The Ohio State University: The deadly impact of urban streets that look like highways

The Ohio State University: The deadly impact of urban streets that look like highways. “Serious auto crashes in urban areas are more likely on city streets that look to drivers like highways, new research suggests. The study used a novel approach: Ohio State University researchers applied machine learning techniques to analyze more than 240,000 images of road segments in Columbus, Ohio, taken from Google Street View. The goal was to see what the roads looked like to drivers and whether that was linked to serious and deadly crashes.”

New York Times: How Native Americans Are Trying to Debug A.I.’s Biases

New York Times: How Native Americans Are Trying to Debug A.I.’s Biases. “Ms. [Chamisa] Edmo explained that tagging results are often ‘outlandish’ and ‘offensive,’ recalling how one app identified a Native American person wearing regalia as a bird. And yet similar image recognition apps have identified with ease a St. Patrick’s Day celebration, Ms. [Davar] Ardalan noted as an example, because of the abundance of data on the topic. As Mr. [Tracy] Monteith put it, A.I. is only as good as the data it is fed. And data on cultures that have long been marginalized, like Native ones, are simply not at the levels they need to be.”

University of Central Florida: UCF Researchers Develop Rapid, Highly Accurate Test to Detect Viruses like COVID-19

University of Central Florida: UCF Researchers Develop Rapid, Highly Accurate Test to Detect Viruses like COVID-19. “University of Central Florida researchers have developed a device that detects viruses like COVID-19 in the body as fast as and more accurately than current, commonly used rapid detection tests. The optical sensor uses nanotechnology to accurately identify viruses in seconds from blood samples.”

Microsoft News: HRH The Duke of Cambridge visits Microsoft’s UK headquarters to learn about Project SEEKER as part of his work with The Royal Foundation

Microsoft News: HRH The Duke of Cambridge visits Microsoft’s UK headquarters to learn about Project SEEKER as part of his work with The Royal Foundation . “The first-of-its-kind multispecies artificial intelligence model to combat the $23 billion illegal wildlife trafficking industry has been developed by Microsoft. Project SEEKER can be easily installed in luggage and cargo scanners at airports, ports, and borders, and will automatically alert enforcement agencies when it detects an illegal wildlife item. Officials can then seize the objects, which can be used as evidence in criminal proceedings against the smugglers.”

Georgia Tech: Through Another’s Eyes: University Researchers, Facebook Release Massive Dataset to Expand Innovation in AI

Georgia Tech: Through Another’s Eyes: University Researchers, Facebook Release Massive Dataset to Expand Innovation in AI. “Imagine a collection of assistive technologies that could help a user learn a new skill, assist an elder individual with a task around the home, or help detect autism in early childhood. There exists an endless list of possibilities where artificial intelligence could impact humanity, but to do so it must see the world as we do — in the first person. A consortium of universities brought together by Facebook AI, including Georgia Tech, has collaborated to compile the largest dataset ever collected on egocentric computer vision — or computer vision from the first-person point of view.”

Popular Science: Use your phone to identify plants, landmarks, and other mysterious objects

Popular Science: Use your phone to identify plants, landmarks, and other mysterious objects. “You don’t need us to tell you just how smart the smartphone has become: From recognizing our voices to plotting complex routes in seconds, this device is a real box of tricks. With the right app, they can also help identify what’s in the world around us, whether it’s the breed of the dog that’s just come up to make friends with you, or information about a landmark you’re visiting.”

VentureBeat: Bias persists in face detection systems from Amazon, Microsoft, and Google

VentureBeat: Bias persists in face detection systems from Amazon, Microsoft, and Google. “Companies say they’re working to fix the biases in their facial analysis systems, and some have claimed early success. But a study by researchers at the University of Maryland finds that face detection services from Amazon, Microsoft, and Google remain flawed in significant, easily detectable ways. All three are more likely to fail with older, darker-skinned people compared with their younger, whiter counterparts. Moreover, the study reveals that facial detection systems tend to favor ‘feminine-presenting’ people while discriminating against certain physical appearances.”

Tech Xplore: Teaching AI to see depth in photographs and paintings

Tech Xplore: Teaching AI to see depth in photographs and paintings . “Researchers in SFU’s Computational Photography Lab hope to give computers a visual advantage that we humans take for granted—the ability to see depth in photographs. While humans naturally can determine how close or far objects are from a single point of view, like a photograph or a painting, it’s a challenge for computers—but one they may soon overcome.”

New York Times: Using Computer Vision to Create A More Accurate Digital Archive

New York Times: Using Computer Vision to Create A More Accurate Digital Archive. “This video series from R&D features team members describing their roles, processes and the specific technical challenges they encounter while building and shipping projects. Along with each episode, we’ll share relevant background, resources, references and advice for anyone interested in creating something similar or learning more…. In this episode, R&D Intern Lasse Nordahl explains the process of converting over 10 million scanned images of articles from The Times’s archive into machine-readable text.”

Salina Post: Web-based AI program encourages users to submit photos of bees for IDs

Salina Post: Web-based AI program encourages users to submit photos of bees for IDs. “A Kansas State University researcher’s effort to develop an artificial intelligence tool for identifying bees has created quite a buzz already. Brian Spiesman, an assistant professor in K-State’s Department of Entomology, launched the website…earlier this year to relieve a backlog of information needed to help track trends in bee populations across the world.”