Lifeboat Foundation

Light-emitting diodes—LEDs—can do way more than illuminate your living room. These light sources are useful microelectronics too.

Smartphones, for example, can use an LED proximity sensor to determine if you’re holding the phone next to your face (in which case the screen turns off). The LED sends a pulse of light toward your face, and a timer in the phone measures how long it takes that light to reflect back to the phone, a proxy for how close the phone is to your face. LEDs are also handy for distance measurement in autofocus cameras and gesture recognition.

One problem with LEDs: It’s tough to make them from silicon. That means LED sensors must be manufactured separately from their device’s silicon-based processing chip, often at a hefty price. But that could one day change, thanks to new research from MIT’s Research Laboratory of Electronics (RLE).

Recently, Google introduced Portrait Light, a feature on its Pixel phones that can be used to enhance portraits by adding an external light source not present at the time the photo was taken. In a new blog post, Google explains how they made this possible.

In their post, engineers at Google Research note that professional photographers discovered long ago that the best way to make people look their best in portraits is by using secondary flash devices that are not attached to the camera. Such flash devices can be situated by the photographer prior to photographing a subject by taking into account the direction their face is pointing, other light available, skin tone and other factors. Google has attempted to capture those factors with its new portrait-enhancing software. The system does not require the camera phone operator to use another light source. Instead, the software simply pretends that there was another light source all along, and then allows the user to determine the most flattering configuration for the subject.

The engineers explain they achieved this feat using two algorithms. The first, which they call automatic directional light placement, places synthetic light into the scene as a professional photographer would. The second algorithm is called synthetic post-capture relighting. It allows for repositioning the light after the fact in a realistic and natural-looking way.

Being able to see, move, and exercise independently is something most of us take for granted. [Thomas Panek] was an avid runner before losing his sight due to a genetic condition, and had to rely on other humans and guide dogs to run again. After challenging attendants at a Google hackathon, Project Guideline was established to give blind runners (or walkers) independence from a cane, dog or another human, while exercising outdoors. Using a smartphone with line following AI software, and bone conduction headphones, users can be guided along a path with a line painted on it. You need to watch the video below to get a taste of just how incredible it is for the users.

Getting a wheeled robot to follow a line is relatively simple, but a running human is by no means a stable sensor platform. At the previously mentioned hackathon, developers put together a rough proof of concept with a smartphone, using its camera to recognize a painted line on the ground and provide left/right audio cues. As the project developed, the smartphone was attached to a waist belt and bone conduction headphones were used, which don’t affect audio situational awareness as much as normal headphones.

The shaking and side to side movement of running, and varying light conditions and visual obstructions in the outdoors made the problem more difficult to solve, but within a year the developers had completed successful running tests with [Thomas] on a well-lit indoor track and an outdoor pedestrian path with a temporary line. For the first time in 25 years, [Thomas] was able to run independently.

:ooooooooooo.

How bright is your flashlight? I only have the one on my phone because I’m completely unprepared for any sort of emergency situation. Well, presumably with the belief that it should be daylight all the time, the team over at Hacksmith Industries took it upon themselves to build a giant, 1,414,224 lumen flashlight. I can already imagine myself staring at it until I go blind.

Continue reading “Team Builds 1.4 Million Lumen ‘World’s Brightest’ Flashlight” »

Ever dream about never having to charge your phone?

Nikola Tesla couldn’t figure out the secret to ubiquitous wireless power. Now, more than 100 years later, are we any closer to pulling it off?

Be it with smartphones, laptops, or mainframes: The transmission, processing, and storage of information is currently based on a single class of material—as it was in the early days of computer science about 60 years ago. A new class of magnetic materials, however, could raise information technology to a new level. Antiferromagnetic insulators enable computing speeds that are a thousand times faster than conventional electronics, with significantly less heating. Components could be packed closer together and logic modules could thus become smaller, which has so far been limited due to the increased heating of current components.

Information transfer at room temperature

So far, the problem has been that the information transfer in antiferromagnetic insulators only worked at low temperatures. But who wants to put their smartphones in the freezer to be able to use it? Physicists at Johannes Gutenberg University Mainz (JGU) have now been able to eliminate this shortcoming, together with experimentalists from the CNRS/Thales lab, the CEA Grenoble, and the National High Field Laboratory in France as well as theorists from the Center for Quantum Spintronics (QuSpin) at the Norwegian University of Science and Technology. “We were able to transmit and process information in a standard antiferromagnetic insulator at room temperature—and to do so over long enough distances to enable information processing to occur”, said JGU scientist Andrew Ross. The researchers used iron oxide (α-Fe₂O₃), the main component of rust, as an antiferromagnetic insulator, because iron oxide is widespread and easy to manufacture.

Powerful neural networks could soon train on smartphones with dramatically faster speeds and less energy.

There is also the fact that privacy crusader Max Schrems undercut Apple’s holier-than-thou privacy image last month when his digital rights group Noyb targeted the tech giant in Germany and Spain, claiming that Apple’s “Identifier for Advertisers” (IDFA) tracking ID, which is automatically generated on every iPhone during setup, allows Apple, app makers and ad networks to follow an individual user’s activities and use that data to show them ads targeted at their interests. Apple has said those claims are “factually inaccurate”.

Fundamentally though, the underlying message of Federighi’s keynote today was clear: Apple is not budging on its new privacy standards, they will come at the start of 2021, and it will play hardball with other tech giants if necessary, at least in certain markets.

Continue reading “Apple fires warning shot at Facebook and Google on privacy, pledges fight against ‘data-industrial complex’” »

There are technologies just around the corner which will change the world, and our lives, massively, and for the better…in ways many cannot even start to imagine.

So in have done just that.

Continue reading “Emerging Technology That Will Change Our World” »