Lifeboat Foundation

Researchers at the University of Waterloo have developed a cheaper and more efficient method for Internet-of-Things devices to receive high-speed wireless connectivity.

With 75 billion Internet of Things (IoT) devices expected to be in place by 2025, a growing strain will be placed on requirements of wireless networks. Contemporary WiFi and cellular networks won’t be enough to support the influx of IoT devices, the researchers highlighted in their new study.

Millimeter wave (mmWave), a network that offers multi-gigahertz of unlicensed bandwidth—more than 200 times that allocated to today’s WiFi and cellular networks, can be used to address the looming issue. In fact, 5G networks are going to be powered by mmWave technology. However, the hardware required to use mmWave is expensive and power-hungry, which are significant deterrents to it being deployed in many IoT applications.

Researchers from North Carolina State University have developed a technique for measuring speed and distance in indoor environments, which could be used to improve navigation technologies for robots, drones—or pedestrians trying to find their way around an airport. The technique uses a novel combination of Wi-Fi signals and accelerometer technology to track devices in near-real time.

“We call our approach Wi-Fi-assisted Inertial Odometry (WIO),” says Raghav Venkatnarayan, co-corresponding author of a paper on the work and a Ph.D. student at NC State. “WIO uses Wi-Fi as a velocity sensor to accurately track how far something has moved. Think of it as sonar, but using radio waves, rather than sound waves.”

Many devices, such as smartphones, incorporate technology called inertial measurement units (IMUs) to calculate how far a device has moved. However, IMUs suffer from large drift errors, meaning that even minor inaccuracies can quickly become exaggerated.

In February, an artificial intelligence lab cofounded by Elon Musk informed the world that its latest breakthrough was too risky to release to the public. OpenAI claimed it had made language software so fluent at generating text that it might be adapted to crank out fake news or spam.

On Thursday, two recent master’s graduates in computer science released what they say is a re-creation of OpenAI’s withheld software onto the internet for anyone to download and use.

Aaron Gokaslan, 23, and Vanya Cohen, 24, say they aren’t out to cause havoc and don’t believe such software poses much risk to society yet. The pair say their release was intended to show that you don’t have to be an elite lab rich in dollars and PhDs to create this kind of software: They used an estimated $50,000 worth of free cloud computing from Google, which hands out credits to academic institutions. And they argue that setting their creation free can help others explore and prepare for future advances—good or bad.

Humans can communicate a range of nonverbal emotions, from terrified shrieks to exasperated groans. Voice inflections and cues can communicate subtle feelings, from ecstasy to agony, arousal and disgust. Even when simply speaking, the human voice is stuffed with meaning, and a lot of potential value if you’re a company collecting personal data.

Now, researchers at the Imperial College London have used AI to mask the emotional cues in users’ voices when they’re speaking to internet-connected voice assistants. The idea is to put a “layer” between the user and the cloud their data is uploaded to by automatically converting emotional speech into “normal” speech. They recently published their paper “Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants” on the arXiv preprint server.

Our voices can reveal our confidence and stress levels, physical condition, age, gender, and personal traits. This isn’t lost on smart speaker makers, and companies such as Amazon are always working to improve the emotion-detecting abilities of AI.

A University of Texas at Dallas physicist has teamed with Texas Instruments Inc. to design a better way for electronics to convert waste heat into reusable energy.

The collaborative project demonstrated that silicon’s ability to harvest energy from heat can be greatly increased while remaining mass-producible.

Dr. Mark Lee, professor and head of the Department of Physics in the School of Natural Sciences and Mathematics, is the corresponding author of a study published July 15 in Nature Electronics that describes the results. The findings could greatly influence how circuits are cooled in electronics, as well as provide a method of powering the sensors used in the growing “internet of things.”

Ukrainian authorities are investigating a potential security breach at a local nuclear power plant after employees connected parts of its internal network to the internet so they could mine cryptocurrency.

The investigation is being led by the Ukrainian Secret Service (SBU), who is looking at the incident as a potential breach of state secrets due to the classification of nuclear power plants as critical infrastructure.

Investigators are examining if attackers might have used the mining rigs as a pivot point to enter the nuclear power plant’s network and retrieve information from its systems, such as data about the plant’s physical defenses and protections.

The ability to securely transmit information over the internet is extremely important, but most of the time, eavesdroppers can still generally determine who the sender and receiver are. In some highly confidential situations, it is important that the sender’s and receiver’s identities remain anonymous.

Over the past couple of decades, researchers have been developing protocols for anonymously transmitting messages over classical networks, but similar protocols for quantum networks are still in much earlier stages of development. The anonymity methods that have been proposed for quantum networks so far face challenges such as implementation difficulties or require that strong assumptions be made about the resources, making them impractical for use in the real world.

In a new paper, Anupama Unnikrishnan, Ian MacFarlane, Richard Yi, Eleni Diamanti, Damian Markham, and Iordanis Kerenidis, from the University of Oxford, MIT, Sorbonne University, the University of Paris and CNRS, have proposed the first practical protocol for anonymous communication in quantum networks.

Ever been frustrated waiting for your YouTube video to stream quickly? A team of experts from MIT has created a system that allows multiple Wi-Fi users to stream and buffer high-quality videos.

The data economy has too often betrayed its customers, whether it’s Facebook sharing data you didn’t even realize it had, or invisible trackers that follow you around the web without your knowledge. But a new app launching in the iOS App Store today wants to help you take back some control—without making your life harder.