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With millions of patients under its belt, digital health startup K Health is looking to scale its artificial intelligence technology in hospitals, starting with new strategic investor Cedars-Sinai.

The problem with turning to the internet.

With a new $59 million investment, digital health startup K Health is looking to scale its AI technology in hospitals, starting with new strategic investor Cedars-Sinai.

Continue reading “This AI Chatbot Has Helped Doctors Treat 3 Million People–And May Be Coming To A Hospital Near You” »

A new study explores how artificial intelligence can not only better predict new scientific discoveries but can also usefully expand them. The researchers, who published their work in Nature Human Behaviour, built models that could predict human inferences and the scientists who will make them.

The authors also built models that avoided human inference to generate scientifically promising “alien” hypotheses that would not likely be considered until the distant future, if at all. They argue that the two demonstrations—the first allowing for the acceleration of human discovery, while the second identifies and passes over its blind spots—means that a human-aware AI would allow for movement beyond the contemporary scientific frontier.

“If you build in awareness to what people are doing, you can improve prediction and leapfrog them to accelerate science,” says co-author James A. Evans, the Max Palevsky Professor in the Department of Sociology and director of the Knowledge Lab. “But you can also figure out what people can’t currently do, or won’t be able to do for decades or more into the future. You can augment them by providing them that kind of complementary intelligence.”

A recent paper published in Nature Aging by researchers from Integrated Biosciences, a biotechnology company combining synthetic biology and machine learning.

Machine learning is a subset of artificial intelligence (AI) that deals with the development of algorithms and statistical models that enable computers to learn from data and make predictions or decisions without being explicitly programmed to do so. Machine learning is used to identify patterns in data, classify data into different categories, or make predictions about future events. It can be categorized into three main types of learning: supervised, unsupervised and reinforcement learning.

For three days, artificial intelligence planned my days, gave me (limited) advice and even took a stab at writing this article. Now I’m left wondering: What did it get out of our arrangement?

“The reason I was invited on is I’m the poster child for getting your ass kicked in the public markets by A.I. since I lost 40% of value in five minutes,” Rosensweig said. “So for those of you who didn’t want to take that, I took it for you,” Rosensweig said with apparent sarcasm. “My pleasure.”

Chegg’s new A.I. tool, called CheggMate, will be a personal learning assistant for students that creates bespoke lesson plans. Trained on a set of 100 million correct answers to 17 million new questions posed by students each year over the past decade, the A.I. will create a tailored learning experience for students, taking into account their learning style, the date of their exam or deadline, and even how they’re feeling that day, among other factors. It will also connect students to remote study groups and help them find job opportunities.

“Just imagine the following scenario,” Rosensweig said, “you start to have a conversation with somebody that knows you, knows how you’re feeling that day, knows what you’re studying, knows when your midterm is, knows what you’re good at, what you’re bad at, builds you a personalized plan, advocates for you.”

Danish architect Bjarke Ingels discusses what it’s like to be one of the world’s best-known architects and the current limitations of AI in this interview.

Ingels sat down with Dezeen at the UIA World Congress of Architects in Copenhagen after delivering a keynote address to delegates.

As the session ended, the Bjarke Ingels Group (BIG) founder and creative director was surrounded by fans hoping to get a photograph with him.

This segment originally aired on July 10, 2023.
Yahoo Finance Tech Editor Dan Howley reports on lawsuits against OpenAI regarding copyright law violations including Sarah Silverman and others.

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Continue reading “OpenAI: Sarah Silverman and others launch lawsuits over alleged copyright violation concerns” »

AI had its nuclear bomb threshold. The biggest thing that happens to human technology maybe since the splitting of the atom.

A conversation with Science Fiction author and a NASA consultant David Brin about the existential risks of AI and what approach we can take to address these risks.

Continue reading “From Sci-Fi to Reality: Addressing AI Risks — with David Brin” »

In a study published recently in Advanced Intelligent Systems, researchers from Queen Mary University of London have made significant advancements in the field of bionics with the development of a new type of electric variable-stiffness artificial muscle that possesses self-sensing capabilities. This innovative technology has the potential to revolutionize soft robotics and medical applications.

Muscle contraction hardening is not only essential for enhancing strength but also enables rapid reactions in living organisms. Taking inspiration from nature, the team of researchers at QMUL’s School of Engineering and Materials Science has successfully created an artificial muscle that seamlessly transitions between soft and hard states while also possessing the remarkable ability to sense forces and deformations.

Dr. Ketao Zhang, a Lecturer at Queen Mary and the lead researcher, explains the importance of variable stiffness technology in artificial muscle-like actuators. “Empowering robots, especially those made from flexible materials, with self-sensing capabilities is a pivotal step towards true bionic intelligence,” says Dr. Zhang.