Amazon may take on Square and PayPal Here with mobile credit card reader

Web giant Amazon is about to release a mobile-based credit card reader to rival the likes of Square, according to reports on Sunday.

9to5Mac has obtained a copy of a recent Staples (an American office supplies store) inventory, that claims Amazon is planning to launch a device known as the 'Amazon Card Reader' next month.

The internal document says the reader will cost $9.99 (around £5.90, AU$10.60), but adds Staples staff are to hold off on making stock available until August 12.

For those keeping score at home, this isn't the first time such a rumour has manifested itself. Earlier this year the Wall Street Journal reported Amazon was working on a point-of-sale system.

Hip to be square

Currently Square, founded and operated by Twitter co-founder Jack Dorsey, dominates the mobile card reader market in the United States, although the PayPal Here rival is also on the scene.

Square provides a small, square (hence the name) reader to vendors, who can plug them into a smartphone's 3.5mm headphone jack in order to take credit card payments via an accompanying app.

Square takes a small cut of the transaction, but offers a far more cost effective solution for small businesses who don't wish to invest in credit card machines or pay inflated fees associated with them.

However, all is far from rosy in the Square garden after it announced losses of $100m earlier this year. Could Amazon capitalise on its perceived weakness?

Amazon is yet to comment on the reports, but with August 12 just around the corner, it won't be long until we find out for sure.

Nvidia's Shield tablet confirmed and available to pre-order

Nvidia has taken the wraps off a new Shield tablet that will work with a Shield wireless controller for on-the-go gaming courtesy of the company's Nvidia Tegra K1 mobile chip.

Built specifically for gamers, the tablet features an 8-inch, 1080p HD screen, front-facing speakers and the same PC streaming feature we saw in the original Shield. It's design matches the leaked images we saw last week.

The tablet will also come with an optional cover that can double as a kickstand and storage choices are the standard 16GB or 32GB variants.

Nvidia has built in LTE-functionality so that gaming doesn't need to be limited to a Wi-Fi connection. And the company states there will be regular, over-the-air upgrades pushed out to keep the Shield tablet on its gaming toes.

It also boasts a new feature called Nvidia ShadowPlay that lets you capture gaming moments and share them using the video platform Twitch. Something that has become increasingly popular and is offered by consoles like the PS4 and Xbox One.

Catering to those with more artistic tendencies, the Shield tablet also makes use of the Nvidia DirectStylus 2 stylus that enables, so Nvidia says, the first GPU-accelerated 3D painting experience.

“If you’re a gamer and you use a tablet, the Nvidia Shield tablet was created specifically for you,” said Jen-Hsun Huang, Nvidia's co-founder and chief executive officer.

“It delivers exceptional tablet performance and unique gaming capabilities to keep even the most avid gamers deeply immersed, anywhere they play.”

The Shield tablet is available to pre-order now in the UK and comes in with a price tag starting at £239.99 for the 16GB Wi-Fi model and going up to £299.99 for the 32GB LTE version.

Unfortunately, that doesn't include the wireless Shield controller, which you'll have to pick up separately for £49.99. The optional cover will set you back £24.99.

Stay tuned to currentbit for latest review of nvidia's tablet.

New self-driving car by Google

You are looking at Google’s very own, built-from-scratch-in-Detroit self-driving car. The battery-powered electric vehicle has as a stop-go button, but no steering wheel or pedals. The plan is to build around 200 of the mostly-plastic cars over the next year, with road testing probably restricted to California for the next year or two. Compared to the fairly aggressive stance of other notable EVs, like the Tesla Model S or Toyota Prius, Google’s new self-driving car is incredibly cutesy, closely resembling a Little Tikes plastic car — there’s even the same damn smiley face on the front. The cutesy appearance is undoubtedly a clever move to reduce apprehension towards the safety or long-term effects of autonomous vehicles — “Aw, how can something so cute be dangerous?”

For the last three years, Google has been retrofitting the Toyota Prius, Audi TT, and Lexus RS450h with the necessary software and hardware to perform autonomous driving. Now, Google has taken everything it has learnt about driverless cars, and built its own prototype from the ground up. Early versions of the prototype (which doesn’t appear to have a name) will still have manual controls for safety, but the eventual plan is to produce a fleet of some 200 completely driverless cars that can nip around California.

Disappointingly, Google’s new car still has a ton of expensive hardware — radar, lidar, 360-degree cameras — sitting on a tripod on the roof. This is to ensure good sightlines around the vehicle, but it’s a shame that Google hasn’t yet worked out how to build the hardware into the car itself, like other car makers that are toying with self-driving-like functionality. (Or maybe it has, but doesn’t want to invest additional money and engineering time until it’s time to commercialize the car.) In the concept art below, you can see that the eventual goal might be to build the computer vision and ranging hardware into a slightly less ugly rooftop beacon.

These first prototypes are mostly of plastic construction, with battery/electric propulsion limited to a max speed of 25 mph (40 kph). Instead of an engine or “frunk,” there’s a foam bulkhead at the front of the car to protect the passengers. Internally, there’s just a couple of seats, and some great big windows so you can enjoy the views (which must surely be one of the best perks of riding in a self-driving car).

