In the first millionths of a second after the Big Bang, the universe was a roiling, trillion-degree plasma of quarks and gluons -- elementary particles that briefly glommed together in countless combinations before cooling and settling into more stable configurations to make the neutrons and protons of ordinary matter. In the chaos before cooling, a fraction of these quarks and gluons collided randomly to form short-lived "X" particles, so named for their mysterious, unknown structures. Today, X particles are extremely rare, though physicists have theorized that they may be created in particle accelerators through quark coalescence, where high-energy collisions can generate similar flashes of quark-gluon plasma. Now physicists at MIT's Laboratory for Nuclear Science and elsewhere have found evidence of X particles in the quark-gluon plasma produced in the Large Hadron Collider (LHC) at CERN, the European Organization for Nuclear Research, based near Geneva, Switzerland. The team used machine-learning techniques to sift through more than 13 billion heavy ion collisions, each of which produced tens of thousands of charged particles.

The conversation is on hold. The Edge community has hit the road... or they're staying home. Preparing for the academic year to begin, wrapping up projects and starting new ones, celebrating with family and friends or contemplating in solitude. After a hiatus, Edge is pleased to revive Summer Postcards: Edgies reporting in from wherever they are and on whatever they're doing, as the dog days wind out and the season comes to a close. As the world slowly returns to a "new normal" with enduring COVID restrictions in the midst of renewed vaccine freedoms, this year's collection is a testament to change (temporary and lasting), a consideration of loss (will travel ever be like it was?), and a celebration of questions (that still need answering). The hammock may be away until next year, but the memories remain. I spent the summer writing and revising the final section of a longish novel I started in 2019. It seems now as though I've been from 1946 to 2021 on my hands and knees. Various lockdowns have been a liberation from obligations and the luggage carousel, and I've never known such sweet and total focus for months on end. We have the luxury of living in the country--no shortage of big skies and moody walks. All our few breaks were in the UK--Scotland, the Lake District, the West country. Even in our remote part of the Lakes, I had to keep on writing--as in photo. The best novel I read this summer was Sandro Veronesi's The Hummingbird. Best non-fiction was Peter Godfrey Smith's Metazoa: Animal Life and the Birth of the Mind. I gave time also to some wonderful novellas--perfect fictional form for you too-busy scientists. IAN MCEWAN is a novelist whose works have earned him worldwide critical acclaim. He is the recipient of the Man Booker Prize for Amsterdam (1998), the National Book Critics' Circle Fiction Award, and the Los Angeles Times Prize for Fiction for Atonement (2003). His most recent novel is Machines Like Me. In 2019, Časlav Brukner and myself were walking on a beach on Lamma Island, near Hong Kong, marvelling together at the astonishing strangeness of quantum phenomena. This summer, the conversation with Časlav has continued on another island, and quite an island: Lesbos, the northern Greek island near the Turkish coast. Lesbos is the place where lyrical poetry was born. Here lived Sappho and Alcaeus.

In order to avoid the worst-case scenario of artificial intelligence (AI) technologies, the European Union is committed to maximizing its economic potential. A draft law from the European Commission would completely ban any use of certain artificial intelligence (AI) systems and would impose a fine of 20 million euros or 4% of income on any country that violates the ban. The final bill will be presented on April 21, 2021. European Union regulators are challenging AI companies to take on more complex tasks in order to protect consumers. It means that the EU will welcome artificial intelligence systems that improve energy efficiency, optimize production, simulate climate change, and analyze national and global data to help governments and businesses overcome problems.

Veteran hypersonic weapons adviser leads research on an artificial intelligence system that trains itself to better analyse wind tunnel experiments.

On patrol with a Ukrainian defence unit carrying out aerial reconnaissance around Kyiv.

In the spring of 2019, artificial intelligence datasets started disappearing from the internet. Such collections -- typically gigabytes of images, video, audio, or text data -- are the foundation for the increasingly ubiquitous and profitable form of AI known as machine learning, which can mimic various kinds of human judgments such as facial recognition. In April, it was Microsoft's MS-Celeb-1M, consisting of 10 million images of 100,000 people's faces -- many of them celebrities, as the name suggests, but also many who were not public figures -- harvested from internet sites. In June, Duke University researchers withdrew their multi-target, multi-camera dataset (DukeMTMC), which consisted of images taken from videos, mostly of students, recorded at a busy campus intersection over 14 hours on a day in 2014. Around the same time, people reported that they could no longer access Diversity in Faces, a dataset of more than a million facial images collected from the internet, released at the beginning of 2019 by a team of IBM researchers. All together, about a dozen AI datasets vanished -- hastily scrubbed by their creators after researchers, activists, and journalists exposed an array of problems with the data and the ways it was used, from privacy, to race and gender bias, to issues with human rights.

Superconductors have long been considered the principal approach for realizing electronics without resistivity. In the past decade, a new family of quantum materials, "topological materials," has offered an alternative but promising means for achieving electronics without energy dissipation (or loss). Compared to superconductors, topological materials provide a few advantages, such as robustness against disturbances. To attain the dissipationless electronic states, one key route is the so-called "magnetic proximity effect," which occurs when magnetism penetrates slightly into the surface of a topological material. However, observing the proximity effect has been challenging.

Although the US remains the leader in the anti-submarine warfare and artificial intelligence domain, China's efforts to harness "quality data" for military use have put Beijing way ahead of the Pentagon, a former admiral of the US Navy said. A new paper published in a journal run by China's aerospace defense industry claims that Beijing has made significant progress in building an AI (artificial intelligence) system that can design new hypersonic weapons autonomously. "It was frustrating for all of us working with large excel spreadsheets, in deciding which programs to advance and which to curb", said Admiral Bill Moran (retired), a former Vice Chief of US Naval Operations, while speaking at a Navy League webinar on artificial intelligence in November 2021. On March 16, a team of researchers led by Professor Le Jialing with China Aerodynamics Research and Development Centre in Mianyang, Sichuan, published their findings in the Journal of Propulsion Technology. Le has been an advisor to the Chinese military on hypersonic weapon technology for more than three decades, according to the publicly available information. As hypersonic research in China advances to Mach 8 – eight times the speed of sound – and above, the volume of experimental data to be processed and analyzed has also been increasing significantly, researchers say.

ABOVE VIDEO: NASA's Perseverance Mars rover is trying to cover more distance in a single month than any rover before it – and it's doing so using artificial intelligence. On the path ahead are sandpits, craters, and fields of sharp rocks that the rover will have to navigate around on its own. At the end of the 3-mile journey, which began March 14, 2022, Perseverance will reach an ancient river delta within Jezero Crater, where a lake existed billions of years ago. This delta is one of the best locations on Mars for the rover to look for signs of past microscopic life. Using a drill on the end of its robotic arm and a complex sample collection system in its belly, Perseverance is collecting rock cores for return to Earth – the first part of the Mars Sample Return campaign.

It is aimed at providing industry exposure to students where experts from reputed organisations guided students to get a deeper understanding of artificial intelligence and machine learning techniques. Madhusudhan Govindaraju, Professor, Department of Computer Science and Vice Provost for International Education and Global Affairs (IEGA), Binghamton University, New York was the chief guest. He mentioned about opportunities available for MAHE students and faculty at Binghamton University. M. D. Venkatesh, Vice Chancellor, MAHE, also spoke at the event, a release mentioned.