Instead, it’s suggested, Amazon sees it more around doing basics like putting together sofas and living room furniture, or installing a straightforward appliance like a washing machine or dishwasher.

Amazon has declined to comment on the leak, but according to Bloomberg there’s some consternation among the company’s delivery drivers about just what might be expected of them. The retailer has already faced criticism about working conditions for delivery staff, with accusations of grueling workloads that leave them little time for bathroom breaks. Among the concerns were just how long Amazon managers might allot for assembly and installation, and the safety of spending extended periods inside customers’ homes during the pandemic which has helped make online shopping so popular.

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Categories
AI

How Yandex plans to expand its autonomous robot delivery service

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The COVID-19 health crisis in much of the U.S. seems likely to hasten the adoption of self-guided robots and drones for goods transportation. They require disinfection, which companies like Kiwibot, Starship Technologies, and Postmates are conducting manually with sanitation teams. But in some cases, delivery rovers like Refraction’s could minimize the risk of spreading disease. Recent market reports from Allied Market Research and Infiniti estimate that annual growth in the last-mile delivery sector over the next 10 years will exceed 14%, with the autonomous delivery segment projected to grow at over 24%, from $11.9 billion in 2021 to more than $84 billion globally by 2031.

As something of a case in point, Yandex says that in early February its Yandex.Rovers autonomous delivery program reached a milestone: 4,000 deliveries since April 2020. After launching at Yandex’s headquarters and the Moscow district of Skolkovo last year, Yandex says its fleets of robots have delivered documents, packages, and more to customers.

Yandex soon plans to pilot the service in Ann Arbor, Michigan, which will be the company’s first autonomous delivery site in the U.S. Ahead of the deployment, VentureBeat spoke with Dmitry Polishchuk, head of driverless cars, about how Yandex is approaching the technology stack for its delivery network and the innovations that might be applied to projects elsewhere at the company.

Early days

Yandex first took the wraps off Yandex.Rover in November 2019. A project within its self-driving division, Yandex.Rover was created to start by delivering small packages before eventually handling food as part of Yandex’s Yandex.Eat platform and groceries from Yandex.Lavka.

Yandex’s six-wheeled rover, which is roughly the size of a small suitcase, taps some of the tech at the core of the company’s autonomous cars to travel “at the speed of a pedestrian.” It’s capable of navigating around obstacles in most weather conditions during daylight or darkness, but in the areas where it’s currently deployed, Yandex says its activities can be monitored by a remote operator.

Yandex.Rover

Customers use an app to arrange deliveries by setting a dropoff destination, after which one of Yandex’s rovers travels on sidewalks and crosses intersections within a radius of “several kilometers.” From the same app, shoppers can remotely open the robot’s storage compartment and monitor its movements on a map or connect with a Yandex engineer for assistance.

“The rovers are operated by the same technology stack as our self-driving cars. We have adopted it for this new platform that utilizes the same approaches and solutions,” Polishchuk told VentureBeat via email. “The sensor configuration on the rover is different than the cars, but these are still the same types of sensors. This allows us to reuse perception models from cars to detect vehicles, pedestrians, static obstacles, and other road objects, as well as use, existing labeling, and training pipelines for developing new models.”

In-house tooling

According to Polishchuk, Yandex draws on a number of tools developed in-house to refine the performance of its delivery rovers. One is Yandex.Toloka, a crowdsourced dataset labeling service that provides the ability to annotate data at scale. Another is a web app — Nirvana — that creates reproducible training and testing pipelines for machine learning models, which feeds into a storage and computation cloud called Yt that’s designed for analytics.

“Using proprietary solutions allows us to have these tools be quickly adjusted or fine-tuned for the specific needs of the self-driving team,” Polishchuk explained. “For example, in Toloka, we’ve created special tools for labeling objects in 3D using joint data from lidars, cameras, and radars. And of course, using our own cloud infrastructure is significantly less expensive than using external services.”

In the case of Yandex.Rover, Yandex’s self-driving team was able to repurpose some of the prediction models developed for the company’s cars to its robots, for purposes like predicting where pedestrians might walk. The team also uses the simulator originally developed to test the cars’ software for validating and fine-tuning the rovers’ algorithms.

