Lifeboat Foundation

And it did so on its own without a tether.

Cassie, a bipedal robot that’s all legs, has successfully run five kilometers on a single charge, all without having a tether. The machine serves as the basis for Agility Robotics’ delivery robot Digit, as TechCrunch notes, though you may also remember it for “blindly” navigating a set of stairs. Oregon State University engineers were able to train Cassie in a simulator to enable it to go up and down a flight of stairs without the use of cameras or LIDAR. Now, engineers from the same team were able to train Cassie to run using a deep reinforcement learning algorithm.

Continue reading “Watch Cassie the bipedal robot run a 5K” »

Push materials to their limits, and strange things can occur – such as the discovery of a previously unknown phase of liquid, which has been reported by scientists looking at the development of super-thin, high-density glass.

These types of glass are used in a variety of ways, including in OLED displays and optical fibers, but they can have stability problems. It’s through an effort to tackle those problems that this different type of material has come to light.

Crucially, the newly discovered liquid phase promises thin glass that’s more stable and denser than the materials that have come before – a progression that could open up different ways of using the glass, and even completely new types of devices.

Researchers at the National Aeronautics and Space Administration (NASA) recently announced that it is using artificial intelligence to calibrate images of the Sun.

NASA launched its Solar Dynamics Observatory (SDO) back in early 2010 to conduct research and capture high-definition images of the Sun.

The new artificial intelligence-powered technology is now helping scientists to precisely calibrate captured images at a quick pace in order to generate accurate, usable data. NASA uses the Atmospheric Imagery Assembly (AIA) present at the SDO to capture the Sun’s images across various wavelengths of ultraviolet light every 12 seconds.

With around two weeks still remaining in its crowdfunding campaign, Buck Institute incubated start-up Gerostate Alpha has cruised through its minimum funding target of $300000. The company also revealed that Longevitytech.fund has joined the round as a lead investor, bringing the total investment in the company to more than $500000 so far.

“At Longevitytech.fund, we invest in start-ups focused on aging that will materially ‘move the needle,’” says the investment firm’s managing partner, Petr Sramek. “The team at Gerostate Alpha is poised to do just that in the coming years, and we are very excited to partner with them for the long haul.”

Longevity. Technology: For early stage biotech companies, particularly those targeting aging, securing funding is a constant challenge. Gerostate Alpha is “testing the water” by exploring crowdfunding as another financing option, and seems to have had some success with it. We caught up with the company’s co-founders Simon Melov and Mark Lucanic to find out more.

How true?

However, after subsequent reporting, I discovered a kernel of truth to the rumors of stainless steel and Blue Origin rockets. Three sources have confirmed to Ars that Blue Origin has started working on a project to develop a fully reusable upper stage for New Glenn, which may potentially use stainless steel propellant tanks.

The primary goal of this change is to bring down the overall launch cost of the New Glenn rocket. The vehicle’s large upper stage, with a 7-meter diameter and two BE-3U engines, is costly, and Blue Origin founder Jeff Bezos is looking for ways to make the overall rocket more economical.

Continue reading “Blue Origin has a secret project named ‘Jarvis’ to compete with SpaceX” »

A team of researchers at ARM Inc., has developed a 32-bit microprocessor on a flexible base which the company claims could pave the way to fully flexible smart integrated systems. In their paper published in the journal Nature, the group describes how they used metal−oxide thin-film transistors along with a type of plastic to create their chip and outline ways they believe it could be used.

Microprocessors power a wide range of products, but what they all have in common is their stiffness. Almost all of them are made using silicon wafers, which means that they have to be hard and flat. This inability to bend, the researchers with this new effort contend, is what is preventing the development of products such as smart clothes, smart labels on foods, packaging and even paper products. To meet that need, the team has created what they describe as the PlasticARM—a RISC-based 32-bit microprocessor set on a flexible base. In addition to its flexibility, the new technique allows for printing a microprocessor onto many types of materials, all at low cost.

To create their bendy microprocessor, the researchers teamed with a group at PragmatIC Semiconductor to create a bendable version of the Cortex M0+ microprocessor, which was chosen for its simplicity and small size. To make their chip, (which includes ROM, RAM and interconnections) the team used amorphous silicon fabricated (in the form of metal-oxide thin-film transistors) onto flexible polymers.

Electron-positron pair generation from nonlinear quantum electrodynamics is predicted at high intensities that are, so far, beyond experimental capabilities. Here, simulations predict a high yield of positrons can be obtained from gamma-gamma photon collisions in the linear regime, using counter-propagating pulses and a microstructured target.

Insulin prices have risen exponentially over the last decade. Learn about the team of volunteer scientists working to make it affordable again.

A trio of researchers at Cornell University has found that it is possible to hide malware code inside of AI neural networks. Zhi Wang, Chaoge Liu and Xiang Cui have posted a paper describing their experiments with injecting code into neural networks on the arXiv preprint server.

As computer technology grows ever more complex, so do attempts by criminals to break into machines running new technology for their own purposes, such as destroying data or encrypting it and demanding payment from users for its return. In this new study, the team has found a new way to infect certain kinds of computer systems running artificial intelligence applications.

AI systems do their work by processing data in ways similar to the human brain. But such networks, the research trio found, are vulnerable to infiltration by foreign code.