Lifeboat Foundation

A quartet of chemists at the University of Oxford has, for the first time, found a way to get two beryllium atoms to bond with one another. In their paper published in the journal Science, Josef Boronski, Agamemnon Crumpton, Lewis Wales and Simon Aldridge, describe their process and how they managed to do it in a safe way—and at room temperature. Jason Dutton with La Trobe University, has published a Perspective piece in the same journal issue, outlining the work done by the team in England.

Beryllium is a strong but lightweight, alkaline earth metal. It is also brittle.

Beryllium only ever occurs naturally when mixed with other elements, forming minerals. It is often found in gemstones such as emeralds. And it is used in a variety of applications, from telecommunications equipment to computers and cell phones. It is also mixed with other metals to create alloys used in applications such as gyroscopes and electrical contacts.

The European Space Agency (ESA) launched the BepiColombo mission in 2018, and it is set to enter orbit around Mercury in 2025. In the meantime, it will be making several flybys of the planet, including a close approach today. That’s because the spacecraft’s route takes it on a series of increasingly close flybys that use the planet’s gravity to adjust its course each time.

In total, between its launch in 2020 and its arrival in Mercury orbit in 2025, the spacecraft will make one flyby of Earth, two of Venus, and six of Mercury. The Earth and Venus flybys are already complete, and today BepiColombo is making its third Mercury flyby, coming within 150 miles of the planet’s surface.

The maneuver will help to slow the spacecraft down so that it can eventually enter orbit. “As BepiColombo starts feeling Mercury’s gravitational pull, it will be traveling at 3.6 kilometers per second [2.2 miles per second] with respect to the planet. That’s just over half the speed it approached with during the previous two Mercury flybys,” explained ESA flight dynamics expert Frank Budnik in a statement. “And this is exactly what the point of such events is. Our spacecraft began with far too much energy because it launched from Earth and, like our planet, is orbiting the sun. To be captured by Mercury, we need to slow down, and we’re using the gravity of Earth, Venus and Mercury to do just that.”

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Every day, tens of thousands of songs are released. This constant stream of options makes it difficult for streaming services and radio stations to choose which songs to add to playlists. To find the ones that will resonate with a large audience, these services have used human listeners and artificial intelligence. This approach, however, lingering at a 50% accuracy rate, does not reliably predict if songs will become hits.

Now, researchers in the US have used a comprehensive machine learning technique applied to brain responses and were able to predict hit songs with 97% accuracy.

“By applying machine learning to neurophysiologic data, we could almost perfectly identify hit songs,” said Paul Zak, a professor at Claremont Graduate University and senior author of the study published in Frontiers in Artificial Intelligence. “That the neural activity of 33 people can predict if millions of others listened to new songs is quite amazing. Nothing close to this accuracy has ever been shown before.”

Gravitational waves, like the discovery of the Higgs boson in 2012, have made their mark on a decade of extraordinary discoveries in physics. Unlike gravity, which is created when massive objects leave their mark in the fabric of spacetime, gravitational waves are very weak ripples in spacetime that are caused by gravity-accelerated masses.

So far, researchers have been able to detect the gravitational waves produced by the melting together of very heavy objects, such as black holes or neutron stars. When this happens, these echoes from the past reverberate through the whole universe and finally reach Earth, allowing us to piece together what happened millions of light-years ago.

Current gravitational-wave observatories can only detect a few gravitational waves as they cover just a narrow spectrum of the whole range of wavelengths that are emitted. Future gravitational-wave observatories, such as the Einstein Telescope, a CERN-recognized experiment, need to be larger in order to search for a larger bandwidth of gravitational waves that could tell us more about the universe.

The design could overcome one of the key challenges facing electrifying larger planes.

DaveAI, a leading virtual sales experience platform, is thrilled to announce the launch of its innovative 3D visualizer for Hindware, a renowned brand in the world of premium sanitaryware. This deployment sets new standards for the virtual showroom experience, providing Hindware customers with an unparalleled level of interactivity and realism.

DaveAI’s 3D visualizer marks an important step forward in the growth of virtual sales, enabling businesses and customers alike to engage with items in a transformative way. Users may now immerse themselves in a visually spectacular virtual environment, where every product detail is brought to life with incredible precision and lifelike accuracy, thanks to modern technology.

“We are excited to partner with DaveAI and bring the 3D visualizer to our customers” said Nitin Dhingra, CDO & Vice President at Hindware Limited. “This cutting-edge technology brings our extensive collection of quality sanitaryware to life in an entirely new way. Our customers can now explore and personalize imaginary bathroom facilities with unprecedented simplicity and realism. This deployment reflects Hindware’s dedication to providing excellent client experiences while remaining at the forefront of industry innovation. We are enthusiastic about the unlimited possibilities that this collaboration opens up, and are looking forward to seeing our customers interact with our products in this immersive virtual environment.”

Airbnb CEO Brian Chesky isn’t afraid of artificial intelligence displacing jobs. In fact, he thinks it’ll create more of them — particularly in the world of entrepreneurship.

Since ChatGPT started gaining popularity last winter, tech icons from Apple co-founder Steve Wozniak to billionaire entrepreneur Mark Cuban have admitted they’re worried that AI will replace human workers in just about every industry.

Continue reading “A.I. will make having a lucrative side hustle or startup much easier, says Airbnb CEO” »

Rocks and minerals contribute essential raw materials for any civilization, and in a technological society minerals (and the rare elements they contain) are especially sought after. In the past, most discoveries of mineral deposits have resulted from perseverance and luck.

In the last 200 years scientists realized that minerals are not distributed randomly. Many of the over 5,000 different minerals occurring on Earth exist in a so-called paragenesis. A paragenesis is a mineral assemblage formed under specific physico-chemical rules, like a certain chemical composition of the host rock or when the right conditions — like temperature and pressure — are met.

A machine learning model can predict the locations of minerals on Earth — and potentially other planets — by taking advantage of patterns in mineral associations.

Continue reading “How AI Can Help Find New Minerals On Earth And Other Planets” »