Chatbots and image generators, newly on the rise, have sparked our imaginations--and our fears. As artificial-intelligence machines sharpen their ability to translate written prompts into images that accurately capture both style and substance, some visual artists worry that their specialized skills might be rendered irrelevant. Even so, the new technologies at our disposal broaden our understanding of the relationship between artist and work. In her cover for the April 24 & May 1, 2023, Innovation & Tech Issue, her first for the magazine, JooHee Yoon addresses the topic in a clever image that illustrates the reciprocity and the tension that can exist between artists and these high-tech tools (is the robot hand drawing the real hand, or vice versa?). Yoon's cover also demonstrates what makes artists unique: their ideas and their point of view. M. C. Escher (1898-1972), a Dutch graphic artist whose approach was an inspiration for Yoon, is a case in point.

Recent techniques for approximating Nash equilibria in very large games leverage neural networks to learn approximately optimal policies (strategies). One promising line of research uses neural networks to approximate counterfactual regret minimization (CFR) or its modern variants. DREAM, the only current CFR-based neural method that is model free and therefore scalable to very large games, trains a neural network on an estimated regret target that can have extremely high variance due to an importance sampling term inherited from Monte Carlo CFR (MCCFR). In this paper we propose an unbiased model-free method that does not require any importance sampling. Our method, ESCHER, is principled and is guaranteed to converge to an approximate Nash equilibrium with high probability. We show that the variance of the estimated regret of ESCHER is orders of magnitude lower than DREAM and other baselines. We then show that ESCHER outperforms the prior state of the art -- DREAM and neural fictitious self play (NFSP) -- on a number of games and the difference becomes dramatic as game size increases. In the very large game of dark chess, ESCHER is able to beat DREAM and NFSP in a head-to-head competition over $90\%$ of the time.

Attributed to Juvenal,a this title phrase translates to "Who will watch the watchers?" In the 21st century, we may well ask this question as we invest increasingly in machine learning methods, platforms, applications, and designs. Nowhere is this more evident as we see increased excitement and investment in artificial intelligence (AI) for military application. In some ways, this is an old story. Early computers were used to improve the calculation of ballistics settings and, with the invention of radar, automatic fire-control systems became important parts of offensive and defensive systems.

This extended abstract presents the first stages of a research on in-painting suited for art reconstruction. We introduce M.C Eschers Print Gallery lithography as a use case example. This artwork presents a void on its center and additionally, it follows a challenging mathematical structure that needs to be preserved by the in-painting method. We present our work so far and our future line of research.

Escher's artwork was an inspiration for Douglas Hofstadter's 1979 book "Gödel, Escher, Bach: An ... [ ] Eternal Golden Braid", sometimes referred to as the Bible of artificial intelligence. The field of artificial intelligence has never been the subject of more attention and analysis than it is today. Almost every week, it seems, a new bestselling book comes out examining the technology, business or ethics of AI. Yet few of the topics and debates at the center of today's AI discourse are new. While not always recognized by commentators, artificial intelligence as a serious academic discipline dates back to the 1950s.

The exploration of geometrical patterns stimulates imagination and encourages abstract reasoning which is a distinctive feature of human intelligence. In cognitive science, Gestalt principles such as symmetry have often explained significant aspects of human perception. We present a computational technique for building artificial intelligence (AI) agents that use symmetry as the organizing principle for addressing Dehaene's test of geometric intelligence \cite{dehaene2006core}. The performance of our model is on par with extant AI models of problem solving on the Dehaene's test and seems correlated with some elements of human behavior on the same test.

The field of artificial intelligence has never been the subject of more attention and analysis than it is today. Almost every week, it seems, a new bestselling book comes out examining the technology, business or ethics of AI. Yet few of the topics and debates at the center of today's AI discourse are new. While not always recognized by commentators, artificial intelligence as a serious academic discipline dates back to the 1950s. For well over half a century, many of the world's leading minds have devoted themselves to the pursuit of machine intelligence and have grappled with what it would mean to succeed in that pursuit.

Escher's artwork was an inspiration for Douglas Hofstadter's 1979 book "Gödel, Escher, Bach: An ... [ ] Eternal Golden Braid", sometimes referred to as the Bible of artificial intelligence. The field of artificial intelligence has never been the subject of more attention and analysis than it is today. Almost every week, it seems, a new bestselling book comes out examining the technology, business or ethics of AI. Yet few of the topics and debates at the center of today's AI discourse are new. While not always recognized by commentators, artificial intelligence as a serious academic discipline dates back to the 1950s.

Artificial Intelligence is the need of the hour. This technology of today is neither an elementary school math nor a rocket science application. The understanding of AI not only allows business decision makers and enthusiasts to make advancements in technologies but also let them make processes better. Another term that is doing the rounds is artificial general intelligence (AGI) which encompasses human-level cognitive ability making automation think and work like a human mind. So how do you benefit from AI and the latest advancements that move around it?

This year is the 40th anniversary of the publication of one of the cult books of my generation: Gödel Escher Bach by Douglas Hofstadter. This Pulitzer prize-winning tome was essential reading in the 1980s for emerging geeks like me. But, despite its name, it is not a book about the composer Bach, the artist Escher or even the mathematician Kurt Gödel. It is about consciousness and Hofstadter's belief that this elusive concept is related to the idea of what he calls "a strange loop". To celebrate the anniversary, I am staging a triptych of events at the Barbican in London called Strange Loops, looking at the impact of technology on what it means to be human.