This could possibly contribute towards saving lives.
Researchers have developed and tested an innovative machine-learning approach that could one day enable the earlier detection of cancer in patients by using smaller blood draws.
FDA approved the device by DermaSensor last week.
In a recent pioneering development, the US Food and Drug Administration (FDA) granted marketing authorization to the DermaSensor, an artificial intelligence-powered hand-held device designed for the early detection of skin cancers such as melanoma, basal cell carcinoma, and squamous cell carcinoma.
Predominantly tailored for use by primary care physicians, DermaSensor uses elastic scattering spectroscopy to look at cellular and subcellular characteristics of suspicious skin lesions.
Continue reading “US FDA approves world’s first AI-powered skin cancer detecting device” »
Tesla is gearing up to build its next-generation Dojo supercomputer at its Gigafactory in Buffalo, New York, as part of a $500 million investment announced by the state’s governor on Friday.
The Dojo supercomputer is designed to process massive amounts of data from Tesla’s vehicles and train its artificial intelligence (AI) systems for autonomous driving and other applications. It is expected to be one of the most powerful computing clusters in the world, surpassing the current leader, NVIDIA.
Soft robots, medical devices, and wearable devices are now common in our daily routines. Researchers at KAIST have created a fluid switch that employs ionic polymer artificial muscles. This switch functions with ultra-low power while generating a force 34 times its own weight. Fluid switches are designed to direct the flow of fluid, guiding it in specific directions to initiate different movements.
KAIST (President Kwang-Hyung Lee) announced on the 4th of January that a research team under Professor IlKwon Oh from the Department of Mechanical Engineering has developed a soft fluidic switch that operates at ultra-low voltage and can be used in narrow spaces.
Stanford researchers have developed a new phase-change memory that could help computers process large amounts of data faster and more efficiently.
We are tasking our computers with processing ever-increasing amounts of data to speed up drug discovery, improve weather and climate predictions, train artificial intelligence, and much more. To keep up with this demand, we need faster, more energy-efficient computer memory than ever before.
Innovations in Memory Technology.
Compared to robots, human bodies are flexible, capable of fine movements, and can convert energy efficiently into movement. Drawing inspiration from human gait, researchers from Japan crafted a two-legged biohybrid robot by combining muscle tissues and artificial materials. Publishing on January 26 in the journal Matter, this method allows the robot to walk and pivot.
Research on biohybrid robots, which are a fusion of biology and mechanics, is recently attracting attention as a new field of robotics featuring biological function. Using muscle as actuators allows us to build a compact robot and achieve efficient, silent movements with a soft touch.
“You want the robot to help others, not others, help the robot,” emphasized Peter Dend, product manager at DEEP Robotics, who dived into the future of Quadruped Robotics during a webinar conducted by Interesting Engineering.
In IE’s first webinar of 2024, a DEEP Robotics representative unveiled a series of robot models employed for various tasks in real time, such as the Robot-Group-Control Dance Show at the 19th Hangzhou Asian Games.
Continue reading “Deep Robotics plan bots for the dark — and a giant one to help at home” »
Gorgan Mohammadi, A., Ganjtabesh, M. Sci Rep 14, 1945 (2024). https://doi.org/10.1038/s41598-024-52299-7
Already, the graphene efforts have offered “a breath of fresh air” to the community, Alicea says. “It’s one of the most promising avenues that I’ve seen in a while.” Since leaving Microsoft, Zaletel has shifted his focus to graphene. “It’s clear that this is just where you should do it now,” he says.
But not everyone believes they will have enough control over the free-moving quasiparticles in the graphene system to scale up to an array of qubits—or that they can create big enough gaps to keep out intruders. Manipulating the quarter-charge quasiparticles in graphene is much more complicated than moving the Majoranas at the ends of nanowires, Kouwenhoven says. “It’s super interesting for physics, but for a quantum computer I don’t see it.”
Just across the parking lot from Station Q’s new office, a third kind of Majorana hunt is underway. In an unassuming black building branded Google AI Quantum, past the company rock-climbing wall and surfboard rack, a dozen or so proto–quantum computers dangle from workstations, hidden inside their chandelier-like cooling systems. Their chips contain arrays of dozens of qubits based on a more conventional technology: tiny loops of superconducting wires through which current oscillates between two electrical states. These qubits, like other standard approaches, are beset with errors, but Google researchers are hoping they can marry the Majorana’s innate error protection to their quantum chip.
Created by Robotiz3d and the University of Liverpool, this autonomous road maintenance robot is stepping out of the lab for its debut journey.
