Lifeboat Foundation

The demo is clever, questionably real, and prompts a lot of questions about how this device will actually work.

Buzz has been building around the secretive tech startup Humane for over a year, and now the company is finally offering a look at what it’s been building. At TED last month, Humane co-founder Imran Chaudhri gave a demonstration of the AI-powered wearable the company is building as a replacement for smartphones. Bits of the video leaked online after the event, but the full video is now available to watch.

The device appears to be a small black puck that slips into your breast pocket, with a camera, projector, and speaker sticking out the top.

Continue reading “Humane’s new wearable AI demo is wild to watch — and we have lots of questions” »

A Twitter engineer says the app accessed his phone’s mic as he slept, prompting Musk’s response, though he has an incentive to attack a rival app. WhatsApp blames the issue on a Google bug.

Over the past year, SideWinder has been linked to a cyber attack aimed at Pakistan Navy War College (PNWC) as well as an Android malware campaign that leveraged rogue phone cleaner and VPN apps uploaded to the Google Play Store to harvest sensitive information.

The latest infection chain documented by BlackBerry mirrors findings from Chinese cybersecurity firm QiAnXin in December 2022 detailing the use of PNWC lure documents to drop a lightweight. NET-based backdoor (App.dll) that’s capable of retrieving and executing next-stage malware from a remote server.

What makes the campaign also stand out is the threat actor’s use of server-based polymorphism as a way to potentially sidestep traditional signature-based antivirus (AV) detection and distribute additional payloads by responding with two different versions of an intermediate RTF file.

In a new study in Nature Machine Intelligence, researchers Bojian Yin and Sander Bohté from the HBP partner Dutch National Research Institute for Mathematics and Computer Science (CWI) demonstrate a significant step towards artificial intelligence that can be used in local devices like smartphones and in VR-like applications, while protecting privacy.

They show how brain-like neurons combined with novel learning methods enable training fast and energy-efficient spiking neural networks on a large scale. Potential applications range from wearable AI to speech recognition and Augmented Reality.

While modern artificial neural networks are the backbone of the current AI revolution, they are only loosely inspired by networks of real, biological neurons such as our brain. The brain however is a much larger network, much more energy-efficient, and can respond ultra-fast when triggered by external events. Spiking neural networks are special types of neural networks that more closely mimic the working of biological neurons: the neurons of our nervous system communicate by exchanging electrical pulses, and they do so only sparingly.

We have various ways of seeing what the brain is up to, from low-resolution electrodes that track waves of activity that ripple across the brain, to implanted electrodes that can follow the activity of individual cells. Combined with a detailed knowledge of which regions of the brain are involved in specific processes, we’ve been able to do remarkable things, such as using functional MRI (fMRI) to determine what letter a person was looking at or an implant to control a robotic arm.

But today, researchers announced a new bit of mind reading that’s impressive in its scope. By combining fMRI brain imaging with a system that’s somewhat like the predictive text of cell phones, they’ve worked out the gist of the sentences a person is hearing in near real time. While the system doesn’t get the exact words right and makes a fair number of mistakes, it’s also flexible enough that it can reconstruct an imaginary monologue that goes on entirely within someone’s head.

The mysterious phenomenon of “spooky action at a distance,” which once troubled Einstein, could soon become as commonplace as the gyroscopes used to measure acceleration in smartphones.

A recent study in Nature Photonics.

<em>Nature Photonics</em> is a prestigious, peer-reviewed scientific journal that is published by the Nature Publishing Group. Launched in January 2007, the journal focuses on the field of photonics, which includes research into the science and technology of light generation, manipulation, and detection. Its content ranges from fundamental research to applied science, covering topics such as lasers, optical devices, photonics materials, and photonics for energy. In addition to research papers, <em>Nature Photonics</em> also publishes reviews, news, and commentary on significant developments in the photonics field. It is a highly respected publication and is widely read by researchers, academics, and professionals in the photonics and related fields.

Year 2021 face_with_colon_three This could be made into a smartphone device that could one day treat everything without the need for surgery or other ways that are not as safe.

Researchers are investigating potential uses for the cell reprogramming technology to treat brain disorders such as Alzheimer’s disease or autoimmune diseases.

Continue reading “Cell Therapy AIDS Stroke-Damaged Brain Repair, Restores 90% of Motor Function” »

In the ceaseless pursuit of energy-efficient computing, new devices designed at UC Santa Barbara show promise for enhancements in information processing and data storage.

Researchers in the lab of Kaustav Banerjee, a professor of electrical and computer engineering, have published a new paper describing several of these devices, “Quantum-engineered devices based on 2D materials for next-generation information processing and storage,” in the journal Advanced Materials. Arnab Pal, who recently received his doctorate, is the lead author.

Each device is intended to address challenges associated with conventional computing in a new way. All four operate at very low voltages and are characterized as being low leakage, as opposed to the conventional metal-oxide semiconductor field-effect transistors (MOSFETs) found in smartphones that drain power even when turned off. But because they are based on processing steps similar to those used to make MOSFETs, the new devices could be produced at scale using existing industry-standard manufacturing processes for semiconductors.

UNSW Sydney researchers have developed a chip-scale method using OLEDs to image magnetic fields, potentially transforming smartphones into portable quantum sensors. The technique is more scalable and doesn’t require laser input, making the device smaller and mass-producible. The technology could be used in remote medical diagnostics and material defect identification.

Smartphones could one day become portable quantum sensors thanks to a new chip-scale approach that uses organic light-emitting diodes (OLEDs) to image magnetic fields.

Researchers from the ARC Centre of Excellence in Exciton Science at UNSW Sydney have demonstrated that OLEDs, a type of semiconductor material commonly found in flat-screen televisions, smartphone screens, and other digital displays, can be used to map magnetic fields using magnetic resonance.