A.I. re-creations of the "Magnificent Ambersons" stars Joseph Cotten, Agnes Moorehead, Dolores Costello, and Tim Holt. Edward Saatchi first saw "The Magnificent Ambersons," Orson Welles's mangled masterpiece from 1942, when he was twelve years old, in the private screening room of his family's crenellated mansion, in West Sussex. Saatchi's parents had already shown him and his brother "Citizen Kane." But "Ambersons," Welles's follow-up film, about a wealthy Midwestern clan brought low, came with a bewitching backstory: R.K.O. had ripped the movie from the director's hands, slashed forty-three minutes, tacked on a happy ending, and destroyed the excised footage in order to free up vault space, leaving decades' worth of cinephiles to obsess over what might have been. Part of this outcome was the result of studio treachery, but Welles, owing to some combination of hubris and distraction, had let his film slip from his grasp. Saatchi recalled, "Around the family dinner table, that was always such a big topic: How much was Welles responsible for this? Mum was always quite tough on him." Saatchi's father, Maurice, a baron also known as Lord Saatchi, is one of two Iraqi British brothers who founded the advertising firm Saatchi & Saatchi, in 1970, which led their family to become one of the richest in the U.K. Edward's mother, Josephine Hart, who died in 2011, was an Irish writer best known for her erotic thriller "Damage," which was adapted into a film by Louis Malle. Edward, born in 1985, grew up in London and at the sprawling country estate, surrounded by palatial gardens and classical statuary. He described his parents as "movie mad." The actor and Welles biographer Simon Callow, a Saatchi family friend, recalled, "They had a cinema of their own inside the house, and it was a ritual of theirs every week to watch a film together." Aside from old movies, Edward was obsessed with "Star Trek"--especially the Holodeck, a device that conjured simulated 3-D worlds populated by characters who could interact with the members of the Starship Enterprise. That kind of wizardry didn't exist in the real world, at least not yet. But the young prince of the Saatchi castle had faith that someday it would, and that it could bring the original "Ambersons" back from oblivion. "To me, this is the lost holy grail of cinema," Saatchi told me recently, like Charles Foster Kane murmuring about Rosebud. "It just seemed intuitively that there would be some way to undo what had happened."

Graph Edit Distance (GED) is defined as the minimum cost transformation of one graph into another and is a widely adopted metric for measuring the dissimilarity between graphs. The major problem of GED is that its computation is NP-hard, which has in turn led to the development of various approximation methods, including approaches based on neural networks (NN). However, most NN methods assume a unit cost for edit operations -- a restrictive and often unrealistic simplification, since topological and functional distances rarely coincide in real-world data. In this paper, we propose a fully end-to-end Graph Neural Network framework for learning the edit costs for GED, at a fine-grained level, aligning topological and task-specific similarity. Our method combines an unsupervised self-organizing mechanism for GED approximation with a Generalized Additive Model that flexibly learns contextualized edit costs. Experiments demonstrate that our approach overcomes the limitations of non-end-to-end methods, yielding directly interpretable graph matchings, uncovering meaningful structures in complex graphs, and showing strong applicability to domains such as molecular analysis.

On a blustery spring Thursday, just after midterms, I went out for noodles with Alex and Eugene, two undergraduates at New York University, to talk about how they use artificial intelligence in their schoolwork. When I first met Alex, last year, he was interested in a career in the arts, and he devoted a lot of his free time to photo shoots with his friends. But he had recently decided on a more practical path: he wanted to become a C.P.A. His Thursdays were busy, and he had forty-five minutes until a study session for an accounting class. He stowed his skateboard under a bench in the restaurant and shook his laptop out of his bag, connecting to the internet before we sat down. Alex has wavy hair and speaks with the chill, singsong cadence of someone who has spent a lot of time in the Bay Area.

This story is part of Future Tense Fiction, a monthly series of short stories from Future Tense and Arizona State University's Center for Science and the Imagination about how technology and science will change our lives. The other homesteaders, mostly engineers and technicians, seemed to enjoy outings in the lunar rover. But for Eugene, this was a grinding chore that frayed his nerves. Suddenly, Mel's soothing feminine voice reverberated in his cochlear implant. "Would you like some affirmations?" You are a well-respected judge … You have worked hard to get here, to this special time and place …" As Mel went on, it seemed the suit hugged his chest a little less tightly. He relaxed his grip on the wheel. Why, he wondered, had he not remembered this technique without her prompting? Strange how the basic principles of cognitive psych were always slipping from his mind. Fortunately, she was there to remind him. "You are someone who wants what is best for the American lunar community and ...

Locked down in London at the height of the pandemic, bombarded with scary news, I'd felt my connection with nature starting to fray. The daily hour we were allowed to walk in the park for exercise became for me (and many others) a lifeline. And for these walks, I took my phone--not to chat, but to learn. Despite being a well-traveled wildlife filmmaker, I was shamefully clueless about the names and habits of many of the species native to my homeland. Soon a tree-identifying app introduced me to the flora I'd been strolling past.

In his 1950's work Computing Machinery and Intelligence, Alan Turing (1912–1954), who is considered by many the father of Artificial Intelligence, laid out the following question: This question, despite its short length and old origin, still remains a frequent source of discussion, navigating the frontier between technology, philosophy, neuroscience and theology. However, more than half a century ago Turing proposed an indirect way to answer it: Through the famous Turing Test. Turing believed that for us to answer this question without ambiguity, the question itself must be rephrased, specifying or replacing the meaning of'think' and'machines'. Lets first see how we can smooth the'think' out of the equation. Turing proposed to do this by first modifying the question from "Can Machines Think?" to: "Can a machine do what we as thinking entities can do?"

Two years ago, a reporter approached a Harvard professor with a very simple question: what is artificial intelligence? The professor did not have a simple answer. "You are right to be confused." AI is so familiar and yet so indistinct. We've seen the movies, the TED talks and the ads promoting "AI-powered _____."

"Machine learning is to businesses today what petrol engines were to horses back then." For this week's ML practitioner's series, Analytics India Magazine got in touch with Eugene Khvedchenya from Ukraine. Eugene is a Kaggle master and is currently ranked 104 on the global leaderboard. He has more than 10 years of experience in developing computer vision applications, and in this interview, he shared few valuable insights from his decade long journey. Eugene started programming from a young age ever since he saw his father assembling Orion 128 PC, a popular DIY PC in the early 90s.

When I hear news about "AI" these days, what is often meant are methods for pattern recognition and approximations of complex functions, most importantly in the form of Machine Learning. It is true that we have seen impressive applications of Machine Learning systems in a number of different industries such as product personalization, fraud detection, credit risk modeling, insurance pricing, medical image analysis, or self-driving cars. What is the origin of intelligent behavior? Intelligent behavior is the capability of using one's knowledge about the world to make decisions in novel situations: people act intelligently if the use what they know to get what they want. The premise of AI research is that this type of intelligence is fundamentally computational in nature, and that we can therefore find ways to replicate it in machines.

A universally acknowledged truth about living in New York City is that there's very little space to go around. What passes for an entire apartment in Manhattan is considered a walk-in closet in Des Moines. This dearth of square footage has resulted in a couple notable phenomenons: Namely, pocket-emptying rents and some--let's just call it--creative uses of space. Twenty floors up in a luxury midtown Manhattan studio apartment, a hulking piece of furniture sat pressed against the wall. From the front it looked like an entertainment console with built in shelving.