Like biologically based systems (left), complex emergent behaviors--which arise when separate components are merged together in a coordinated system--also result from neuromorphic networks made up of quantum-materials-based devices (right). Pandemic lockdown forces a new perspective on designs for futuristic AI-based computing devices. Isaac Newton's groundbreaking scientific productivity while isolated from the spread of bubonic plague is legendary. University of California San Diego physicists can now claim a stake in the annals of pandemic-driven science. A team of UC San Diego researchers and colleagues at Purdue University have now simulated the foundation of new types of artificial intelligence computing devices that mimic brain functions, an achievement that resulted from the COVID-19 pandemic lockdown.
Despite a tough year for many, US companies are accelerating plans to implement artificial intelligence (AI). Another 54% are heading there fast. And they've moved way beyond just laying the foundation. Many are reaping rewards from AI right now, in part because it proved to be a highly effective response to the challenges brought about by the COVID-19 crisis. In fact, most of the companies that have fully embraced AI already report seeing major benefits.
The existential threat of COVID-19 has highlighted an acute need to develop working therapeutics against emerging health threats. One of the luxuries deep learning has afforded us is the ability to modify the landscape as it unfolds -- so long as we can keep up with the viral threat, and access the right data. As with all new medical maladies, oftentimes the data needs time to catch up, and the virus takes no time to slow down, posing a difficult challenge as it can quickly mutate and become resistant to existing drugs. This led scientists from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) to ask: how can we identify the right synergistic drug combinations for the rapidly spreading SARS-CoV-2? Typically, data scientists use deep learning to pick out drug combinations with large existing datasets for things like cancer and cardiovascular disease, but, understandably, they can't be used for new illnesses with limited data.
Isaac Newton's groundbreaking scientific productivity while isolated from the spread of bubonic plague is legendary. University of California San Diego physicists can now claim a stake in the annals of pandemic-driven science. A team of UC San Diego researchers and colleagues at Purdue University have now simulated the foundation of new types of artificial intelligence computing devices that mimic brain functions, an achievement that resulted from the COVID-19 pandemic lockdown. By combining new supercomputing materials with specialized oxides, the researchers successfully demonstrated the backbone of networks of circuits and devices that mirror the connectivity of neurons and synapses in biologically based neural networks. Like biologically based systems (left), complex emergent behaviors--which arise when separate components are merged together in a coordinated system--also result from neuromorphic networks made up of quantum-materials-based devices (right).
Much of the U.S. artificial intelligence (AI) discussion revolves around futuristic dreams of both utopia and dystopia. However, it bears remembering that AI is also becoming a real-world economic fact with major implications for national and regional economic development as the U.S. crawls out of the COVID-19 pandemic. Based on advanced uses of statistics, algorithms, and fast computer processing, AI has become a focal point of U.S. innovation debates. Even more, AI is increasingly viewed as the next great "general purpose technology"--one that has the power to boost the productivity of sector after sector of the economy. All of which is why state and city leaders are increasingly assessing AI for its potential to spur economic growth.
Singapore is in the midst of a three-week trial for a pair of autonomous robots that patrol the public for "undesirable social behaviors" that include smoking in prohibited areas and violating COVID-19 gathering regulations. The pair of robots, known as Xavier, are equipped with cameras that can provide 360-degree footage and sensors that allow them to navigate in public and analyze potential public safety violations. According to a press release from the Home Team Science and Technology Agency, if Xavier detects an undesirable behavior, it will alert a public officer control center and officers can respond in person or remotely via the robot's interactive dashboard. Five Singaporean government agencies are involved in the testing of Xavier. "The deployment of ground robots will help to augment our surveillance and enforcement resources," said Lilly Ling, the Singapore Food Agency's East Regional Office Director, in a press release.
Singapore is well known for its tough laws (and penalties for flouting them). Now it has a new ally in the fight against chewing gum, littering and bigger misdemeanors. The country has started testing a robot named Xavier. Over the next three weeks, Xavier robots will monitor the crowds of Singapore's Toa Payoh Central to look for what the nation's authorities describe as "undesirable social behaviors" -- including any group of people. The country's current COVID-19 safety measure forbids congregations of more than five people. To gauge the crowds, Xavier models have cameras that create 360-degree views.
Experiences with AI and machine learning at CVS Health and St. Luke's Health System in Boise, Idaho, are having practical benefits to the two organizations. CVS Health is learning how to scale AI applications using machine learning, especially through the house of machine learning operations (MLOps) tools, according to Nels Lindahl, director of Clinical Decision Systems, speaking in a virtual session at the recent Ai4 Conference held virtually recently. And St. Luke's Health Center put a COVID-19 prediction program, a supply chain purchase engine and a demand-based staffing application into initial production using AI and machine learning, said Dr. Justin Smith, senior director of advanced analytics at St. Luke's, also at a recent Ai4 virtual conference session. "We are at an MLOps tipping point, where ML has a growing production footprint, with adoption picking up pace and awareness and understanding at an all-time high," stated Lindahl. "ML tech can now deliver; people are seeing real use cases in the wild and having them grow; it's real."
Approximately 30% of the world's data volume is created by the healthcare industry, according to RBC and IDC. The compound annual growth rate of healthcare data between 2018 and 2025 is predicted to be 36%, a much faster rate of data growth than that of other industries, including financial services at 26%. Last year, healthcare's share of all the data created worldwide amounted to 21 zettabytes or 21 trillion gigabytes. Also last year, Covid-19 made all of us aware of the important role of high-quality data in the successful enlistment of AI in humanity's battle with diseases and in keeping people healthy. Centaur Labs, a startup focused on improving the quality of healthcare data, today announced $15 million in funding to advance their mission to label the world's medical data. The Series A round was led by Matrix Partners with participation from other funds including Accel, Global Founders Capital, Susa Ventures, Y Combinator, and individual investors.
It seems counterintuitive, but robots may be a growing bright spot for American manufacturing. The latest example is an announcement by a leading autonomous delivery company that it will create two new facilities in southern Nevada as it moves to scale production of its latest autonomous delivery vehicle. Overall, the market for autonomous mobile robots (AMRs) and autonomous ground vehicles (AGVs) is forecasted to generate over $10bn by 2023 according to Interact Analysis, and that prediction relies on data from before the COVID-19 pandemic. Delivery robots in particualr are quickly coming of age as COVID lingers and touchless fulfillment becomes the norm. Sidestepping municipal red tape, enterprising companies like Starship Technologies have launched pilot programs in controlled access spaces, such as college campuses.