Lisbon musician Moullinex has shared an exclusive short music video showing an endlessly changing landscape of brutalist buildings drawn up by a generative design algorithm with Dezeen. Moullinex, whose real name is Luís Clara Gomes, created two videos that use artificial intelligence (AI) to imagine a series of brutalist buildings. The first video, which the artist shared on his Facebook page, is based on 200 photographs of modernist, concrete buildings. These images acted as the dataset, which was used to train a generative network via the machine learning tool StyleGAN2, to create a string of entirely non-existent buildings with similar characteristics. "It's akin to showing thousands of pictures of a cat to a child and then asking them to draw a brand new cat based on what they now know are cat-like characteristics," Gomes told Dezeen.

Written communication is among the greatest inventions in human history, yet reading and writing are skills most of us take for granted. After we learn them at school, we seldom stop to think about the mental-cum-physical process that turns our language and thoughts into symbols on a piece of paper or computer screen, or the reverse process whereby our brains extract meaning from written symbols. The neural correlates of reading remain a mystery to neuroscientists. They once assumed that an auditory pathway in the brain was used for alphabetic symbols and a visual pathway for Chinese characters but have since discovered experimentally that both neural pathways are used together—if in differing proportions—in each instance. Meanwhile, key aspects of writing's development have yet to be demystified by archaeologists and philologists. Was there a single origin, circa 3100 BCE—either cuneiform in Mesopotamia or hieroglyphs in Egypt—or did writing arise in multiple places independently? When and how did Chinese characters, first identified on Shang oracle bones dated to circa 1200 BCE, originate? And what prompted the invention of the radically simple alphabetic principle, circa 1800 BCE, in a script that contains certain signs resembling Egyptian hieroglyphs? The Secret History of Writing —a BBC television series broadcast in three parts, two of which have been adapted as NOVA's A to Z: The First Alphabet and A to Z: How Writing Changed the World —explores these questions and more. Both versions of the series are intelligent, articulate, and visually imaginative, discussing five millennia of writing—by hand, by printing, and by computer keyboard. The programs feature notable scholars of many scripts and cultures, such as Assyriologist Irving Finkel, Egyptologist Pierre Tallet, and Sinologist Yongsheng Chen, interviewed by Lydia Wilson, an academic with expertise in medieval Arabic philosophy and the winning ability to interrogate authorities at their own level while rendering their views broadly understandable and engaging. The idea for the series grew from a long-standing friendship between writer-director David Sington and calligrapher Brody Neuenschwander, who charismatically demonstrates his skill at penning ancient and modern scripts, using materials such as Egyptian papyrus, European parchment, and Islamic paper. At one point, Neuenschwander observes that Latin alphabetic letter forms, unlike calligraphic scripts such as Chinese and Arabic, were ideally shaped for the movable metal type created by Johannes Gutenberg in the 1450s—a technology that enabled the growth of European literacy and the European scientific revolution beginning in the 16th century. The pairing was so ideal, in fact, that the Gutenberg Bible fooled some scholars for centuries, who believed it was handwritten and cataloged it as such. “I think Gutenberg would have been delighted by our confusion, because what he was trying to achieve with the printing of this book was to produce a book, by a new technique, that people would think was just as good as the manuscripts that they were used to buying and reading,” observes archivist Giles Mandelbrote. He was trying to do “something new that would seem old.” In another scene, Finkel, a lifelong scholar of cuneiform at the British Museum, avidly dissects a few signs on early clay tablets to explain the rebus principle, which permits the sounds of pictograms, written together, to express the sound of an unrelated, nonpictographic word. Thus, for example, the plainly pictographic Sumerian sign for barley, pronounced “she,” can be written beside the pictographic sign for milk, pronounced “ga,” to create two signs read as “shega,” meaning something like “beautiful.” As Finkel reasonably speculates, rebuses are so “obvious” that they could have been developed in languages anywhere in the world, supporting the hypothesis that writing may have arisen on multiple, separate occasions. Today, pictography has returned to writing in the form of international transport symbols and computerized emojis. Meanwhile, many young people in China, having become habituated to smartphone writing, are increasingly using the Romanized spelling known as Pinyin (“spell sound”) and, as a result, some no longer know how to write Chinese characters. Could smartphones, or the internet more generally, eventually lead to a universal writing system, independent of particular languages, like the one envisioned by polymath Gottfried Leibniz in 1698? It is unlikely, in my view, and, according to Wilson, undesirable. “A world of perfect communication is also a world of cultural uniformity,” she cautions.

Have you heard the good news? Disney is available to stream on Google smart displays, just like many other popular streaming services including Netflix and Hulu. Technically you've always been able to watch Disney on a Google smart display (like the Nest Hub Max) by casting from another device, but that's not quite as smooth as calling out, "Hey Google, play Hamilton on Disney ." With the new update, it's easier than ever to catch up on all of your favorite movies and more when your Disney account is connected to a Google smart display--all you have to do is ask. Here's how to watch Disney using your Google-enabled smart display.

