Lifeboat Foundation

AI And Robots For Law And Order — Irakli Beridze — Head, Artificial Intelligence and Robotics, UNICRI – United Nations Interregional Crime and Justice Research Institute.

Irakli Beridze is the Head of the Centre for Artificial Intelligence and Robotics at The United Nations Interregional Crime and Justice Research Institute (UNICRI).

Continue reading “Irakli Beridze, Head, Centre for Artificial Intelligence and Robotics — UNICRI — United Nations” »

Half a century after the last astronauts left the Moon, the idea of sending crews to Mars still seems like some sort of vague space policy notion. After all, crews have yet to revisit the Moon. So, even today, talk of getting astronauts to Mars seems largely confined to PowerPoint presentations.

Thus, it was precisely that sense of inexactitude that prompted a young South African-born entrepreneur named Elon Musk to begin his quest to make the dream of boots on Mars a reality.

It’s a notion that is chronicled with alacrity in Eric Berger’s page-turning new book “Liftoff: Elon Musk and the Desperate Early Days that Launched SpaceX.” Berger, senior space editor at Ars Technica, writes with the kind of hard-won insider authority that only comes through covering the nuts and bolts of the commercial space industry for the past twenty years.

The sounds of 30 impacts are heard, some slightly louder than others, said NASA in its press release. SuperCam, equipped with a microphone, is using the laser to interrogate the composition of rock on the red planet. The variations in the zapping sound picked up the equipment would help the scientists in understanding the physical structure of the rocks and is a key component in probing the signs of ancient life.

“Variation in the intensity of the zapping sounds will provide information on the physical structure of the targets, such as its relative hardness or the presence of weathering coatings,” said NASA.

Continue reading “NASA shares first recording of Perseverance firing its laser on Mars” »

Researchers at Tufts University School of Engineering have created light-activated composite devices able to execute precise, visible movements and form complex three-dimensional shapes without the need for wires or other actuating materials or energy sources. The design combines programmable photonic crystals with an elastomeric composite that can be engineered at the macro and nano scale to respond to illumination.

The research provides new avenues for the development of smart light-driven systems such as high-efficiency, self-aligning solar cells that automatically follow the sun’s direction and angle of light, light-actuated microfluidic valves or soft robots that move with light on demand. A “photonic sunflower,” whose petals curl towards and away from illumination and which tracks the path and angle of the light, demonstrates the technology in a paper that appears March 12th, 2021 in Nature Communications.

Color results from the absorption and reflection of light. Behind every flash of an iridescent butterfly wing or opal gemstone lie complex interactions in which natural photonic crystals embedded in the wing or stone absorb light of specific frequencies and reflect others. The angle at which the light meets the crystalline surface can affect which wavelengths are absorbed and the heat that is generated from that absorbed energy.

It didn’t take long. Intelligence agencies and cybersecurity researchers had been warning that unpatched Exchange Servers could open the pathway for ransomware infections in the wake of swift escalation of the attacks since last week.

Now it appears that threat actors have caught up.

According to the latest reports, cybercriminals are leveraging the heavily exploited ProxyLogon Exchange Server flaws to install a new strain of ransomware called “DearCry.”

New Browser Side-Channel Attack Allows Sites Track Visitors with JavaScript Disabled.

Most new achievements in artificial intelligence (AI) require very large neural networks. They consist of hundreds of millions of neurons arranged in several hundred layers, i.e. they have very ‘deep’ network structures. These large, deep neural networks consume a lot of energy in the computer. Those neural networks that are used in image classification (e.g. face and object recognition) are particularly energy-intensive, since they have to send very many numerical values from one neuron layer to the next with great accuracy in each time cycle.

Computer scientist Wolfgang Maass, together with his Ph.D. student Christoph Stöckl, has now found a design method for artificial neural networks that paves the way for energy-efficient high-performance AI hardware (e.g. chips for driver assistance systems, smartphones and other mobile devices). The two researchers from the Institute of Theoretical Computer Science at Graz University of Technology (TU Graz) have optimized artificial neuronal networks in computer simulations for image classification in such a way that the neurons —similar to neurons in the brain—only need to send out signals relatively rarely and those that they do are very simple. The proven classification accuracy of images with this design is nevertheless very close to the current state of the art of current image classification tools.

What is the origin of black holes and how is that question connected with another mystery, the nature of dark matter? Dark matter comprises the majority of matter in the Universe, but its nature remains unknown.

Multiple gravitational wave detections of merging black holes have been identified within the last few years by the Laser Interferometer Gravitational-Wave Observatory (LIGO), commemorated with the 2017 physics Nobel Prize to Kip Thorne, Barry Barish, and Rainer Weiss. A definitive confirmation of the existence of black holes was celebrated with the 2020 physics Nobel Prize awarded to Andrea Ghez, Reinhard Genzel and Roger Penrose. Understanding the origin of black holes has thus emerged as a central issue in physics.

Surprisingly, LIGO has recently observed a 2.6 solar-mass black hole candidate (event GW190814, reported in Astrophysical Journal Letters 896 (2020) 2, L44). Assuming this is a black hole, and not an unusually massive neutron star, where does it come from?