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Category: mobile phones – Page 207

Low-latency JPEG XS format is optimized for live streaming and VR

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.

Team develops sodium ion batteries using copper sulfide

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 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 require less expensive, more abundant materials. Hence, a SIBs have attracted enormous attention for their advantage over lithium-based batteries.

New AI systems on a chip will spark an explosion of even smarter devices

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.

The world’s most valuable AI startup is a Chinese company specializing in real-time surveillance

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.

Putting the ‘smart’ in manufacturing

“Although smartphones and tablets are ubiquitous, many of the companies that make our everyday consumer products still rely on paper trails and manually updated spreadsheets to keep track of their production processes and delivery schedules,” says Leyuan Shi, a professor of industrial and systems engineering at the University of Wisconsin-Madison.

That’s what she hopes to change with a research idea she first published almost two decades ago.

During the past 16 years, Shi has visited more than 400 companies in the United States, China, Europe, and Japan to personally observe their production processes. “And I have used that insight to develop tools that can make these processes run much more smoothly,” she says.

How AI and Machine Learning Are Redefining Cybersecurity

We are now a connected global community where many digital natives cannot remember a time before the iPhone. The rise of smart homes means that we are increasingly attaching our lighting, door locks, cameras, thermostats, and even toasters to our home networks. Managing our home automation through mobile apps or our voice illustrates how far we have evolved over the last few years.

However, in our quest for the cool and convenient, many have not stopped to consider their cybersecurity responsibilities. The device with the weakest security could allow hackers to exploit vulnerabilities on our network and access our home. But this is just the tip of the proverbial iceberg.

Businesses and even governments are starting to face up to the vulnerabilities of everything being online. Sophisticated and disruptive cyberattacks are continuing to increase in complexity and scale across multiple industries. Areas of our critical infrastructure such as energy, nuclear, water, aviation, and critical manufacturing have vulnerabilities that make them a target for cybercriminals and even a state-sponsored attack.

Research trend: Combining brain stimulation with cognitive training to enhance attention and memory

In summary — “I am cautiously optimistic about the promise of tDCS; cognitive training paired with tDCS specifically could lead to improvements in attention and memory for people of all ages and make some huge changes in society. Maybe we could help to stave off cognitive decline in older adults or enhance cognitive skills, such as focus, in people such as airline pilots or soldiers, who need it the most. Still, I am happy to report that we have at least moved on from torpedo fish” smile

In 47 CE, Scri­bo­nius Largus, court physi­cian to the Roman emper­or Claudius, described in his Com­po­si­tiones a method for treat­ing chron­ic migraines: place tor­pe­do fish on the scalps of patients to ease their pain with elec­tric shocks. Largus was on the right path; our brains are com­prised of elec­tri­cal sig­nals that influ­ence how brain cells com­mu­ni­cate with each oth­er and in turn affect cog­ni­tive process­es such as mem­o­ry, emo­tion and attention.

The sci­ence of brain stim­u­la­tion – alter­ing elec­tri­cal sig­nals in the brain – has, need­less to say, changed in the past 2,000 years. Today we have a hand­ful of tran­scra­nial direct cur­rent stim­u­la­tion (tDCS) devices that deliv­er con­stant, low cur­rent to spe­cif­ic regions of the brain through elec­trodes on the scalp, for users rang­ing from online video-gamers to pro­fes­sion­al ath­letes and peo­ple with depres­sion. Yet cog­ni­tive neu­ro­sci­en­tists are still work­ing to under­stand just how much we can influ­ence brain sig­nals and improve cog­ni­tion with these techniques.

Brain stim­u­la­tion by tDCS is non-inva­sive and inex­pen­sive. Some sci­en­tists think it increas­es the like­li­hood that neu­rons will fire, alter­ing neur­al con­nec­tions and poten­tial­ly improv­ing the cog­ni­tive skills asso­ci­at­ed with spe­cif­ic brain regions. Neur­al net­works asso­ci­at­ed with atten­tion con­trol can be tar­get­ed to improve focus in peo­ple with atten­tion deficit-hyper­ac­tiv­i­ty dis­or­der (ADHD). Or peo­ple who have a hard time remem­ber­ing shop­ping lists and phone num­bers might like to tar­get brain areas asso­ci­at­ed with short-term (also known as work­ing) mem­o­ry in order to enhance this cog­ni­tive process. How­ev­er, the effects of tDCS are incon­clu­sive across a wide body of peer-reviewed stud­ies, par­tic­u­lar­ly after a sin­gle ses­sion. In fact, some experts ques­tion whether enough elec­tri­cal stim­u­la­tion from the tech­nique is pass­ing through the scalp into the brain to alter con­nec­tions between brain cells at all.

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