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The tech savvy physician: How AI will transform your practice

#artificialintelligence

Artificial intelligence (AI) is no longer just the future of medicine--it is already here, and over time it will transform nearly every area of medical practice, according to experts. AI involves machine learning, where computers get smarter at seeking patterns or connections the more data is input; natural language processing, where computers learn to read and analyze unstructured clinical notes or patient reports; robotic process automation, such as chat bots; diagnostic capabilities such as IBM's Watson; and even more processes that help with patient adherence and administrative tasks. "AI is impacting health care at every level, from the provider to the payer to pharma," according to Dan Riskin, MD, CEO and founder of Verantos, a health care data company in Palo Alto, California, that uses AI to sort through real world evidence. "AI is utilized in a multitude of ways depending on the health care ecosystem," added Athena Robinson, PhD, chief clinical officer at Woebot Labs, a digital therapeutics company in San Francisco. "Some folks think of augmented systems, such as transactional bots that you call to schedule an appointment."


How to build the transportation hub of the future in 5 days

#artificialintelligence

Did you miss a session at the Data Summit? This article was contributed by Andrey Bolshakov, founder and CEO of Evocargo. Autonomous vehicles are subject to far more stringent requirements than long-haul truck drivers and their vehicles. After all, there is no margin of error for robots. That is why self-driving cars are tested more thoroughly, even on public roads, and why the media and the public react so strongly when they fail.


Fighter ace leads tech effort to battle emerging China threat

FOX News

"We must do something about the investment China is making in cyber and AI, as well, because in certain spheres, I believe they are much ahead of us," said Daniel Robinson, CEO and founder of Red 6. FORMER PENTAGON OFFICIAL'NOT SURPRISED' BY CHINESE LAUNCH, SAYS US IS RUNNING OUT OF TIME IN AI RACE Robinson and his team developed what they call a "revolutionary approach" to augmented reality โ€“ a technology that enables fighter pilots to go up in real airplanes and train against virtual enemies. "The whole reason I started this company is pilots must fly," Robinson, a former F-22 pilot, told Fox News. "We can't do this in simulators." "The beautiful thing with this technology is it's reset, reset, reset," Robinson continued. He said a traditional flight hour may give a pilot three looks at a problem set.


Can Science Fiction Wake Us Up to Our Climate Reality?

The New Yorker

This content can also be viewed on the site it originates from. Last summer, the science-fiction writer Kim Stanley Robinson went on a backpacking trip with some friends. They headed into the High Sierra, hiking toward Deadman Canyon--a fifty-mile walk through challenging terrain. Now sixty-nine, Robinson has been hiking and camping in the Sierras for half a century. At home, in Davis, California, he tracks his explorations on a wall-mounted map, its topography thick with ink.


Seattle Researchers Claim to Have Built Artificial Intelligence That Has Morality

#artificialintelligence

Many questions have arisen since the advent of artificial intelligence (AI), even in its most primitive incarnations. One philosophical point is whether AI can actually reason and make ethical decisions in an abstract sense, rather than one deduced by coding and computation. For example, if you program into an AI that intentionally harming a living thing without provocation is "bad" and not to be done, will the AI understand the idea of "bad," or why doing so is bad? Researchers from a Seattle lab claim to have developed an AI machine with its own sense of morality, though the answers it gives only lead to more questions. Are its "morals" only a reflection of those of its creators, or did it create its own sense of right and wrong?


Utilizing Machine Learning and AI in Your GRC Practice

#artificialintelligence

I recently had the chance to visit with Andrew Robinson to discuss utilizing ML and AI into your GRC practice for a sponsored podcast. Robinson is the co-founder and Chief Information Security Officer at 6clicks. You can check out Robinson's podcast episode here. We began with the very basic proposition that many compliance professionals and others are scared by AI in the GRC space. Robinson believes it is based on the fear of the unknown, both to many inside and outside of GRC.


Avoiding Shortcut Solutions in Artificial Intelligence

#artificialintelligence

If your Uber driver takes a shortcut, you might get to your destination faster. But if a machine learning model takes a shortcut, it might fail in unexpected ways. In machine learning, a shortcut solution occurs when the model relies on a simple characteristic of a dataset to make a decision, rather than learning the true essence of the data, which can lead to inaccurate predictions. For example, a model might learn to identify images of cows by focusing on the green grass that appears in the photos, rather than the more complex shapes and patterns of the cows. A new study by researchers at MIT explores the problem of shortcuts in a popular machine-learning method and proposes a solution that can prevent shortcuts by forcing the model to use more data in its decision-making.


Avoiding shortcut solutions in artificial intelligence

#artificialintelligence

If your Uber driver takes a shortcut, you might get to your destination faster. But if a machine learning model takes a shortcut, it might fail in unexpected ways. In machine learning, a shortcut solution occurs when the model relies on a simple characteristic of a dataset to make a decision, rather than learning the true essence of the data, which can lead to inaccurate predictions. For example, a model might learn to identify images of cows by focusing on the green grass that appears in the photos, rather than the more complex shapes and patterns of the cows. A new study by researchers at MIT explores the problem of shortcuts in a popular machine-learning method and proposes a solution that can prevent shortcuts by forcing the model to use more data in its decision-making.


From Fortnite to Fifa, online video game players warned of rise in fraud

The Guardian

Players of online video games such as Roblox, Fortnite and Fifa are being warned to watch out for scammers, amid concerns that gangs are targeting the platforms. Multiplayer games boomed during the pandemic lockdowns as people turned to socialising in virtual spaces. One of the UK's biggest banks, Lloyds, is so concerned about how games are being used that it will this week launch a warning code for players, and a character to go with it. Its research found that a fifth of gamers had either been a victim of a gaming-related scam, or knew someone who had, but less than a third said they knew how to spot one. "Scammers are always looking for new ways to trick people out of their money, and the world of video games is no exception," said Philip Robinson, fraud prevention director at Lloyds.


AI model can predict where it'll rain in the next 90 minutes

#artificialintelligence

Computer scientists at DeepMind and the University of Exeter in England teamed up with meteorologists from the Met Office to build an AI model capable of predicting whether it will rain up to 90 minutes beforehand. Traditional forecasting methods rely on solving complex equations that take into account various weather conditions, such as air pressure, moisture, and the temperature of Earth's atmosphere. The trouble is, at least in Blighty, these systems tend to predict what lies in store for us whole days or weeks ahead. Deep-learning models are better suited for making more near-term forecasts โ€“ such as within the next couple of hours โ€“ according to a paper published by the aforementioned boffins in Nature on Wednesday. There are advantages to using AI algorithms; they don't have to solve thermodynamic equations and are less computationally intensive than other predictive techniques.