Google’s stated goal in the blog post introducing the new car is “improving road safety and transforming mobility for millions of people.” Driverless cars could definitely revolutionize travel for people who can’t drive. Improving road safety is a little more nebulous, though. While it’s generally agreed that if all cars on the road were autonomous, there could be some massive gains in safety and efficiency (both in terms of fuel usage and squeezing more cars onto the roads). In the lead-up to that utopian scenario, though, there are all sorts of questions about how to effectively integrate a range of manual, semi- and fully self-driving vehicles on the same roadways.

Removing everything except for a stop-go button might sound like a good idea, but it’s naive. How do you move the car a few feet, so someone can get out, or for backing up to a trailer? Will Google’s software allow for temporary double parking, or off-road for a concert or party? Can you choose which parking spot the car will use, to leave the better/closer parking spots for your doddery grandfather? How will these cars handle the very “human” problems of giving way for other cars and pedestrians? Can you program the car to give way to a hot girl, but not an angry-looking trucker?

Plus, is it even sensible to promote a system that will eventually make it easier to cram more cars onto the road? Shouldn’t we be moving towards better, more efficient public transportation? At least until we move away from coal and gas towards cleaner power sources, like nuclear, solar, and fusion.

Google is now safety testing some early units, and will hopefully scale up production to around 200 cars that could be on the road “within the year.”

UK military creates quantum compass that could be the successor to GPS

A quantum compass takes advantage of the 1997 Nobel-winning discovery that lasers can be used to cool atoms to within fractions of a degree of absolute zero. Atoms in this frozen state are extremely sensitive to the magnetic and gravitational field of the Earth. Thus, they can be used to track movement with amazing accuracy. To be clear, this is still a type of inertial “dead reckoning” navigation. The difference is that after getting a solid GPS lock, a sub could go underwater and be exactly on target when it surfaces days or even weeks later.                                                                                                                                                                                                                                                                                     

 GPS began its life as a military technology in the 1970s, then everything changed in the late 80s when the US government decided to allow civilian use of the satellite network. Virtually every mobile device on the planet has a GPS chip built-in that lets you find your way around, but GPS is getting old and doesn’t work well in all situations. The British Ministry of Defence is hard at work developing a so-called “quantum compass” that could become the successor to GPS, and just like GPS, it might land in your pocket one day.

The UK military is investing millions of pounds in the quantum compass mainly for use in submarines. GPS systems require a view of the sky, or at least very little obstruction to get a location fix. A tube of metal sliding through the water 100 meters beneath the waves can’t really get a GPS lock. Subs currently use a type of inertial location system based on accelerometers. Each twist and turn a submarine makes is recorded and used to calculate its position based on the last known coordinates. This is called dead reckoning navigation.

Sandia Labs Is Stepping Up Its Neuro-Inspired Computer Chip Research

 Human ingenuity has given birth to incredibly powerful computers that can plow through more calculations in a second than most people could in their entire lives, but computers still aren’t terribly adaptable. The human brain is a very different kind of computer — a massively parallel processor that has been shaped by millions neuromorphic, computer systems.

of years of evolution to recognize patterns and adjust to changing situations. This is the kind of capability computer science researchers are now trying to unlock, and scientists at Sandia National Laboratories are stepping up their game to design neuro-inspired, or

Sandia isn’t just attracted to the idea of computers designed like brains because of the capabilities, but the human brain is also incredibly efficient. A computer has trouble telling the difference between a picture of a dog and a cat, but it eats up hundreds of watts of power simply trying. A brain, by contrast, operates continuously for decades and only consumes roughly the same power as a 20-watt light bulb.A modern computer is essentially a very powerful calculator — linear and much faster than humans at running the numbers. Scandia is spinning up this long term project to work on the hardware and software that could make a computer more like a biological brain. The first step in doing so, according to Sandia, is to look at the physical architecture of transistors.

A single neuron, like the ones seen above, can be connected to as many as 10,000 other neurons. Then each of those neurons could be connected to 10,000 more, and so on until you’ve got the bundle of nerve tissue between your ears that makes you who you are. Researchers believe this parallel system is what makes the brain so flexible, or plastic inneurology lingo. Most conventional transistors only have connections to four other transistors, but making a computer more interconnected is just the first step.

Sandia isn’t embarking on a quest to crank out an artificial intelligence platform right away, which is actually the approach many researchers take. A neuro-inspired parallel computer isn’t one and the same with AI, but they are closely linked. At Sandia National Labs, scientists are going to work on improved hardware and processing algorithms, and see if artificial intelligence can be developed as a consequence of that.Computers designed from the ground up like a brain could have important applications in robotics and remote sensors. These devices could benefit from the common sense and adaptability the brain imbues us with. They could learn from data and experiences to make predictions about what a human is going to want to know or do without being explicitly programmed for it. This is a bit like taking baby steps toward true AI.

Right now, your computer, phone, and everything else with a microchip works a certain way. There is very little room for error — either you enter commands correctly, and click on the right things, or you don’t. Regular computer systems are beginning to show a little flexibility, for example Google Now can often figure out what data you might want to see. It’s really cool when it works, but that’s because we’re still at the point where a computer guessing anything right is amazing. Sandia researchers want to make that common place.