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The field of photonics has seen significant advances during the past decades, to the point where it is now an integral part of high-speed, international communications. For general processing photonics is currently less common, but is the subject of significant research. Unlike most photonic circuits which are formed using patterns etched into semiconductor mask using lithography, purely light-based circuits are a tantalizing possibility. This is the focus of a recent paper (press release, ResearchGate) in Nature Photonics by [Tianwei Wu] and colleagues at the University of Pennsylvania.

What is somewhat puzzling is that despite the lofty claims of this being ‘the first time’ that such an FPGA-like device has been created for photonics, this is far from the case, as evidenced by e.g. a 2017 paper by [Kaichen Dong] and colleagues (full article PDF) in Advanced Materials. Here the researchers used a slab of vanadium dioxide (VO2) with a laser to heat sections to above 68 °C where the material transitions from an insulating to a metallic phase and remains that way until the temperature is lowered again. The μm-sized features that can be created in this manner allow for a wide range of photonic devices to be created.

What does appear to be different with the photonic system presented by [Wu] et al. is that it uses a more traditional 2D approach, with a slab of InGaAsP on which the laser pattern is projected. Whether it is more versatile than other approaches remains to be seen, with the use of fully photonic processors in our computers still a long while off, never mind photonics-accelerated machine learning applications.

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.”

Exponential Organizations 2.0: The New Playbook for 10x Growth and Impact — Kindle edition by Ismail, Salim, Diamandis, Peter H., Malone, Michael S., Kurzweil, Ray. Download it once and read it on your Kindle device, PC, phones or tablets. Use features like bookmarks, note taking and highlighting while reading Exponential Organizations 2.0: The New Playbook for 10x Growth and Impact.

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 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 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.

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.

But they’re forgetting something, Chesky recently told the “This Week in Startups” podcast: We don’t even know what kinds of jobs it’ll create.