Fender’s new American Acoustasonic Telecaster has a unique digital system on board that gives it a tremendously varied sonic palette.
Feed: All Latest
DJI, the world’s leading maker of consumer drones, said today that extensive corruption discovered within the company could lead to losses as great as $ 150 million in the 2018 financial year. The exact nature of the corruption is not stated, but it seems to involve dozens of people at the least.
The China Securities Journal, a state-operated finance-focused newspaper, got hold of an internal company report on a corruption investigation that said some 40 people had been investigated so far, but the numbers may also be as high as 100.
Reuters confirmed with the company that it “set up a high-level anti-corruption task force to investigate further and strengthen anti-corruption measures,” and that “a number of corruption cases have been handed over to the authorities, and some employees have been dismissed.”
When contacted for details, DJI offered a statement (just after this post went live) partly explaining the situation:
During a recent investigation, DJI itself found some employees inflated the cost of parts and materials for certain products for personal financial gain. We took swift action to address this issue, fired the bad actors, and contacted law enforcement officials. We continue to investigate the situation and are cooperating fully with law enforcement’s investigation.
We are taking steps to strengthen internal controls and have established new channels for employees to submit confidential and anonymous reports relating to any violations of the company’s ethical and workplace conduct policies.
It’s a little hard to believe that people padding invoices and giving sweetheart deals to certain contractors for kickbacks could amount to more than a million dollars per person involved, but then again, DJI makes a lot of hardware and a few well-placed people could siphon off quite a bit.
Google is removing apps from Google Play that request permission to access call logs and SMS text message data but haven’t been manually vetted by Google staff.
The search and mobile giant said it is part of a move to cut down on apps that have access to sensitive calling and texting data.
Google said in October that Android apps will no longer be allowed to use the legacy permissions as part of a wider push for developers to use newer, more secure and privacy minded APIs. Many apps request access to call logs and texting data to verify two-factor authentication codes, for social sharing, or to replace the phone dialer. But Google acknowledged that this level of access can and has been abused by developers who misuse the permissions to gather sensitive data — or mishandle it altogether.
“Our new policy is designed to ensure that apps asking for these permissions need full and ongoing access to the sensitive data in order to accomplish the app’s primary use case, and that users will understand why this data would be required for the app to function,” wrote Paul Bankhead, Google’s director of product management for Google Play.
Any developer wanting to retain the ability to ask a user’s permission for calling and texting data has to fill out a permissions declaration.
Google will review the app and why it needs to retain access, and will weigh in several considerations, including why the developer is requesting access, the user benefit of the feature that’s requesting access and the risks associated with having access to call and texting data.
Bankhead conceded that under the new policy, some use cases will “no longer be allowed,” rendering some apps obsolete.
So far, tens of thousands of developers have already submitted new versions of their apps either removing the need to access call and texting permissions, Google said, or have submitted a permissions declaration.
Developers with a submitted declaration have until March 9 to receive approval or remove the permissions. In the meantime, Google has a full list of permitted use cases for the call log and text message permissions, as well as alternatives.
The last two years alone has seen several high-profile cases of Android apps or other services leaking or exposing call and text data. In late 2017, popular Android keyboard ai.type exposed a massive database of 31 million users, including 374 million phone numbers.
Robots are amazing things, but outside of their specific domains they are incredibly limited. So flexibility — not physical, but mental — is a constant area of research. A trio of new robotic setups demonstrate ways they can evolve to accommodate novel situations: using both “hands,” getting up after a fall, and understanding visual instructions they’ve never seen before.
The robots, all developed independently, are gathered together today in a special issue of the journal Science Robotics dedicated to learning. Each shows an interesting new way in which robots can improve their interactions with the real world.
On the other hand…
First there is the question of using the right tool for a job. As humans with multi-purpose grippers on the ends of our arms, we’re pretty experienced with this. We understand from a lifetime of touching stuff that we need to use this grip to pick this up, we need to use tools for that, this will be light, that heavy, and so on.
Robots, of course, have no inherent knowledge of this, which can make things difficult; it may not understand that it can’t pick up something of a given size, shape, or texture. A new system from Berkeley roboticists acts as a rudimentary decision-making process, classifying objects as able to be grabbed either by an ordinary pincer grip or with a suction cup grip.
A robot, wielding both simultaneously, decides on the fly (using depth-based imagery) what items to grab and with which tool; the result is extremely high reliability even on piles of objects it’s never seen before.