Yandex.Rover

“The machine learning-based solutions greatly help our cars [and rovers] predict other agents’ behavior in situations that are not strictly regulated by traffic rules. In comparison to cars, human traffic on sidewalks is less structured and thus creates even more uncertainty,” Polishchuk said. “We are using the latest machine learning-based motion-planning solutions to help robots safely and intelligently navigate busy sidewalks.”

Mapping is another area where Yandex’s autonomous cars have helped its robots. The rovers need high-definition maps in order to position themselves in the real world, and portions of the maps can be constructed with the help of the cars’ sensors. The sensors are sensitive enough to capture sidewalk surfaces — the robots only need to enhance the map where the view from the street is obscured by other objects.

Hardware development

Yandex’s delivery fleet currently comprises about 35 robots, most of which are making deliveries from Yandex.Eats and Yandex.Lavka in four Moscow districts and the town of Innopolis. A few additional robots are being used for testing purposes and to map new delivery locations, Polishchuk says.

During the first few months of 2020, Yandex’s self-driving team began testing various hardware and sensor configurations for the rovers, eventually settling on an ARM platform equipped with a lidar sensor, sonar, cameras, and radars on the sides to detect vehicles when crossing a street. Deliveries during the winter months revealed new challenges that led to upgrades, including an adjustment to the rovers’ speed-planning system that could better handle icy walkways. The team also improved power consumption so that the robots could drive up to 10 hours on a charge, even in cold, snowy wintery weather.

Yandex.Rover

The rovers’ form factor also saw some changes in response to customer feedback. For example, its storage unit expanded in size and gained a lid that opens and closes automatically so that each delivery is contactless.

Future work

Beyond Ann Arbor, Yandex says it is shipping rovers to Israel and South Korea for autonomous delivery testing. In the future, Yandex envisions the robots making their way into the ecommerce platforms for order fulfillment and delivery or the company’s own warehouses and datacenters to transport cargo. Yandex is now in “active talks” about partnerships with companies in Russia and abroad, according to Polishchuk.

Beyond Yandex, startups like Marble, Starship, Nuro, Robomart, Boxbot, FedEx, Refraction AI, Dispatch, and Robby are vying for a slice of the self-driving robot delivery market. Amazon is testing its Scout robots in parts of Southern California, expanding the tech giant’s pilot program from Snohomish County, Washington. And in a sign of the segment’s competitiveness, Uber-owned Postmates X, the division of Postmates developing autonomous delivery robots, recently spun off into a separate company.

“Pandemic is changing last-mile delivery both on the side of customers and business. Demand for contactless delivery changed the protocols of couriers’ interaction with customers, and robots perfectly fit into this new reality,” Polishchuk said. “We think that the ideal combination of human couriers and rovers is in an efficient split of the orders. Rovers can do hyperlocal orders close to a shop or a restaurant, while humans can deliver the rest — as they cover long distances faster — using bicycles, scooters, or public transportation … Such a split of the orders between humans and robots can help services improve current last-mile delivery time, even with [the] constantly growing demand.”

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AI

Delivery startup Refraction AI raises $4.2M to expand service areas

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Refraction AI, a company developing semi-autonomous delivery robots, today announced that it raised $4.2 million in seed funding led by Pillar VC. Refraction says that the proceeds will be used for customer acquisition, geographic expansion, and product development well into the next year.

The worsening COVID-19 health crisis in much of the U.S. seems likely to hasten the adoption of self-guided robots and drones for goods transportation. They require disinfection, which companies like Kiwibot, Starship Technologies, and Postmates are conducting manually with sanitation teams. But in some cases, delivery rovers like Refraction’s could minimize the risk of spreading disease. Recent market reports from Allied Market Research and Infiniti  estimate that annual growth in the last-mile delivery sector over the next 10 years will exceed 14%, with the autonomous delivery segment projected to grow at over 24%, from $11.9 billion in 2021 to more than $84 billion globally by 2031.

