How did your smartphone end up in your hands? The microchips that help power our smartphones and computers start out as sand. Explore how microchips come to live in our phones, with the help of IoT technologies.
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Category: mobile phones – Page 180
My #transhumanism work in this fun new article on future of sports:
Can bionic limbs and implanted technology make you faster and stronger? Meet biohackers working on the frontier.
Zoltan Istvan has achieved every runner’s fantasy: the ability to run without the hassle of carrying his keys. Thanks to a tiny chip implanted in his hand, Istvan doesn’t have to tie a key onto his laces, tuck it under a rock in the front yard, or find shorts with little zipper pockets built in. Just a wave of the microchip implanted in his hand will unlock the door of his home. The chip doesn’t yet negate the need for a Fitbit, a phone, or a pair of earbuds on long runs, but Istvan says it’s only a matter of time.
A long-time athlete and technology geek, Istvan identifies as a transhumanist: he believes that the transformation of the human body through ever-developing and evolving technologies will improve human life and ultimately lead to immortality.
Are we witnessing, as Truthstream Media calls it, “A Zombie Apocalypse” Where reality is becoming a little less real by the day or is this trend something else?
Are people merging with their Smart Phones and becoming programmed by them using Cyborgification or is this something different? Find out…
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A new biotech company co-founded by CRISPR pioneer Jennifer Doudna is developing a device that uses CRISPR to detect all kinds of diseases like malaria, tuberculosis, and Zika. The tech is still just in prototype phase, but research in the field is showing promising results. These CRISPR-based diagnostic tools have the potential to revolutionize how we test for diseases in the hospital, or even at home.
Called Mammoth Biosciences, the company is working on a credit card-sized paper test and smartphone app combo for disease detection. But the applications extend beyond that: The same technology could be used in agriculture, to determine what’s making animals sick or what sorts of microbes are found in soil, or even in the oil and gas industry, to detect corrosive microbes in pipelines, says Trevor Martin, the CEO of Mammoth Biosciences, who holds a PhD in biology from Stanford University. The company is focusing on human health applications first, however.
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About a year ago, Apple made the bold proclamation that it was zeroing in on a future where iPhones and MacBooks were created wholly of recycled materials. It was, and still is, an ambitious thought. In a technologically-charged world, many forget that nearly 100 percent of e-waste is recyclable. Apple didn’t.
Named “Daisy,” Apple’s new robot builds on its previous iteration, Liam, which Apple used to disassemble unneeded iPhones in an attempt to scrap or reuse the materials. Like her predecessor, Daisy can successfully salvage a bulk of the material needed to create brand new iPhones. All told, the robot is capable of extracting parts from nine types of iPhone, and for every 100,000 devices it manages to recover 1,900 kg (4,188 pounds) of aluminum, 770 kg of cobalt, 710 kg of copper, and 11 kg of rare earth elements — which also happen to be some of the hardest and environmentally un-friendly materials required to build the devices.
In its latest environmental progress report, Apple noted:
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You might only know JPEG as the default image compression standard, but the group behind it has now branched out into something new: JPEG XS. JPEG XS is described as a new low-energy format designed to stream live video and VR, even over WiFi and 5G networks. It’s not a replacement for JPEG and the file sizes themselves won’t be smaller; it’s just that this new format is optimized specifically for lower latency and energy efficiency. In other words, JPEG is for downloading, but JPEG XS is more for streaming.
The new standard was introduced this week by the Joint Photographic Experts Group, which says that the aim of JPEG XS is to “stream the files instead of storing them in smartphones or other devices with limited memory.” So in addition to getting faster HD content on your large displays, the group also sees JPEG XS as a valuable format for faster stereoscopic VR streaming plus videos streamed by drones and self-driving cars.
“We are compressing less in order to better preserve quality, and we are making the process faster while using less energy,” says JPEG leader Touradj Ebrahimi in a statement. According to Ebrahimi, the JPEG XS video compression will be less severe than with JPEG photos — while JPEG photos are compressed by a factor of 10, JPEG XS is compressed by a factor of 6. The group promises a “visual lossless” quality to the images of JPEG XS.
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A KAIST research team recently developed sodium ion batteries using copper sulfide anode. This finding will contribute to advancing the commercialization of sodium ion batteries (SIBs) and reducing the production cost of any electronic products with batteries.
Professor Jong Min Yuk and Emeritus Professor Jeong Yong Lee from Department of Materials Science and Engineering developed a new anode material suitable for use in an SIB. Compared to the existing anode materials, the copper sulfide anode was measured to exhibit 1.5 times better cyclability with projected 40 percent reduction in cost.
Lithium-ion batteries (Li-ion batteries or LIBs) are widely used in mobile phones and other personal electronics. However, large-scale energy storage systems require less expensive, more abundant materials. Hence, a SIBs have attracted enormous attention for their advantage over lithium-based batteries.
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Artificial intelligence is permeating everybody’s lives through the face recognition, voice recognition, image analysis and natural language processing capabilities built into their smartphones and consumer appliances. Over the next several years, most new consumer devices will run AI natively, locally and, to an increasing extent, autonomously.
But there’s a problem: Traditional processors in most mobile devices aren’t optimized for AI, which tends to consume a lot of processing, memory, data and battery on these resource-constrained devices. As a result, AI has tended to execute slowly on mobile and “internet of things” endpoints, while draining their batteries rapidly, consuming inordinate wireless bandwidth and exposing sensitive local information as data makes roundtrips in the cloud.
That’s why mass-market mobile and IoT edge devices are increasingly coming equipped with systems-on-a-chip that are optimized for local AI processing. What distinguishes AI systems on a chip from traditional mobile processors is that they come with specialized neural-network processors, such as graphics processing units or GPUs, tensor processing units or TPUs, and field programming gate arrays or FPGAs. These AI-optimized chips offload neural-network processing from the device’s central processing unit chip, enabling more local autonomous AI processing and reducing the need to communicate with the cloud for AI processing.
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Artificial intelligence is being used for a dizzying array of tasks, but one of the most successful is also one of the scariest: automated surveillance. Case in point is Chinese startup SenseTime, which makes AI-powered surveillance software for the country’s police, and which this week received a new round of funding worth $600 million. This funding, led by retailing giant Alibaba, reportedly gives SenseTime a total valuation of more than $4.5 billion, making it the most valuable AI startup in the world, according to analyst firm CB Insights.
This news is significant for a number of reasons. First, it shows how China continues to pour money into artificial intelligence, both through government funding and private investment. Many are watching the competition between China and America to develop cutting-edge AI with great interest, and see investment as an important measure of progress. China has overtaken the US in this regard, although experts are quick to caution that it’s only one metric of success.
Secondly, the investment shows that image analysis is one of the most lucrative commercial applications for AI. SenseTime became profitable in 2017 and claims it has more than 400 clients and partners. It sells its AI-powered services to improve the camera apps of smartphone-makers like OPPO and Vivo; to offer “beautification” effects and AR filters on Chinese social media platforms like Weibo; and to provide identity verification for domestic finance and retail apps like Huanbei and Rong360.
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