It’s done with a neural network that consumed millions of data points on items, arrangements, and attempts to grab them. If you attempted to pick up a teddy bear with a suction cup and it didn’t work the first ten thousand times, would you keep on trying? This system learned to make that kind of determination, and as you can imagine such a thing is potentially very important for tasks like warehouse picking for which robots are being groomed.
Interestingly, because of the “black box” nature of complex neural networks, it’s difficult to tell what exactly Dex-Net 4.0 is actually basing its choices on, although there are some obvious preferences, explained Berkeley’s Ken Goldberg in an email.
“We can try to infer some intuition but the two networks are inscrutable in that we can’t extract understandable ‘policies,’ ” he wrote. “We empirically find that smooth planar surfaces away from edges generally score well on the suction model and pairs of antipodal points generally score well for the gripper.”
Now that reliability and versatility are high, the next step is speed; Goldberg said that the team is “working on an exciting new approach” to reduce computation time for the network, to be documented, no doubt, in a future paper.
ANYmal’s new tricks
Quadrupedal robots are already flexible in that they can handle all kinds of terrain confidently, even recovering from slips (and of course cruel kicks). But when they fall, they fall hard. And generally speaking they don’t get up.
The way these robots have their legs configured makes it difficult to do things in anything other than an upright position. But ANYmal, a robot developed by ETH Zurich (and which you may recall from its little trip to the sewer recently), has a more versatile setup that gives its legs extra degrees of freedom.
What could you do with that extra movement? All kinds of things. But it’s incredibly difficult to figure out the exact best way for the robot to move in order to maximize speed or stability. So why not use a simulation to test thousands of ANYmals trying different things at once, and use the results from that in the real world?
This simulation-based learning doesn’t always work, because it isn’t possible right now to accurately simulate all the physics involved. But it can produce extremely novel behaviors or streamline ones humans thought were already optimal.
At any rate that’s what the researchers did here, and not only did they arrive at a faster trot for the bot (above), but taught it an amazing new trick: getting up from a fall. Any fall. Watch this:
It’s extraordinary that the robot has come up with essentially a single technique to get on its feet from nearly any likely fall position, as long as it has room and the use of all its legs. Remember, people didn’t design this — the simulation and evolutionary algorithms came up with it by trying thousands of different behaviors over and over and keeping the ones that worked.
Ikea assembly is the killer app
Let’s say you were given three bowls, with red and green balls in the center one. Then you’re given this on a sheet of paper:
As a human with a brain, you take this paper for instructions, and you understand that the green and red circles represent balls of those colors, and that red ones need to go to the left, while green ones go to the right.
This is one of those things where humans apply vast amounts of knowledge and intuitive understanding without even realizing it. How did you choose to decide the circles represent the balls? Because of the shape? Then why don’t the arrows refer to “real” arrows? How do you know how far to go to the right or left? How do you know the paper even refers to these items at all? All questions you would resolve in a fraction of a second, and any of which might stump a robot.
Researchers have taken some baby steps towards being able to connect abstract representations like the above with the real world, a task that involves a significant amount of what amounts to a sort of machine creativity or imagination.
Making the connection between a green dot on a white background in a diagram and a greenish roundish thing on a black background in the real world isn’t obvious, but the “visual cognitive computer” created by Miguel Lázaro-Gredilla and his colleagues at Vicarious AI seems to be doing pretty well at it.
It’s still very primitive, of course, but in theory it’s the same toolset that one uses to, for example, assemble a piece of Ikea furniture: look at an abstract representation, connect it to real-world objects, then manipulate those objects according to the instructions. We’re years away from that, but it wasn’t long ago that we were years away from a robot getting up from a fall or deciding a suction cup or pincer would work better to pick something up.
The papers and videos demonstrating all the concepts above should be available at the Science Robotics site.
The company needs more cash for content and global expansion—and it’s still cheaper than a lot of streaming services.
Feed: All Latest
Investors are still pouring millions into scooter startups, albeit sometimes at flat valuations. At the same time a little cash is flowing the other way, in cases where cities have realized the importance of prioritizing the needs of the local environment and its citizens, over and above the ambitions of VCs for a swift and lucrative exit.
Scooter startups affected by such regulatory bumps in the road are, unsurprisingly, rather less keen to shout about this sort of policy friction and the negative cash and ride flow it generates.
The startup is so new it doesn’t even have scooters available for public hire yet. But it’s already had some of its ‘test’ rides removed by police and been fined for breaking scooter sharing rules.
If it was hoping to copy-paste from an Uber 1.0 playbook, things aren’t looking good for Reby. (Indeed, that’s a very tatty manual in most places these days.)
