Lifeboat Foundation

Like walking and breathing and could one day allow people to control prosthetics simply by thinking…

The US Army is funding a project that could lead to brain-machine interfaces. It includes an algorithm capable of isolating brain signals and linking them to specific behaviors such as walking and breathing.

Continue reading “Army-funded algorithm decodes brain signals responsible for behaviors” »

Scientists have detected two bright radio bursts from a magnetar in our galaxy, as they get closer to discovering the source of the blasts.

Earlier this month, scientists discovered that fast radio bursts were coming from the object, in a major breakthrough in the search for the source of those mysterious blasts of energy. It was the first time an FRB had been detected coming from inside our Milky Way, and also the first time such a blast had been traced back to a particular source.

Now scientists say they have found new bursts coming from that same magnetar. That should help further indicate whether it is really a source of FRBs – and whether the same process could be powering those bursts we have discovered coming from elsewhere in the universe.

To perform tasks that involve moving or handling objects, robots should swiftly adapt their grasp and manipulation strategies based on the properties of these objects and the environment surrounding them. Most robotic hands developed so far, however, have a fixed and limiting structure; thus, they can perform a limited number of movements and can only grasp specific types of objects.

Researchers at Hong Kong University of Science and Technology have recently developed a robotic fingertip that can change its shape and switch across three different configurations, which could allow it to grasp a broader variety of objects. This fingertip’s unique design, outlined in a paper presented at this year’s IEEE International Conference on Automation Science and Engineering (CASE), is inspired by origami, the renowned Japanese art of paper folding.

Continue reading “An origami-inspired robotic fingertip with shape-morphing capabilities” »

This article is part of our reviews of AI research papers, a series of posts that explore the latest findings in artificial intelligence.

Creating machines that have the general problem–solving capabilities of human brains has been the holy grain of artificial intelligence scientists for decades. And despite tremendous advances in various fields of computer science, artificial general intelligence still eludes researchers.

Our current AI methods either require a huge amount of data, or a very large number of hand-coded rules, and they’re only suitable for very narrow domains. AGI, on the other hand, should be able to perform multiple tasks with little data and specific instructions.

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Work could lead to tiny swimming robots for autonomous drug delivery in human body.

Circa 2019

‘I did it. I led all 6 pitches placing my own gear, feeling my way up… It was truly epic’

Analysis of an ancient meteorite from Mars suggests that the mineral zircon may be abundant on the surface of the red planet.

By determining the age and hafnium isotope composition of zircon, researchers from the University of Copenhagen have shown that a population of these crystals were sourced from the deep interior of Mars. If the researchers are correct, it means that the young zircons contain information about the deep, inaccessible interior of Mars, providing insights into the internal structure of the planet.

The uranium-bearing mineral zircon is an abundant constituent of Earth’s continental crust, providing information about the age and origin of the continents and large geological features such as mountain chains and giant volcanoes. But unlike Earth, Mars’s crust is not evolved and is compositionally similar to the crust found under the Earth’s oceans, where zircon is rare. Therefore, zircon is not expected to be a common mineral on Mars.

A technology for building quantum computers that has long been sidelined by major companies is gaining momentum. As quantum computing has transformed from academic exercise to big business over the past decade, the spotlight has mostly been on one approach — the tiny superconducting loops embraced by technology giants such as IBM and Intel. Superconductors enabled Google last year to claim it had achieved ‘quantum advantage’ with a quantum machine that for the first time performed a particular calculation that is beyond the practical capabilities of the best classical computer. But a separate approach, using ions trapped in electric fields, is gaining traction in the quest to make a commercial quantum computer.

A survey of more than 800 AI systems identified four distinct types of tools.