Lamborghini's new hybrid supercar includes a three-level drift mode and three axial flux motors The supercar pulls out the stops with a screaming 10,000 revolutions per minute at the redline. With a top speed of 213 miles per hour and a 10,000 rpm redline, the Lamborghini Temerario is a wild machine. Breakthroughs, discoveries, and DIY tips sent every weekday. Lamborghini's legacy gas-only machines have been unapologetically loud, brash, and in your face with sonorous symphonies conducted by fuel-guzzling V12 and V10 engines. Today, the brand is in its electrification age, with three plug-in hybrids: the Urus SE SUV, the top-tier Revuelto, and the newest Raging Bull, the Temerario.

Many practical applications involve classification tasks on time series data, e.g., the diagnosis of cardiac insufficiency by evaluating the recordings of an electrocardiogram. Since most machine learning algorithms for classification are not capable of dealing with time series directly, mappings of time series to scalar values, also called representations, are applied before using these algorithms. Finding efficient mappings, which capture the characteristics of a time series is subject of the field of representation learning and especially valuable in cases of few data samples. Time series representations based on information theoretic entropies are a proven and well-established approach. Since this approach assumes a total ordering it is only directly applicable to univariate time series and thus rendering it difficult for many real-world applications dealing with multiple measurements at the same time.

After an exhausting 12-hour shift caring for patients, it's hard to blame frontline workers for forgetting to sing "Happy Birthday" twice to guarantee a full 30 seconds of proper hand-washing. Though at times tedious, the process of confirming such detailed, protective measures like the amount of time hospital employees spend sanitizing their hands, the cleaning status of a room, or the number of beds available is crucial to preventing the spread of infectious diseases such as COVID-19. DARVIS, an AI company founded in San Francisco in 2015, automates tasks like these to make hospitals "smarter" and give hospital employees more time for patient care, as well as peace of mind for their own protection. The company developed a COVID-19 infection-control compliance model within a month of the pandemic breaking out. It provides a structure to ensure that workers are wearing personal protective equipment and complying with hygiene protocols amidst the hectic pace of hospital operations, compounded by the pandemic.

During your stay in a hospital, computer systems are collecting and analyzing all sorts of data about you. In the background of all the beeping and gadgetry, an electronic medical record contains thousands of bits of information about your medical history, vital signs and laboratory results. Sentara Healthcare is now deploying artificial intelligence to use that data to stop patients from contracting life-threatening sepsis. Earlier this year the system launched a sepsis prediction tool that alerts doctors and nurses when a patient is at risk of developing the deadly infection. The tool --looks at relationships in order to predict what might happen in the future,-- said Dr. David Mohr, Sentara's vice president of clinical informatics and transformation.

During your stay in a hospital, computer systems are collecting and analyzing all sorts of data about you. In the background of all the beeping and gadgetry, an electronic medical record contains thousands of bits of information about your medical history, vital signs and laboratory results. Sentara Healthcare is now deploying artificial intelligence to use that data to stop patients from contracting life-threatening sepsis. Earlier this year the system launched a sepsis prediction tool that alerts doctors and nurses when a patient is at risk of developing the deadly infection. The tool "looks at relationships in order to predict what might happen in the future," said Dr. David Mohr, Sentara's vice president of clinical informatics and transformation.

There's been a barrage of insurtech products hitting the market for several years now, creating confusion for some agency owners trying to decipher what is relevant to them, how to implement these products and whether to wait for new agency systems. Regardless of the confusion, choosing to do nothing is not an option, according to agency consultant Chris Burand, founder of Chris Burand & Associates, who says agencies have to get in the technology game if they want to not only thrive but also survive – and the sooner the better. "Your peers, your competitors, they're going to wait five, 10 years," Burand said. "They're going to wait on their agency system management company to get all these modules all into one system. It's so critical to move early and fast and move intelligently."

When Tavis Rudd decided to build a system that would allow him to write computer code using his voice, he was driven by necessity. In 2010, he tore his rotator cuffwhile rock-climbing, forcing him to quit climbing while the injury healed. Rather than sitting idle, he poured more of his energy into his work as a self-employed computer programmer. "I'd get in the zone and just go for hours," he says. Whether it was the increased time pounding away at a keyboard or the lack of other exercise, Rudd eventually developed a repetitive strain injury (RSI) that caused his outer fingers to go numb and cold, leaving him unable to type/code without pain.

That could be the setup for a very bad joke -- or a tremendously fascinating conversation. Fortunately for us, it was the latter. On a blustery evening in late September, in a private room at a bar near Times Square, the magazine gathered five brilliant scientists and thinkers around a table for a three-hour dinner. In the (edited) transcript below -- moderated by Mark Jannot, a story editor at the magazine and a former editor in chief of Popular Science -- you can see what they had to say about the future of medicine, health care and humanity. MARK JANNOT: For years, many pregnant women have undergone amniocentesis to test for rare metabolic disorders and other fetal issues. And couples who use in vitro fertilization can screen the embryos for genetic abnormalities. What sorts of advances in genetic screening and manipulation are coming, and where do you see that taking us? CATHERINE MOHR: When I was pregnant with my daughter, my husband and I were joking, "Well, if she gets the best of both of us, she'll be a superhero, and if she gets the worst of both of us, she's not going to make it out of first grade." And so we were rolling the genetic dice, which you do when you choose to have a child. It's not totally random, of course; there's all kinds of great things about your mate -- that's why you chose them -- and hopefully there's some pretty good things about you, too. But the temptation to engineer what you think of as the best combination, as we become more capable of doing it, I think it's going to be irresistible for a lot of people. You're investing so much of your life into this little being, and you're going to love this child, and you want to give them every advantage in life. We are already screening for diseases to avoid passing on our "bad" genes, but this same technology will let us start screening for our "best" genes -- the ones we really want to pass on. As screening becomes cheaper, easier and more reliable, and more people are using assisted-reproductive technologies, I see us, as a society, sliding down that slippery slope pretty far, one couple at a time, each trying to do what's best for the child they are hoping to bring into the world.

Cisco Systems is making what is perhaps the most significant development in the decade-long history of its UCS server line with the introduction of the C480ML, an Nvidia GPU-loaded heavyweight aimed at the burgeoning market for AI and machine learning. The C480ML is the second major new Cisco UCS server rollout in little more than three months. Its introduction is part of a concerted effort to capitalize on dramatic big data customer growth and to send a message to enterprises and solution providers that Cisco intends to rule the AI roost. The number of customers running big data workloads on UCS servers has increased 18X in the last four years, according to Han Yang, Cisco senior product manager. "We're seeing a tremendous amount of growth for big data workloads, and those are the same customers that are asking for additional analytic capabilities like machine learning and deep learning," Yang said.

As far back as 3,500 years ago ancient Egyptian doctors were performing invasive surgeries. Even though our tools and knowledge have improved drastically over time, until very recently surgery was still a manual task for human hands. When it came out about 15 years ago, Intuitive Surgical's da Vinci surgical robot was a major innovation. The da Vinci robot helps surgeons be more precise and dexterous and to remove natural hand tremors during surgery. In the years since da Vinci first came out, many other surgical robots have arrived.