Lifeboat Foundation

USA: Timely diagnosis and treatment are critical to restore blood flow and reduce injury to the heart muscle and increase a person’s chance of recovery after a heart attack.

A recent study has revealed that technology incorporating artificial intelligence (AI) and electrocardiogram (EKG) testing for patients having a heart attack decreased the time to diagnose and send patients for treatment by almost 10 minutes. The findings from the late-breaking science study conducted in a hospital in Taiwan were presented at the American Heart Association’s Scientific Sessions 2023 held from Nov. 11–13, in Philadelphia.

“Modern AI may now be as good as expert cardiologists in diagnosing serious heart attacks,” said lead study author Chin-Sheng Lin, M.D., Ph.D., a professor, director of the Medical Technology Education Center and vice dean at the School of Medicine, at the National Defense Medical Center, in Taipei, Taiwan. “Hospitals can use AI tools more to help front-line doctors, especially those with less experience. This could lead to faster treatment and less mistakes when it comes to treating patients who are experiencing heart attacks.”

Multimaterial 3D-printing approach produces functional devices in a single shot.

Time to dump Windows and Linux and prepare for infinity and beyond.

The onslaught of press, research and perceived urgency has done little to prepare business and information technology leaders to deploy artificial intelligence-powered technologies.

That’s according to the first Cisco AI Readiness Index, issued Tuesday. The company used a double-blind survey of over 8,000 business and IT leaders worldwide.

The findings are alarming. Although 97% of the organizations say that the urgency around deploying AI tech has risen in the last six months, only 14% feel they’re prepared to deploy and utilize it.

AI and the space industry point the way forward to rethink how we view operating systems. Can we free ourselves and redesign from the ground up?

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A new hallucination index developed by the research arm of San Francisco-based Galileo, which helps enterprises build, fine-tune and monitor production-grade large language model (LLM) apps, shows that OpenAI’s GPT-4 model works best and hallucinates the least when challenged with multiple tasks.

Published today, the index looked at nearly a dozen open and closed-source LLMs, including Meta’s Llama series, and assessed each of their performance at different tasks to see which LLM experiences the least hallucinations when performing different tasks.

Months after signing a letter calling for the pause of AI development, Elon Musk started a new company designed to create it.

The company on Wednesday announced Astro for Business, a version of its household robot that it’s framing as a crime prevention tool for retailers, manufacturers and a range of other industries, in spaces that are up to 5,000 square feet. Astro for Business is launching only in the U.S. to start, and it comes at a steep price point of $2,349.99.

Amazon unveiled Astro, its first home robot, in September 2021. The squat, three-wheeled device can roll around the house to answer Alexa voice commands, and it has a 42-inch periscope camera that allows it to see over countertops or other obstacles to check if a stove has been left on, among other tasks.

Two years on from its debut, the original Astro, which costs $1,599, is available in limited quantities and on an invite-only basis.

An artificial sensory system that is able to recognize fine textures—such as twill, corduroy and wool—with a high resolution, similar to a human finger, is reported in a Nature Communications paper. The findings may help improve the subtle tactile sensation abilities of robots and human limb prosthetics and could be applied to virtual reality in the future, the authors suggest.

Humans can gently slide a finger on the surface of an object and identify it by capturing both static pressure and high-frequency vibrations. Previous approaches to create artificial tactile sensors for sensing physical stimuli, such as pressure, have been limited in their ability to identify real-world objects upon touch, or they rely on multiple sensors. Creating a real-time artificial sensory system with high spatiotemporal resolution and sensitivity has been challenging.

Chuan Fei Guo and colleagues present a flexible slip sensor that mimics the features of a human fingerprint to enable the system to recognize small features on surface textures when touching or sliding the sensor across the surface. The authors integrated the sensor onto a prosthetic human hand and added machine learning to the system.