Movie ratings are vital to a film's bottom line and determine its impact on audiences. Traditionally, a movie is manually rated by humans watching it, taking into account violence, drug abuse, and sexual content. This dynamic could change soon with the rise of artificial intelligence (AI). Recently, researchers at the USC Viterbi School of Engineering used AI tools to rate a movie within seconds. One of the most impressive aspects of this approach is that the rating could be done based solely on the movie script, without shooting a single shot.

Hyperdub are releasing a special edition of Lawrence Lek's soundtrack to his first feature-length film, AIDOL 爱道. Lek, a simulation artist who uses computer-generated animation and video game engines to create films and virtual worlds, plays with the language of science fiction, music videos and corporate worldbuilding. With AIDOL 爱道, the artist has created a CGI fantasy, deploying 3D rendering and video gaming software. It tells the story of Diva--a fading superstar preparing for a comeback performance at the 2065 "eSports Olympics"--and Geo, an AI who wants to be an artist. Set in a smoke-and-mirrors realm of fantastical architecture, sentient drones and snow-deluged jungles, AIDOL 爱道 revolves around the long and complex struggle between humanity and Artificial Intelligence.

Hollywood filmmakers love to present artificial intelligence as an intelligent agent who's more capable than humans. Luckily, we haven't reached this state -- yet. We still need engineers to develop innovative algorithms and tools to improve human interactions with software and systems. Don't worry -- we can't solve user experience with machine learning, nor are we close. Machine learning has matured over the years, allowing us to gain more insights from the data we collect.

As the recent rise in Covid-19 threatens once again to shutter advertising agencies, film studios, and similar media "factories" globally, a quiet, desperate shift is taking place in the creation of new media, brought about by increasingly sophisticated AI capabilities. A new spate of actors and models are making their way to people's screens, such as pink-haired Imma, right, who has developed an extensive following in Japan on Instagram and TikTok, and is appearing increasingly on the covers of Japanese magazines. Imma joins a growing host of digital avatars who are replacing human actors, models, and photographers with computer-generated equivalents. Cloud-based GPUs and sophisticated game and modeling software have increasingly attracted the attention of a new generation of artist/programmers who are taking advantage of this to generate images, video, and audio that are becoming increasingly indistinguishable from reality, especially when that reality is otherwise captured via jump cuts, and matte overlays that have made tools such as TikTok and Reels the primary tools for video production for the typical Instagram celebrity. The business potential for such virtual models and spokespeople is huge, according to a recent piece by Bloomberg on digital avatars. Such avatars have obvious benefits over their flesh and blood counterparts.

Technology continues to advance at impressive rates. And while the novelty of technologies such as self-parking cars and robotic vacuums have worn off, we are still many years away from the age of computers capable of human thought. Well, that was true before the development of Artificial Neural Networks (ANN), of course. ANN is one of the only techniques currently available for training machines to truly think like people, and it is a tool used within the deep learning space. Artificial intelligence, defined broadly, is the field of training machines to autonomously perform tasks normally thought to require intelligence. Beneath that umbrella is machine learning, in which machines autonomously learn new tasks, and deep learning is a further subcategory of machine learning.

Zyro's Head of AI, Tomas Rasymas told Express.co.uk: "Previously, creating a professional logo was a lengthy and costly process which involved expert help from a designer. "In fact, the average UK small business spends £750 on designing their logo. "But new, experimental AI tools -- like our new logo generator -- will soon make it possible for businesses to create a logo for their brand without the hefty price tag associated with hiring a designer." As part of their ongoing experiments, Zyro's team have been training the AI to draw new logos for some of the world's biggest brands.

Aerial vehicles are revolutionizing the way film-makers can capture shots of actors by composing novel aerial and dynamic viewpoints. However, despite great advancements in autonomous flight technology, generating expressive camera behaviors is still a challenge and requires non-technical users to edit a large number of unintuitive control parameters. In this work we develop a data-driven framework that enables editing of these complex camera positioning parameters in a semantic space (e.g. calm, enjoyable, establishing). First, we generate a database of video clips with a diverse range of shots in a photo-realistic simulator, and use hundreds of participants in a crowd-sourcing framework to obtain scores for a set of semantic descriptors for each clip. Next, we analyze correlations between descriptors and build a semantic control space based on cinematography guidelines and human perception studies. Finally, we learn a generative model that can map a set of desired semantic video descriptors into low-level camera trajectory parameters. We evaluate our system by demonstrating that our model successfully generates shots that are rated by participants as having the expected degrees of expression for each descriptor. We also show that our models generalize to different scenes in both simulation and real-world experiments. Supplementary video: https://youtu.be/6WX2yEUE9_k