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Devices such as cellphones, laptops and smartwatches are constant companions for most people, spending days and nights in their pocket, on their wrist, or otherwise close at hand.

But when these technologies break down or a newer model hits stores, many people are quick to toss out or replace their device without a second thought. This disposability leads to rising levels of electronic waste—the fastest-growing category of waste, with 40 million tons generated each year.

University of Chicago scientists Jasmine Lu and Pedro Lopes wondered if they could change that fickle relationship by bringing devices to life—literally.

Deep-learning models have proven to be highly valuable tools for making predictions and solving real-world tasks that involve the analysis of data. Despite their advantages, before they are deployed in real software and devices such as cell phones, these models require extensive training in physical data centers, which can be both time and energy consuming.

Researchers at Texas A&M University, Rain Neuromorphics and Sandia National Laboratories have recently devised a new system for deep learning models more efficiently and on a larger scale. This system, introduced in a paper published in Nature Electronics, relies on the use of new training algorithms and memristor crossbar , that can carry out multiple operations at once.

“Most people associate AI with health monitoring in smart watches, face recognition in smart phones, etc., but most of AI, in terms of energy spent, entails the training of AI models to perform these tasks,” Suhas Kumar, the senior author of the study, told TechXplore.

Neurotechnology and Brain-Computer Interfaces are advancing at a rapid pace and may soon be a life-changing technology for those with limited mobility and/or paralysis. There are already two brain implants, Blackrock Neurotech’s NeuroPort and Synchron’s Stentrode, that have been approved to start clinical trials under an Investigational Device Exemption. In this video, we compare these devices on the merits of safety, device specifications, and capability.

Thanks to Blackrock Neurotech for sponsoring this video. The opinions expressed in this video are that of The BCI Guys and should be taken as such.

——–ABOUT US:——-

Harrison and Colin (The BCI Guys) are neurotech researchers and entrepreneurs dedicated to creating a brain-controlled future! Neurotechnology and brain-computer interfaces are devices that allow users to control machines with their thoughts and interact with technology in new ways. This revolutionary technology will change life as we know it, and soon will be as common as the touchscreen on your smartphone. Join us in learning about the brain-controlled future!

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George Hotz, the 32-year-old CEO of Comma AI who made a name for himself as the hacker “geohot” when he was just a teenager, announced that he is stepping away from his company on his GitHub page. According to Hotz, he no longer feels “capable” to continue leading the driver-assist technology company he created seven years ago.

Hotz has had a long history in the tech industry despite his young age. He gained notoriety in hacker communities at the age of 17 after becoming the first person to carrier unlock the iPhone. He also bumped heads with Sony a few years later for hacking the PlayStation 3.

Hotz also got into a disagreement with Elon Musk in 2015 after Musk allegedly wanted to hire him because he thought he could improve Tesla’s Autopilot software. Hotz later founded Comma AI, which focused itself on driver-assist technologies. In true hacker fashion, Hotz’s autonomous driving code, “openpilot,” was posted online for free.

Starlink and T-Mobile’s partnership will be revolutionary for cellular service and Smarter AI CEO Chris Piche had some thoughts on how the new partnership will impact 5G capability for the automotive industry.

Chris, who has created services including AT&T TV, BBM Video, Poly Video, and STUN/TURN/ICE shared his thoughts on the effect of 5G on vehicles and telecommunications in an interview with Teslarati.

AI CAMERAS, TESLA, STARLINK & AUTONOMOUS VEHICLES Before founding Smarter AI, the Top 40 under 40 entrepreneur’s company created a technology that BlackBerry licensed to enable voice and video calling. This gave Chris a front-row seat to witness the speed at which technology can transform markets.

Nerve cells can regulate their sensitivity to incoming signals autonomously. A new study led by the University of Bonn has now discovered a mechanism that does just that. The German Center for Neurodegenerative Diseases and the Max Planck Institute for Neurobiology of Behavior were involved in the work. The results have now been published in the journal Cell Reports.

Anyone who has ever sent a voice message with a knows how much the volume matters: Shouting into the microphone results in a distorted and unclear recording. But whispering is not a good idea either—then the result is too quiet and also difficult to understand. That is why sound engineers ensure the perfect sound at every concert and talk show: They regulate each microphone’s gain to match the input signal.

The neurons in the brain can also fine-tune their sensitivity, and even do so autonomously. A new study led by the University of Bonn and the University Hospital Bonn shows how they do this. For this purpose, the participants investigated nerve cell networks that also play a role in vision, hearing and touch. The stimulus first travels to the so-called thalamus, a structure deep in the center of the brain. From there, it is then conducted to the , where it is further processed.

Researchers in the field of optical spectrometry have created a better instrument for measuring light. This advancement could improve everything from smartphone cameras to environmental monitoring.

The research, led by Finland’s Aalto University, developed a powerful, incredibly small spectrometer that fits on a microchip and is run by artificial intelligence. Their research was recently published in the journal Science.

The study used a relatively new class of super-thin materials known as two-dimensional semiconductors, and the result is a proof of concept for a spectrometer that could be easily integrated into a number of technologies such as quality inspection platforms, security sensors, biomedical analyzers, and space telescopes.