Lifeboat Foundation: Safeguarding Humanity
Toggle light / dark theme

Blog – Page 5673

Researchers have developed a new technique, called MonoCon, that improves the ability of artificial intelligence (AI) programs to identify three-dimensional (3D) objects, and how those objects relate to each other in space, using two-dimensional (2D) images. For example, the work would help the AI used in autonomous vehicles navigate in relation to other vehicles using the 2D images it receives from an onboard camera.

“We live in a 3D world, but when you take a picture, it records that world in a 2D image,” says Tianfu Wu, corresponding author of a paper on the and an assistant professor of electrical and computer engineering at North Carolina State University.

“AI programs receive visual input from cameras. So if we want AI to interact with the world, we need to ensure that it is able to interpret what 2D images can tell it about 3D space. In this research, we are focused on one part of that challenge: how we can get AI to accurately recognize 3D objects—such as people or cars—in 2D images, and place those objects in space.”

Read more | >

You may not be able to teach an old dog new tricks, but Cornell researchers have found a way to train physical systems, ranging from computer speakers and lasers to simple electronic circuits, to perform machine-learning computations, such as identifying handwritten numbers and spoken vowel sounds.

The experiment is no mere stunt or parlor trick. By turning these physical systems into the same kind of that drive services like Google Translate and online searches, the researchers have demonstrated an early but viable alternative to conventional electronic processors—one with the potential to be orders of magnitude faster and more energy efficient than the power-gobbling chips in data centers and server farms that support many artificial-intelligence applications.

“Many different physical systems have enough complexity in them that they can perform a large range of computations,” said Peter McMahon, assistant professor of applied and engineering physics in the College of Engineering, who led the project. “The systems we performed our demonstrations with look nothing like each other, and they seem to [be] having nothing to do with handwritten-digit recognition or vowel classification, and yet you can train them to do it.”

Read more | >

For humans, background noise is generally just a minor irritant. But for quantum computers, which are very sensitive, it can be a death knell for computations. And because “noise” for a quantum computer increases as the computer is tasked with more complex calculations, it can quickly become a major obstacle.

But because quantum computers could be so incredibly useful, researchers have been experimenting with ways to get around the noise problem. Typically, they try to measure the noise in order to correct for it, with mixed success.

A group of scientists from the University of Chicago and Purdue University collaborated on a new technique: Instead of directly trying to measure the noise, they instead construct a unique “fingerprint” of the noise on a quantum as it is seen by a program run on the computer.

Read more | >

A few weeks ahead the Beijing 2022 Winter Olympics, Chinese engineers have presented a six-legged skiing robot that expertly slaloms down a snowy white slope in Shenyang, China. The team of engineers said that the robot stands on a pair of skis with four of its legs and grips poles using its two other limbs.

Researchers have put it to tests in both beginner and intermediate slopes and have proven to stay upright and avoid obstacles. The robot was developed by engineers from the Shanghai Jiao Tong University.

Read more | >

A robot has performed laparoscopic surgery on the soft tissue of a pig without the guiding hand of a human—a significant step in robotics toward fully automated surgery on humans. Designed by a team of Johns Hopkins University researchers, the Smart Tissue Autonomous Robot (STAR) is described today in Science Robotics.

“Our findings show that we can automate one of the most intricate and delicate tasks in surgery: the reconnection of two ends of an intestine. The STAR performed the procedure in four animals and it produced significantly better results than humans performing the same procedure,” said senior author Axel Krieger, an assistant professor of mechanical engineering at Johns Hopkins’ Whiting School of Engineering.

The robot excelled at intestinal anastomosis, a procedure that requires a high level of repetitive motion and precision. Connecting two ends of an intestine is arguably the most challenging step in gastrointestinal surgery, requiring a surgeon to suture with high accuracy and consistency. Even the slightest hand tremor or misplaced stitch can result in a leak that could have catastrophic complications for the patient.

Read more | >

Pioneer Suzana Herculano-Houzel discusses the challenges and solutions of comparing brain size and function across species and shares her groundbreaking insights into the uniqueness, or lack thereof, of the human brain. #WorldSciU

This lecture was recorded on XXX at the World Science Festival in New York City.

Experience the associated free online course at World Science U: XXX

Official Site: https://www.worldscienceu.com.

Continue reading “WSU Master Class: Big Brains, Small Brains with Suzana Herculano-Houzel” | >