Spain’s capital city Madrid also forced a temporary suspension on scooter sharing startups recently, as we reported last month, after changes to mobility laws that tighten the screw on scooter sharing — requiring already operational startups to tweak how their rides operate in order to come into compliance.
While Madrid authorities haven’t banned scooter sharing entirely, they have imposed more limits on where and how they can be used, thereby injecting fresh friction into the business model.
But compared to Barcelona that’s actually a free ride. Things aren’t so much bumpy as roadblocked entirely for scooter sharing in the latter city where regulations adopted by Barcelona town hall in 2017 essentially ban the on-demand scooter model, at least as startups prefer to operate it.
These rules require companies that wanting to offer scooters for hire must provide a guide with the ride (one guide per maximum two people), as well as a helmet. They must also verify that the person to whom the vehicle is hired has the ability to ride it properly.
Rides might scale if you’re able to litter enough cheap and easy scooters all over the urban place but a (human) guide per two rides definitely does not.
Yet, as we’ve written before, there’s no shortage of patinetes electronics weaving around Barcelona’s often narrow and crowded streets. Most of these are locally owned though. And the town hall appears to prefer it that way. After all, people who own high tech scooters aren’t usually in a rush to ditch them in stupid places.
In its 2017 by-law regulating various personal mobility vehicles (PMVs) — including, but not limited to, two-wheeled electric scooters — the city council said it wanted to foster safer and sustainable usage of scooters and other PMVs, pointing to “the growing presence of this new mobility which is taking up more and more road space”.
“Barcelona City Council is committed to a sustainable city mobility model which gives priority to journeys on foot, by bicycle or on public transport,” it added, setting out what it dubbed a “pioneering regulation” that forbids e-scooter use on pavements; imposes various speed restrictions; and gives priority to pedestrians at all times.
Scooters can also only be parked in authorized parking places, with the council emphasizing: “It is forbidden to tie them to trees, traffic lights, benches or other items of urban furniture when this could affect their use or intended purpose; in front of loading or unloading zones, or in places reserved for other users, such as persons with reduced mobility; in service areas or where parking is prohibited, such as emergency exits, hospitals, clinics or health centres, Bicing [the local city bike hire scheme] zones and on pavements where this might block the path of pedestrians.”
There’s more though: The regulation also targets scooter sharing startups seeking to exploit PMVs as a commercial opportunity — with “special conditions for economic activities”.
These include the aforementioned guide, helmet and minimum skill level rule. There’s also a registration scheme for PMVs being used for economic activity which allows city police to scan a QR code that must be displayed on the ride to check it conforms to the regulation’s technical requirements. How’s that for a smart use of tech?
“There may be specific restrictions in specific areas and districts where there is a lot of pressure from these kinds of vehicles or they pose a specific problem,” the council also warns, giving itself further leeway to control PMVs and ensure they don’t become a concentrated nuisance.
Despite what are clear, strict and freshly imposed controls on scooter sharing, that hasn’t stopped a couple of smaller European startups from trying their luck at getting rentable rubber on Catalan carrers anyway — perhaps encouraged by demonstrable local appetite to scoot (that and the lack of any big Birds).
The opportunity probably looks tantalizing; a dense urban environment that’s also a tourist hotspot with clement weather, lots of two-wheel-loving locals and a small but vibrant tech scene.
In Reby’s case, the very early stage Catalan startup, whose co-founders’ LinkedIn profiles suggests the business was founded last July, has a website and not much else at this point, aside from its ambitions to follow in the wheeltracks of Bird, Lime et al.
Nonetheless it has racked up fines worth €5,300 (just over $ 6,000), according to town hall sources, after being deemed to have breached the city’s PMV rules.
Reby had put out up to a hundred scooters in Barcelona for ten days, according to El Pais, padlocking them to bike anchors (with a digital password for unchaining delivered via app) — presumably in the hopes of locating a grey area in the regulation and unlocking the pile em’ high, rent em’ cheap dockless on-demand scooter model that’s disrupted cities elsewhere.
But the Ayuntamiento de Barcelona was unimpressed. Its new by-law brought in a penalty system with fines of up to €100 for minor infringements, up to €200 for serious infringements and up to €500 for very serious infringements. (We understand Reby received 53 sanctions for minor infringements — costing €100 apiece).
Penalties are levied per infringement, so essentially per scooter deployed on the street. And while a few thousand euros might not sound that much of a big deal, the more scooters you scatter the higher the fine scales. And of course that’s not the kind of scaling these startups are scooting for.
