Lifeboat Foundation

The landscape of artificial intelligence (AI) applications has traditionally been dominated by the use of resource-intensive servers centralized in industrialized nations. However, recent years have witnessed the emergence of small, energy-efficient devices for AI applications, a concept known as tiny machine learning (TinyML).

We’re most familiar with consumer-facing applications such as Siri, Alexa, and Google Assistant, but the limited cost and small size of such devices allow them to be deployed in the field. For example, the technology has been used to detect mosquito wingbeats and so help prevent the spread of malaria. It’s also been part of the development of low-power animal collars to support conservation efforts.

Small size, big impact Distinguished by their small size and low cost, TinyML devices operate within constraints reminiscent of the dawn of the personal-computer era—memory is measured in kilobytes and hardware can be had for as little as US$1. This is possible because TinyML doesn’t require a laptop computer or even a mobile phone. Instead, it can instead run on simple microcontrollers that power standard electronic components worldwide. In fact, given that there are already 250 billion microcontrollers deployed globally, devices that support TinyML are already available at scale.

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The rumor mill has fired up again, with a new supply chain report claiming that the “Apple Ring” will arrive sooner, rather than later.

Samsung’s tease of the Galaxy Ring during its Unpacked event in January will help expand the smart ring market considerably. However, a report claims Apple isn’t too far away from introducing its own.

According to an industry insider speaking to ETNews on Tuesday, Apple is getting very close to launching the rumored wearable. After filing many patent applications, and spurned on by Samsung, it could soon be Apple’s turn.

Researchers from Nanyang Technological University in Singapore (NTU Singapore) have created a low-cost tool that can capture power from wind energy as moderate as a light breeze.

The gadget can create a voltage of three volts and energy power of up to 290 microwatts when exposed to winds with speeds as low as 2 meters per second (m/s). This is enough to power a commercial sensor device and allow it to transfer data to a smartphone or computer.

A team of academic researchers show that a new set of attacks called ‘VoltSchemer’ can inject voice commands to manipulate a smartphone’s voice assistant through the magnetic field emitted by an off-the-shelf wireless charger.

VoltSchemer can also be used to cause physical damage to the mobile device and to heat items close to the charger to a temperature above 536F (280C).

A technical paper signed by researchers at the University of Florida and CertiK describes VoltSchemer as an attack that leverages electromagnetic interference to manipulate the charger’s behavior.

Fashioned from the same element found in sand and covered by intricate patterns, microchips power smartphones, augment appliances and aid the operation of cars and airplanes.

Now, scientists at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) are developing computer simulation codes that will outperform current simulation techniques and aid the production of microchips using plasma, the electrically charged state of matter also used in fusion research.

These codes could help increase the efficiency of the manufacturing process and potentially stimulate the renaissance of the chip industry in the United States.

The Anatsa banking trojan has been targeting users in Europe by infecting Android devices through malware droppers hosted on Google Play.

Over the past four months, security researchers noticed five campaigns tailored to deliver the malware to users in the UK, Germany, Spain, Slovakia, Slovenia, and the Czech Republic.

Researchers at fraud detection company ThreatFabric noticed an increase of Anatsa activity since November, with at least 150,000 infections.

Recent technological advances have enabled the development of increasingly sophisticated sensors, which can help to advance the sensing capabilities of robots, drones, autonomous vehicles, and other smart systems. Many of these sensors, however, rely on individual cameras, thus the accuracy of the measurements they collect is limited by the cameras’ field of view (FOV).

Researchers at Beihang University in China recently developed a new multi-camera differential binocular vision sensor with a wider FOV that could collect more accurate measurements. This sensor, introduced in a paper published in Optics & Laser Technology, could be integrated into a wide range of devices and smart robotic systems.

“Aiming at the high-precision requirements of environment perception for unmanned aerial vehicle detection, robot navigation, and autonomous driving, inspired by the multi-camera module of mobile phones, we introduced a visual perception mode based on the principle of high-precision binocular vision measurement,” Fuqiang Zhou, co-author of the paper, told Tech Xplore. “This principle involves a central high-resolution camera and peripheral auxiliary cameras that work together.”

Apple is playing catch-up, but it should take note.