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It is becoming increasingly evident that serverless technology is losing relevance and will soon fade away in the cloud technology space. Why did this happen? What can we learn from this evolution of technology? When serverless computing first hit the streets over a decade ago as a cloud computing paradigm, it saved us from needing to handle detailed compute and storage configurations. Everything was done automatically at the time of execution. This seemed more evolution than revolution because PaaS systems were already doing an aspect of this type of computing. I remember when many wanted me to get on board the hype train and change the focus of my cloud computing podcast to concentrate on serverless. Having been in this industry for a while, I realized this technology would have a more strategic role. Promoting it as a “second coming” was somewhat naive. Today, serverless cloud technology is increasingly overshadowed in the cloud technology marketplace. Initially lauded for its promi

Artificial intelligence has the potential to impact almost every area of life. In this first of a two-part series explaining the technology behind the headlines, this article looks at the different branches of AI technology, and what they can do When we think of artificial intelligence (AI), most of us teeter between excitement and concern about its rise. And with AI, just like anything, the unknowns fuel our concerns. AI and generative AI are unleashing amazing opportunities that will enable governments to be much more productive and effective – getting more done – better, faster, and easier. These technologies will enable us to run virtual simulations before taking real actions, prevent adverse events, prepare for changing conditions, detect areas of concern sooner and with greater accuracy, engage in more meaningful ways, and manage our resources better. So, what is AI? Artificial intelligence is the science of designing systems to support and accelerate human decisions and actions.

Four and a half billion years ago, our solar system was a swirling cloud of gas and dust around the sun, known as a protoplanetary disk. This cosmic nursery eventually condensed to form asteroids and planets. While astronomers can observe protoplanetary disks around distant stars, it is impossible to see what our own solar system looked like in its infancy. However, meteorites that have fallen to Earth provide valuable clues about the early solar system. These metals, such as iridium and platinum, typically condense at high temperatures and were expected to form close to the sun. Surprisingly, the study found that these metals were more abundant in meteorites from the outer disk, which was colder and farther from the sun. The researchers proposed that the early solar disk did not have a ring structure like those observed around other stars, such as HL Tau. Instead, it resembled a doughnut, allowing metal grains to migrate from the inner to the outer disk as it expanded. This migration

In the ever-evolving landscape of manufacturing and automation, the quest for efficiency, quality, and flexibility remains paramount. However, achieving these goals has become increasingly complex due to a myriad of challenges faced by modern manufacturing facilities. Fortunately, advancements in artificial intelligence (AI) and machine learning technologies offer a beacon of hope, promising to revolutionize industrial automation and address these challenges head-on. Challenges Driving Interest in AI and Machine Learning Manufacturers today grapple with the pressing need to predict manufacturing performance with unparalleled precision. Rising operating costs, including energy and software license expenses, coupled with the escalating costs of quality errors such as product recalls, underscore the urgency for solutions that optimize process efficiency. This imperative for efficiency gains drives the heightened interest in AI and machine learning technologies. Generative AI and machine

In late 2019, the previously unremarkable galaxy SDSS1335+0728 suddenly started shining brighter than ever before. To understand why, astronomers have used data from several space and ground-based observatories, including the European Southern Observatory's Very Large Telescope (ESO's VLT), to track how the galaxy's brightness has varied. In a study out today, they conclude that they are witnessing changes never seen before in a galaxy—likely the result of the sudden awakening of the massive black hole at its core. "Imagine you've been observing a distant galaxy for years, and it always seemed calm and inactive," says Paula Sánchez Sáez, an astronomer at ESO in Germany and lead author of the study accepted for publication in Astronomy & Astrophysics. "Suddenly, its [core] starts showing dramatic changes in brightness, unlike any typical events we've seen before." This is what happened to SDSS1335+0728, which is now classified as having an act

The vicinity of Sagittarius A* (Sgr A*), the supermassive black hole at the Milky Way’s center, is hyperactive. Stars, gas, and dust zip around the black hole’s gravitational well at thousands of kilometers per hour. Previously, astronomers thought that only mature stars had been pulled into such rapid orbits. However, a new paper from the University of Cologne and elsewhere in Europe found that some relatively young stars are making the rounds rather than older ones, which raises some questions about the models predicting how stars form in these hyperactive regions.   Astronomers have known about the highly mobile stars surrounding Sgr A* for over thirty years now. They even have their own categorization, known as S stars. However, researchers lacked the equipment to analyze the age of some of these stars, and theories pointed to older, dimmer stars being the most likely to survive near a black hole. But then, as it does so often with science, evidence that challenged the old and dim