Launched in July 2019, Refraction was cofounded by Matt Johnson-Roberson and Ram Vasudevan, both professors at the University of Michigan. Working alongside several retail partners, people within a few-mile radius can have orders delivered by Refraction’s REV-1 robot. After customers order through a dedicated website, Refraction’s employees load the vehicles at the store, and recipients receive text message updates, along with a code to open the robot’s storage compartment when it arrives.

REV-1, which is approximately the size of an electric bicycle and is legally categorized as an ebike, weighs approximately 100 pounds and stands roughly 4 feet tall, including its three wheels. It travels an average 10 to 15 miles per hour with a very short stopping distance, and the compartment holds about six bags of groceries.

Refraction AI

REV-1’s perception system comprises 12 cameras, in addition to redundant radar and ultrasound sensors — a package the company claims costs a fraction of the lidar sensors used in rival rovers. The robot can navigate in inclement weather, including rain and snow, and it doesn’t depend on high-definition maps for navigation.

Prior to a partnership with Ann Arbor, Michigan-based Produce Station, REV-1 had been delivering exclusively from Ann Arbor restaurants, including Miss Kim and Tio’s Mexican Cafe, during lunchtime as part of a three-month pilot. The company charges the restaurant a flat $7.50, and Refraction’s over 500 customers pay a portion of that fee if the business chooses. (Tips go directly to Refraction’s partners.)

As of May 2020, Refraction had eight robots running in Ann Arbor, and it expects to have over 20 within the next few weeks. The latest investment brings its total raised to date to over $10 million.

“Last-mile delivery is the quintessential example of a sector that is ripe for innovation, owing to a powerful confluence of advancing technology, demographics, social values and consumer models. Conventional approaches have left businesses and consumers with few choices in this new environment as they struggle to keep pace with surging demand — burdened by the costs, regulatory, and logistical challenges of a legacy infrastructure,” Refraction CEO Luke Schneider, who took the helm in fall 2020, said in a press release. “Our platform uses technology that exists today in an innovative way, to get people the things they need, when they need them, where they live. And we’re doing so in a way that reduces business’ costs, makes roads less congested, and eliminates carbon emissions.”

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Tech News

Uber is about to acquire a big US alcohol delivery service for $1.1bn

Uber has announced that it will acquire Drizly, an alcohol delivery service that offers on-demand access to adult beverages in hundreds of markets across the US. The Drizly platform itself won’t be going away, but Uber notes that in the future, it will integrate the alcohol delivery platform with its own Uber Eats delivery service.

According to Uber, it has agreed to acquire Drizly for around $1.1 billion in the form of cash and stock. Once the acquisition is complete, Drizly will become a wholly-owned Uber subsidiary, eventually making its way within the Uber Eats app while also remaining available through the standalone Drizly mobile app.

Once the integration arrives, Uber Eats users will have greatly expanded on-demand alcohol delivery options — while you can currently get alcohol delivered with your Uber Eats order, it comes from the restaurant you order your meals from, assuming they offer such products.

Drizly, meanwhile, is a platform through which you can order wine, beer, liquor, and other alcoholic goods from local stores and have them delivered on your behalf using a Drizly delivery driver. Once the platform is integrated with Uber Eats, you’ll be able to place the same type of orders through that platform.

Drizly currently offers alcohol delivery in around 1,400 cities spanning most of the US. Assuming the regulatory approval and other business matters are settled as expected, Uber says the acquisition deal will likely close sometime in the first half of this year.

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Categories
AI

Wingcopter raises $22 million to ramp up delivery drone production

Wingcopter, a Darmstadt, Germany-based drone manufacturer, today announced that it raised $22 million in a funding round led by Xplorer Capital and Futury Regio Growth Fund. The company says it will use the proceeds to expand its health care-related activities (including the distribution of COVID-19 vaccines), prepare for the launch of its next-gen drones, set up a partially automated production facility, and grow its team at a new U.S. complex.

The commercial drone market was already accelerating, with reports the industry would grow more than fivefold by 2026 from the $1.2 billion it was reportedly worth in 2018. But the pandemic has increased demand for drone services in areas such as medical supply deliveries and site inspections. Honeywell, a major supplier of aerospace systems, launched a new business unit covering drones, air taxis, and unmanned cargo delivery vehicles. And last week, startup American Robotics snagged the first-ever U.S. Federal Aviation Administration (FAA) approval to fly automated drones beyond the line of sight.