We asked Reby for its version of events but it didn’t want to talk about it. A spokesman told us it’s still very early days for the business, adding: “We are a very small team and haven’t launched yet officially. We are doing some tests in Barcelona.”
A more established European scooter startup, Berlin-based Wind, has also clashed with city hall. El Pais reports it had around 100 scooters seized by police last August, also after abortively trying to put them on the streets for hire.
Town hall sources told us that, in Wind’s case, the company’s rides were removed immediately by police, not even lasting a day — so there wasn’t even the chance for a fine to be issued. (We contacted Wind for comment on the incident but it did not respond.)
The bottom line is legislative hurdles won’t simply vanish because startups wish it.
Where scooters are concerned city authorities aren’t dumb and can also move surprisingly fast. The dumping grounds some urban spaces have become after being flooded with unwanted dockless rides by overfunded startups chasing scale via max disruption (and minimum environmental sensitivity) certainly hasn’t gone unnoticed.
At the same time, keeping streets flowing, uncluttered and safe is the bread and butter business of city councils — naturally pushing PMVs up the regulatory agenda.
You also don’t have to look far for tragic stories vis-a-vis scooters. Last summer a 90-year-old pedestrian was killed in a suburb of Barcelona after she was hit by two men riding an electric scooter. In another incident in a nearby town a 40-year-old scooter rider also reportedly died after falling off her ride and being run over by a truck.
The risks of PMVs mingling with pedestrians and more powerful road vehicles are both clear and also not about to disappear. Not without radical action to expel most non-PMV vehicles from city centers to expand the safe (road) spaces where lower powered, lighter weight PMVs could operate. (And no major cities are proposing anything like that yet).
Add to that, in European cities like Barcelona, where there has already been major investment in public transport infrastructure, there’s a clear incentive to funnel residents along existing tracks, including by tightly controlling new and supplementary forms of micro-mobility.
If the Barcelona city council has one potential blind spot where urban mobility is concerned it’s air pollution. Like most dense urban centers the city often suffers terribly from this. And savvy scooter companies would do well to be pressing on that policy front.
But there’s little doubt that would-be fast-follower scooter clones have their work cut out to scale at all, let alone go the distance and get big enough to attract acquisitive attention from the category’s beefed up early movers.
Even then, for the Birds and Limes of the scooter world, multi-millions in funding may buy runway and the opportunity to scoot for international growth but policy roadblocks aren’t the kind of thing that money alone can shift.
Scooter startups need to sell cities on the potential civic benefits of their technology, by demonstrating how PMVs could replace dirtier alternatives that are already clogging roads and having a deleterious impact on urban air quality, as part of a modern and accessible mobility mix.
But that kind of lobbying, while undoubtedly benefiting from local connections, takes money and time. So there’s no shortage of challenge and complexity in the road ahead for scooter startups, even as — as we wrote last month — the investment opportunity is shrinking, with investors having now placed their big bets.
In some cities, scooter ownership also appears to be growing in popularity which will also eat into any sharing opportunities.
One regional investor from an early stage Madrid-based fund that we spoke to about scooters had no qualms at having passed over the space. “We’ve looked at various companies in the space and in Spain but we’re not very attracted by the market given our fund size, competition and regulation question marks,” KFund‘s Jamie Novoa told us.
So those entrepreneurs still dreaming of fast following the likes of Bird, Lime and Spin may find the race they were hoping to join is already over and park gates being padlocked shut.
WIRED’s Gadget Lab team kicks off the new year with a wrap-up of the year’s biggest electronics show. Plus, an interview with Reddit’s Jen Wong.
Feed: All Latest
The Amazon boogie-man has every retailer scrambling for ways to fight back. But the cost and effort to install cameras all over the ceiling or into every shelf could block stores from entering the autonomous shopping era. Caper Labs wants to make eliminating checkout lines as easy as replacing their shopping carts while offering a more familiar experience for customers.
The startup makes a shopping cart with a built-in barcode scanner and credit card swiper, but it’s finalizing the technology to automatically scan items you drop in thanks to three image recognition cameras and a weight sensor. The company claims people already buy 18 percent more per visit after stores are equipped with its carts.
Today, Caper is revealing that it’s raised a total of $ 3 million including a $ 2.15 million seed round led by prestigious First Round Capital and joined by food-focused angels like Instacart co-founder Max Mullen, Plated co-founder Nick Taranto, Jet’s Jetblack shopping concierge co-founder Jenny Fleiss, plus Y Combinator. Caper is now in two retailers in the NYC area, though it plans to use the cash to expand to more and develop a smart shopping basket for smaller stores.
