Wireless networks have traditionally been defined by enhancements to core components such as antennas and communications technologies. We have seen the transition from 2G, to 3G, to 4G, to 5G—but continued progress will need to be made if we want to meet future processing and networking needs. Could the next generation of AI (artificial intelligence) come to the wireless network, unleashing a new revolution in connectivity? Some new research says yes. Researchers at Virginia Tech are exploring this and here is what they have found. The next generation of wireless systems will need two key things: Extreme wireless quality-of-service requirements for perfectly synchronizing worlds. A hyper form of AI that can enable the network to seamlessly orchestrate the physical, virtual, and digital dimensions.  The challenge is this: both the physical constraints of wireless technologies and the limited capacities of current AI technologies. Enter the telecom brain. Researchers are proposing a paradigm shift. Instead of the AI-native wireless system anticipated with 6G, consider a system that is equipped with human levels of intelligence that is learned at the intersection of the digital world and the future wireless networks. This network could provide some common sense ability to digital twins and unleash a new breed of human-like AI agents. The researchers postulate the missing link in the wireless revolution is next-generation AI and the missing link in the next generation of AI is wireless technologies—and at the end of the day the solution is to bring AI closer to human intelligence through common sense. Do you…

There are big opportunities to use AI (artificial intelligence) in healthcare. Consider the example of deep vein thrombosis, which is a condition that occurs when blood clots develop in veins, in legs, and block blood flow, and impacts up to 300,000 Americans every year. In severe cases, these clots can become dislodged and travel to either the heart or lungs, causing stroke, heart attack, or pulmonary embolism. Historically, detection takes place via a duplex ultrasound performed by a trained vascular technologist or sonographer in a designated ultrasound lab. But now AI can help during point-of-care—and some hospitals are beginning to move to this method. As one example, at Allegheny General Hospital, AI has helped detect deep vein thrombosis in cardiac patients. Here AI-powered ultrasound technology can be used to diagnose deep vein thrombosis, from point-of-care images captured by a clinician using a handheld scanner and smartphone. Here is how this can help: Clinicians can capture images of veins in the exam room or at the bedside. Improve patient outcomes by speeding up detection. Address the healthcare worker shortage by giving tools to any healthcare staff rather than just sonogram-trained technicians. Throughout the clinical trial, workers at Allegheny General Hospital will use both the traditional method and the AI method and they will compare and assess the validity of the technology. This hospital joins two others nationwide that are also participating in this clinical trial. The trial will finish and publish its results later this year in preparation for subsequent FDA…