"It's a really tricky kind of model where you want to decline every possible fraudulent transaction, but at the same time, let the legitimate transactions pass through without any friction," he says. "On an average day, we see over a billion transactions, and since data is what fuels AI, we were definitely one of the early adopters." Yet, the benefits of AI adoption surpass improved fraud detection. As such, the application of AI throughout Mastercard has become a priority, Chauhan said. "The use of AI is about future-proofing Mastercard," Chauhan says.

Microsoft is adding new AI features to its popular apps like Word, PowerPoint, and Excel. The new set of tools, called Microsoft 365 Copilot, will let people do things like create PowerPoint decks with a short prompt or summarize meeting recordings. Copilot runs on the same underlying AI technology that powers the buzzy viral chatbot ChatGPT, and is being tested now with a few business partners ahead of a wider release to all users in the "coming months," according to the company. "Today we are at the start of a new era of computing," said Microsoft CEO Satya Nadella in a livestreamed announcement on Thursday. Nadella said Microsoft's new AI products will "remove the drudgery of our daily tasks and jobs, freeing us to rediscover the joy of creation."

From ShutEye to SleepScore, several smartphone apps are available if you're trying to better understand how snoring impacts your rest, allowing you to leave the microphone on overnight to record your raucous nasal grunts and rumbling throat reverberations. But while smartphone apps are helpful for tracking the presence of snores, their accuracy remains an issue when applied to real-world bedrooms with extraneous noises and multiple audible people. Preliminary research from the University of Southampton looks into whether your snores have a signature sound that could be used for identification. "How do you actually track snoring or coughing accurately?" asks Jagmohan Chauhan, an assistant professor at the university who worked on the research. Machine learning models, specifically deep neural networks, might provide assistance in verifying who is performing that snore-phonic symphony.

From ShutEye to SleepScore, several smartphone apps are available if you're trying to better understand how snoring impacts your rest, allowing you to leave the microphone on overnight to record your raucous nasal grunts and rumbling throat reverberations. But while smartphone apps are helpful for tracking the presence of snores, their accuracy remains an issue when applied to real-world bedrooms with extraneous noises and multiple audible people. Preliminary research from the University of Southampton looks into whether your snores have a signature sound that could be used for identification. "How do you actually track snoring or coughing accurately?" asks Jagmohan Chauhan, an assistant professor at the university who worked on the research. Machine learning models, specifically deep neural networks, might provide assistance in verifying who is performing that snore-phonic symphony.

There are plenty of organizations that are dabbling with AI, but relatively few have decided to go all in on the technology. One that is decidedly on that path is Mastercard. Employing a combination of acquisitions and internal capabilities, Mastercard has the clear objective of becoming an AI powerhouse. Just what does that term mean, and how is it being applied at the company? Some refer to the idea of aggressive, pervasive adoption of AI as being "AI first." Others use the term "AI fueled" or "all in on AI" (that's Tom's favorite, since it's the title of his forthcoming book on the subject).

Every year, nearly one out of eight U.S deaths is caused due to heart failure. One of acute heart failure's most common causes is the presence of excess fluid in the lungs. This condition is known as'pulmonary edema.' A patient's excess fluid level often indicates the doctor's course of action, but such determination requires clinicians to rely on subtle features in X-rays that sometimes lead to inconsistent diagnoses and treatment plans. A group of researchers at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) has developed a machine learning model that can analyse the X-ray to quantify how severe the edema is, on a four-level scale ranging from 0 means healthy to 3 which is very bad.

Every year, roughly one out of eight U.S. deaths is caused at least in part by heart failure. One of acute heart failure's most common warning signs is excess fluid in the lungs, a condition known as "pulmonary edema." A patient's exact level of excess fluid often dictates the doctor's course of action, but making such determinations is difficult and requires clinicians to rely on subtle features in X-rays that sometimes lead to inconsistent diagnoses and treatment plans. To better handle that kind of nuance, a group led by researchers at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) has developed a machine learning model that can look at an X-ray to quantify how severe the edema is, on a four-level scale ranging from 0 (healthy) to 3 (very, very bad). The system determined the right level more than half of the time, and correctly diagnosed level 3 cases 90 percent of the time.

In March, as her friends and neighbors were scrambling to pack up and leave campus due to the Covid-19 pandemic, Geeticka Chauhan found her world upended in yet another way. Just weeks earlier, she had been elected council president of MIT's largest graduate residence, Sidney-Pacific. Suddenly the fourth-year PhD student was plunged into rounds of emergency meetings with MIT administrators. From her apartment in Sidney-Pacific, where she has stayed put due to travel restrictions in her home country of India, Chauhan is still learning the ropes of her new position. With others, she has been busy preparing to meet the future challenge of safely redensifying the living space of more than 1,000 people: how to regulate high-density common areas, handle noise complaints as people spend more time in their rooms, and care for the mental and physical well-being of a community that can only congregate virtually.