“If you walked in to a grocery store 100 years ago versus today, nothing has really changed” says Caper co-founder and CEO Lindon Gao. “It doesn’t make sense that you can order a cab with your phone or go book a hotel with your phone, but you can’t use your phone to make a payment and leave the store. You still have to stand in line.”
Autonomous retail is going to be a race. $ 50 million-funded Standard Cognition, ex-Pandora CTO Will Glaser’s Grabango, and scrappier startups like Zippin and Inokyo are all building ceiling and shelf-based camera systems to help merchants keep up with Amazon Go’s expanding empire of cashierless stores. But Caper’s plug-and-play cart-based system might be able to leapfrog its competitors if it’s easier for shops to set up.
Inventing The Smart Cart
“I don’t have an altruistic reason to care about retail, but I really want to put a dent in the universe and I think retail is severely under-innovated” Gao candidly remarked. Most founders try to spin a “super hero origin story” about why they’re the right person for the job. For Gao, chasing autonomous retail is just good business. He built his first startup in gaming commerce at age 14. The jewelry company he launched at 19 still operates. He went on to become an investment banker at Goldman Sachs and JP Morgan but “I always felt like I was more of a startup guy.”
Caper was actually a pivot from his previous entry to the space called QueueHop that made cashierless apparel security tags that unlocked when you paid. But during Y Combinator, he discovered how tough it’d be to scale a product that requires a complete rethinking of a merchant’s operations flow. So Gao hoofed it around NYC to talk to 150 merchants and discover what they really wanted. The cart was the answer.
V1 of Caper’s cart lets people scan their items’ barcodes and pay on the cart with a credit card swipe or Apple/Android Pay tap and their receipt is emailed to them. But each time they scan, the cart is actually taking 120 photos and precisely weighing the items to train Caper’s machine vision algorithms in what Gao likens to how Tesla is inching towards self-driving.
Soon, Caper wants to go entirely scanless, and sections of its two pilot stores already use the technology. The cameras on the cart employ image recognition matched with a weight sensor to identify what you toss in your cart. You shop just like normal but then pay and leave with no line. Caper pulls in a store’s existing security feed to help detect shoplifting, which could be a bigger risk than with ceiling and shelf camera systems, but Gao says it hasn’t been a problem yet. He woudn’t reveal the price of the carts but said “they’re not that much more expensive than a standard shopping cart. To outfit a store it should be comparable to the price of implementing traditional self-checkout.” Shops buy the carts outright and pay a technology subscriptions but get free hardware upgrades. They’ll have to hope Caper stays alive.
“Do you want guacamole with those chips?”
Caper hopes to deliver three big benefits to merchants. First, they’ll be able to repurpose cashier labor to assist customers so they buy more and to keep shelves stocked, though eventually this technology is likely to eliminate a lot of jobs. Second, the ease and affordable cost of transitioning means businesses will be able to recoup their investment and grow revenues as shoppers buy more. And third, Caper wants to share data that its carts collect on routes through the store, shelves customers hover in front of, and more with its retail partners so they can optimize their layouts.
One big advantage over its ceiling and shelf camera competitors is that Caper’s cart can promote deals on nearby or related items. In the future, it plans to add recommendations based on what’s on your cart to help you fill out recipes. ‘Threw some chips in the cart? Here’s where to find the guacamole that’s on sale.’ A smaller hand-held smart basket could broaden Caper’s appeal beyond grocers amongst littler shops, though making it light enough to carry will be a challenge.
Gao says that with merchants already seeing sales growth from the carts, what keeps him up at night is handling Caper’s supply chain since the product requires a ton of different component manufacturers. The startup has to move fast if it wants to be what introduces Main Street to autonomous retail. But no matter what gadgets it builds in, Caper must keep sight of the real-world stress their tech will undergo. Gao concludes “We’re basically building a robot here. The carts need to be durable. They need to resist heat, vibration, rain, people slamming them around. We’re building our shopping cart like a tank.”
CES 2019 is here and there has been a lot of technology announced at the show. From the latest autonomous vehicle technology to the coolest personal gadgets, here’s a roundup of the best from the show so far.
- Citizens Reserve is building a supply chain platform on the blockchain
- Tips to maximize ROI on paid social: Facebook + Instagram
- The case against behavioral advertising is stacking up
- Fender American Acoustasonic Telecaster: Pricing, Specs, Release Date
- The Newest Amazon Sponsored Products Features of 2019