BARCELONA, SPAIN - FEBRUARY 28: A visitor enjoys a Virtual Reality experience at the SK telecom ... [ ] booth on day 1 of the GSMA Mobile World Congress on February 28, 2022 in Barcelona, Spain. A pattern we see in many industries is that technology changes alongside culture and society, and this remains true for entertainment. The most obvious to consumers has been the shift from terrestrial television to streaming services like Netflix NFLX and Amazon AMZN Prime. The greater flexibility allowed consumers to decouple themselves from an entertainment schedule, being dictated by broadcast times. OTT platforms are aligned with the changing patterns of casualized work and study that focus on individual freedom.

Sensorium, a leading developer in the metaverse space, is joining GITEX GLOBAL for the second year in a row. The company has prepared a range of thrilling activities for all visitors to discover and experience the Sensorium Galaxy metaverse ahead of its public launch. As a key participant of X-Verse, a new GITEX event dedicated to immersive technologies and the Web 3.0 industry, Sensorium will showcase some of its latest innovations in the field of extended reality and artificial intelligence with an interactive multi-day program. Sasha Tityanko, Deputy CEO & Art Director at Sensorium: "GITEX GLOBAL is one of the most influential events for the tech sector, and we are delighted to once again contribute to its outstanding agenda. This year, we wanted to take the metaverse one step closer to everyone, ensuring all visitors can experience the different technological advancements that come together at Sensorium Galaxy. From remarkably natural conversations with AI beings to the high-quality generative music created by our virtual artists and the striking visuals available all around the metaverse. With our program this year, we intend to reshape people's vision of the metaverse and set new standards for the creation of future virtual environments."

Do it all in one app. Social experiences unleashed by AI! Download the Sensorium App and expand your social life via exciting talks with AI-powered virtual beings. Choose a character with a unique personality that unfolds in a dialogue. Start your journey with an intelligent conversation using interactive video and text chat. Build your digital companionship from scratch! Equipped with the most advanced conversational AI, virtual beings can discuss complex topics in a fully unscripted manner without losing context.

Explore a new dimension in social experiences with Sensorium app! Meet an intelligent AI-powered virtual being and talk to it about anything via video or text chat. Download the Sensorium App and expand your social life via exciting talks with AI-powered virtual beings. Choose a character with a unique personality that unfolds in a dialogue. Start your journey with an intelligent conversation using interactive video and text chat. Build your digital companionship from scratch! Equipped with the most advanced conversational AI, virtual beings can discuss complex topics in a fully unscripted manner without losing context.

Multi-modal domain translation typically refers to synthesizing a novel image that inherits certain localized attributes from a 'content' image (e.g. layout, semantics, or geometry), and inherits everything else (e.g. texture, lighting, sometimes even semantics) from a 'style' image. The dominant approach to this task is attempting to learn disentangled 'content' and 'style' representations from scratch. However, this is not only challenging, but ill-posed, as what users wish to preserve during translation varies depending on their goals. Motivated by this inherent ambiguity, we define 'content' based on conditioning information extracted by off-the-shelf pre-trained models. We then train our style extractor and image decoder with an easy to optimize set of reconstruction objectives. The wide variety of high-quality pre-trained models available and simple training procedure makes our approach straightforward to apply across numerous domains and definitions of 'content'. Additionally it offers intuitive control over which aspects of 'content' are preserved across domains. We evaluate our method on traditional, well-aligned, datasets such as CelebA-HQ, and propose two novel datasets for evaluation on more complex scenes: ClassicTV and FFHQ-Wild. Our approach, Sensorium, enables higher quality domain translation for more complex scenes.

You might not know this, but the metaverse is coming. Where you can live a life that expands on reality and can approach hyperrealism. I just took my next big step toward embracing it – and soon you may, too. Within a matter of minutes, I was reborn as a holographic avatar – a digital version of me – with the help of the Avatar Dimension technicians in northern Virginia, just west of the nation's capital. My virtual doppelgänger is ready to embark on digital adventures, be inserted into a video game, a movie, or virtual reality. And it's ready for the metaverse, the persistent alternate reality in cyberspace author Neal Stephenson envisioned in his 1992 science fiction novel "Snow Crash."

You might not know this, but the metaverse is coming. Where you can live a life that expands on reality and can approach hyperrealism. I just took my next big step toward embracing it – and soon you may, too. Within a matter of minutes, I was reborn as a holographic avatar – a digital version of me – with the help of the Avatar Dimension technicians in northern Virginia, just west of the nation's capital. My virtual doppelgänger is ready to embark on digital adventures, be inserted into a video game, a movie or virtual reality. And it's ready for the metaverse, the persistent alternate reality in cyberspace author Neal Stephenson envisioned in his 1992 science fiction novel "Snow Crash."

A central problem to understanding intelligence is the concept of generalisation. This allows previously learnt structure to be exploited to solve tasks in novel situations differing in their particularities. We take inspiration from neuroscience, specifically the Hippocampal-Entorhinal system (containing place and grid cells), known to be important for generalisation. We propose that to generalise structural knowledge, the representations of the structure of the world, i.e. how entities in the world relate to each other, need to be separated from representations of the entities themselves. We show, under these principles, artificial neural networks embedded with hierarchy and fast Hebbian memory, can learn the statistics of memories, generalise structural knowledge, and also exhibit neuronal representations mirroring those found in the brain. We experimentally support model assumptions, showing a preserved relationship between grid and place cells across environments.

This question pops up on the KloudsKape, and my first thought is: How did they know? I'm in the middle of a downward spiral, almost crying as I choke down my lysine-dopamine smoothie and hunch over the teak bar at the Zyme Shack. As with all these questions, I don't even have to ponder before I answer with an eyeblink--it's lonesome, of course. Something about the way you have to purse your lips for a nonexistent kiss at the end of the word, the extra weight of that second syllable--the word lonesome is definitely more miserable. Soon I've answered a dozen other questions in the retinal sensorium, about everything from Koffee Kop to a local bike-lane ordinance, each of them just a sparkly ball rolling around the edges of my vision.