Wingcopter, which was founded in 2017 by Ansgar Kadura, Jonathan Hesselbarth, and Tom Plümmer, aims to develop drones that improve the lives through commercial and humanitarian applications. The company focuses on the delivery of medical goods, packages, and food as well as inspection, inter-site logistics, and mapping via photogrammetry using aircraft that operates in wind gusts over 45 miles per hour, reaches speeds upwards of 150 miles per hour (in fixed-wing mode), and carries payloads weighing up to 13 pounds.

“In 2015, I came back from a longer stay in Ghana where I had seen the negative consequences of poorly developed healthcare supply chains,” Plümmer told VentureBeat via email. “As I already had some experience with commercial drone services, I fell in love with the idea of using drones for the delivery of urgently needed medical goods to create positive social impact. Not being able to build drones myself, I was looking for an engineer to team up. Shortly after, I was introduced to Hesselbarth, an engineer with a focus on aerospace as well as an outstanding inventor … In 2017, we officially founded Wingcopter as properly registered company together with a third partner, Ansgar Kadura, who helped set up our first medical delivery project in Tanzania and who is now heading our global flight operations.”

Wingcopter

Wingcopter’s electric-powered drones — among them the Wingcopter 178 Heavy Lift — feature a tilt-rotor mechanism that enables them to take off and land vertically, like multicopters. The company claims they can reach a range of up to 75 miles without a payload (or 88 miles with a payload) and an altitude of roughly 3.1 miles while remaining relatively quiet.

In a collaboration with Merck and the Frankfurt University of Applied Sciences, Wingcopter recently performed what it claims was the world’s first beyond-visual-line-of-sight flight between production facilities, flying lab samples 15.5 miles from a Merck plant in Gernsheim to the company’s headquarters in Darmstadt. And last year, Wingcopter announced it would collaborate with UPS subsidiary UPS Flight Forward to design package delivery drones, ultimately toward earning regulatory certification for a Wingcopter aircraft to make commercial delivery flights in the U.S.

As a part of its humanitarian efforts, Wingcopter delivered insulin to an Irish island in the North Sea that’s frequently cut off from the mainland due to inclement weather. On the South Sea island of Vanuatu, the company partnered with the local ministry of health, UNICEF, and health care providers to set up an on-demand vaccines supply, delivering children’s vaccines on-demand from one central hub to 19 remote villages and reducing waiting times from up to 7 hours to a few minutes. In Scotland, Wingcopter launched a drone-based COVID-19 response trial on behalf of the National Health Service Scotland to provide the Isle of Mull with tests, ostensibly cutting delivery times from 6 hours to 15 minutes. And Wingcopter says it’s working with the African Drone and Data Academy to establish a delivery drone network in Malawi, where the company has delivered nearly 200 pounds of medicine to remote areas affected by flooding and started a long-term project — Drone + Data — to improve local health care supply chains.

In the near term, Wingcopter, which has raised $25 million to date and employs over 100 people, says it plans to expand its drone-delivery-as-a-service offerings, which give customers access to its five-continent, fully managed drone delivery network. The company also plans to scale up production at its new 77,500-square-foot headquarters in Weiterstadt, Germany, and hire engineers in the areas in the fields of flight testing, certification, production, software development, ground and flight control software, embedded systems, architecture, and cloud infrastructure.

“We managed to bootstrap and grow the team to over 30 employees just based on revenues, before we decided to accept our first VC investment by Corecam Capital Partners in late 2019 to be able to scale faster,” Plümmer added. “As we are expanding our business model from a pure OEM to OEM-and-drone-as-a-service, we generate more and more recurring revenues for our drone operations services. We have a solid customer base and already sold drones and services … With the fresh funding [and] the new and game-changing Wingcopter generation to be released within the next months, we are now ready to establish partnerships centering around other fully automated delivery applications as well, for example. in groceries, ecommerce, inter-site logistics, or food.”

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