Greg Nichols covers robotics, AI, and AR/VR for ZDNet. A full-time journalist and author, he writes about tech, travel, crime, and the economy for global media outlets and reports from across the U. You might think you should look down toward the water to spot a sub. If you're in North Carolina, you'd be better off looking up. That terrible joke is brought to you by a drone delivery services company called Flytrex, which just announced a partnership with Jersey Mike's Subs.
Chintan Shah is a senior product manager at NVIDIA, focusing on AI products for intelligent video analytics. Chintan manages an end-to-end toolkit for efficient deep learning training and real-time inference. Previously, he developed hardware IPs for NVIDIA GPUs. Chintan holds a master's degree in electrical engineering from North Carolina State University.
Just as asking a single person about their health will provide tailored, personalized information impossible to glean from a large poll, an individual cell's genome or transcriptome can provide much more information about their place in living systems than sequencing a whole batch of cells. But until recent years, the technology didn't exist to get that high resolution genomic data--and until today, there wasn't a reliable way to ensure the high quality and usefulness of that data. Researchers from the University of North Carolina at Charlotte, led by Dr. Weijun Luo and Dr. Cory Brouwer, have developed an artificial intelligence algorithm to "clean" noisy single-cell RNA sequencing (scRNA-Seq) data. The study, "A Universal Deep Neural Network for In-Depth Cleaning of Single-Cell RNA-Seq Data," was published in Nature Communications on April 7, 2022. From identifying the specific genes associated with sickle cell anemia and breast cancer to creating the mRNA vaccines in the ongoing COVID-19 pandemic, scientists have been searching genomes to unlock the secrets of life since the Human Genome Project of the 1990s.
Fifteen-year-old Jordyne Lewis was stressed out. The high school sophomore from Harrisburg, North Carolina, was overwhelmed with schoolwork, never mind the uncertainty of living in a pandemic that has dragged on for two long years. Despite the challenges, she never turned to her school counselor or sought out a therapist. Instead, she shared her feelings with a robot. Lewis has struggled to cope with the changes and anxieties of pandemic life and for this extroverted teenager, loneliness and social isolation were among the biggest hardships.
To effectively interact with humans in crowded social settings, such as malls, hospitals, and other public spaces, robots should be able to actively participate in both group and one-to-one interactions. Most existing robots, however, have been found to perform much better when communicating with individual users than with groups of conversing humans. Hooman Hedayati and Daniel Szafir, two researchers at University of North Carolina at Chapel Hill, have recently developed a new data-driven technique that could improve how robots communicate with groups of humans. This method, presented in a paper presented at the 2022 ACM/IEEE International Conference on Human-Robot Interaction (HRI '22), allows robots to predict the positions of humans in conversational groups, so that they do not mistakenly ignore a person when their sensors are fully or partly obstructed. "Being in a conversational group is easy for humans but challenging for robots," Hooman Hedayati, one of the researchers who carried out the study, told TechXplore.
An artificial intelligence model was able to create 40,000 chemical weapons compounds in just six hours, after being given the task by researchers. A team of scientists were using AI to look for compounds that could be used to cure disease, and part of this involves filtering out any that could kill a human. As part of a conference on potentially negative implications of new technology, biotech startup Collaborations Pharmaceuticals, from Raleigh, North Carolina, 'flipped a switch' in its AI algorithm, and had it find the most lethal compounds.
Far from the stuff of fantasy, artificial intelligence (AI) has become an integral part of our lives. Even the most tech-adverse among us use AI, perhaps unknowingly, when we type a query into Google or plug in GPS. Those who embrace technology, on the other hand, actively look for ways AI can improve their work and personal lives. Though it seems AI is a new phenomenon, the technology has been around since 1956. While AI's popularity has waxed and waned, it gained legitimacy in the 1990s and 2000s when a chess computer program beat the grand chess master Garry Kasparov and speech recognition software was installed on Windows.
An artificial intelligence model was able to create 40,000 chemical weapons compounds in just six hours, after being given the task by researchers. A team of scientists were using AI to look for compounds that could be used to cure disease, and part of this involves filtering out any that could kill a human. As part of a conference on potentially negative implications of new technology, biotech startup Collaborations Pharmaceuticals, from Raleigh, North Carolina, 'flipped a switch' in its AI algorithm, and had it find the most lethal compounds. The team wanted to see just how quickly and easily an artificial intelligence algorithm could be abused, if it were set on a negative, rather than positive task. Once in'bad mode' the AI was able to invent thousands of new chemical combinations, many of which resembled the most dangerous nerve agents in use today, according to a report by The Verge.
DURHAM, NC -- Whether preventing explosions on electrical grids, spotting patterns among past crimes, or optimizing resources in the care of critically ill patients, Duke University computer scientist Cynthia Rudin wants artificial intelligence (AI) to show its work. Especially when it's making decisions that deeply affect people's lives. While many scholars in the developing field of machine learning were focused on improving algorithms, Rudin instead wanted to use AI's power to help society. She chose to pursue opportunities to apply machine learning techniques to important societal problems, and in the process, realized that AI's potential is best unlocked when humans can peer inside and understand what it is doing. Now, after 15 years of advocating for and developing "interpretable" machine learning algorithms that allow humans to see inside AI, Rudin's contributions to the field have earned her the $1 million Squirrel AI Award for Artificial Intelligence for the Benefit of Humanity from the Association for the Advancement of Artificial Intelligence (AAAI).
Whale sharks can carry up to 300 babies at once--at different fetal stages and from different fathers. Zebra sharks experience "virgin birth." These are but a mere sampling of the decade's most fascinating shark discoveries. Some 500 known species of these toothy fish ply our planet's waters, ranging from bite size to bus size, and scientists are still becoming acquainted with most of them. Since 2000, when scientists discovered shark populations were collapsing around the world, research on sharks has ramped up across many fields of study, from paleontology to neuroscience to biomechanics.