Asymptomatic spread of COVID-19 is a huge contributor to the pandemic, but of course if there are no symptoms, how can anyone tell they should isolate or get a test? MIT research has found that hidden in the sound of coughs is a pattern that subtly, but reliably, marks a person as likely to be in the early stages of infection. It could make for a much-needed early warning system for the virus. The sound of one's cough can be very revealing, as doctors have known for many years. AI models have been built to detect conditions like pneumonia, asthma and even neuromuscular diseases, all of which alter how a person coughs in different ways.

In recent years, unsupervised deep learning approaches have received significant attention to estimate the depth and visual odometry (VO) from unlabelled monocular image sequences. However, their performance is limited in challenging environments due to perceptual degradation, occlusions and rapid motions. Moreover, the existing unsupervised methods suffer from the lack of scale-consistency constraints across frames, which causes that the VO estimators fail to provide persistent trajectories over long sequences. In this study, we propose an unsupervised monocular deep VO framework that predicts six-degrees-of-freedom pose camera motion and depth map of the scene from unlabelled RGB image sequences. We provide detailed quantitative and qualitative evaluations of the proposed framework on a) a challenging dataset collected during the DARPA Subterranean challenge; and b) the benchmark KITTI and Cityscapes datasets. The proposed approach outperforms both traditional and state-of-the-art unsupervised deep VO methods providing better results for both pose estimation and depth recovery. The presented approach is part of the solution used by the COSTAR team participating at the DARPA Subterranean Challenge.

Even as the U.S. Army attempts to integrate cutting edge technologies into its operations, many of its platforms remain fundamentally in the 20th century. The way tank crews operate their machine has gone essentially unchanged over the last 40 years. At a time when the military is enamored with robotics, artificial intelligence and next generation networks, operating a tank relies entirely on manual inputs from highly trained operators. "Currently, tank crews use a very manual process to detect, identify and engage targets," explained Abrams Master Gunner Sgt. "Tank commanders and gunners are manually slewing, trying to detect targets using their sensors. Once they come across a target they have to manually select the ammunition that they're going to use to service that target, lase the target to get an accurate range to it, and a few other factors."

MIT researchers have identified a powerful new antibiotic compound using a machine-learning algorithm. A deep-learning model identifies a powerful new drug that can kill many species of antibiotic-resistant bacteria. Using a machine-learning algorithm, MIT researchers have identified a powerful new antibiotic compound. In laboratory tests, the drug killed many of the world's most problematic disease-causing bacteria, including some strains that are resistant to all known antibiotics. It also cleared infections in two different mouse models.

On an otherwise routine July day, inside a laboratory at Duke University, two rhesus monkeys sat in separate rooms, each watching a computer screen that featured an image of a virtual arm in two-dimensional space. The monkeys' task was to guide the arm from the center of the screen to a target, and when they did so successfully, the researchers rewarded them with sips of juice. But there was a twist. The monkeys were not provided with joysticks or any other devices that could manipulate the arm. Rather, they were relying on electrodes implanted in portions of their brains that influence movement.

While there are many modes and preferences when it comes to transportation, every person is a pedestrian at some point in their day. Unfortunately, being a pedestrian can be hazardous. For instance, in 2018 in the United States, there was a more than three percent increase in the number of pedestrians killed in traffic crashes. According to the National Highway Traffic Safety Administration, the number totaled 6,283 deaths, which was the highest since 1990. Accidents involving pedestrians are preventable tragedies.

Martin Aspen, the purported author of a September report that tried to link Presidential nominee Joe Biden's family to the Chinese government, was fabricated for the lone purpose of disseminating the information, the man behind the scandal has revealed. Christopher Balding, a blogger and occasional journalist, revealed to NBC News in a piece published Thursday that the identity of the "intelligence" document's co-author, Martin Aspen, was made up. Aspen, previously labeled as a Swiss security analyst, had a profile picture that was generated using computer software. It was an "entirely fictional individual created solely for the purpose of releasing this report," Balding said. Public records also do not support Aspen's existence.

Fifteen years ago, when I returned home after fighting in Iraq, a friend asked me to describe the bravest thing I saw anyone do. I had led a Marine platoon in the Second Battle of Fallujah, in 2004, and had seen plenty of heroism--Marines dragging their wounded off machine-gun-swept streets, or fighting room to room to recover a comrade's body. But none of these compared to the cumulative heroism of the 19- and 20-year-old infantrymen who placed their bodies across that fatal funnel--a doorway with a potential enemy inside--every day. Clearing the enemy from the city, house by house, was a game of Russian roulette played on a grand scale. You never knew who might be waiting on the other side of the door.

Researchers are using machine learning algorithms trained on simulations of space debris as part of a key project. With more than 34,000 pieces of junk orbiting around the Earth, their removal is becoming a matter of safety. Earlier this month an old Soviet Parus navigation satellite and a Chinese ChangZheng-4c rocket were involved in a near miss and in September the International Space Station conducted a manoeuvre to avoid a possible collision with an unknown piece of space debris. A project led by ClearSpace-1, a spin off from research lab EPFL in Zurich, will recover the now obsolete Vespa Upper Part, a payload adapter orbiting 660km above the Earth that was once part of the European Space Agency's Vega rocket. The mission, set for 2025, aims to ensure that it re-enters the atmosphere and burns up in a controlled way.

Technology keeps creating challenges for intellectual property law. The infamous case of the "monkey selfie" challenged the notion of not just who owns a piece of intellectual property, but what constitutes a "who" in the first place. Last decade's semi-sentient monkey is giving way to a new "who": artificial intelligence. The rapid rise of AI has forced the legal field to ask difficult questions about whether an AI can hold a patent at all, how existing IP and patent laws can address the unique challenges that AI presents, and what challenges remain. The answers to these questions are not trivial; stakeholders have poured billions upon billions of dollars into researching and developing AI technologies and AI-powered products and services across academia, government, and industry.