This post was co-written with Baptiste Rocca. Views and opinions expressed are solely those of the authors and do not express the views or opinions of their employers. Unless otherwise noted, all images are by the authors. Modelling complex probability distributions is a central problem in machine learning. If this problem can appear under different shapes, one of the most common setting is the following: given a complex probability distribution only described by some available samples, how can one generates a new sample?

A new Google feature will let consumers use artificial intelligence to bring their fantastical creations to (digital) life by just typing a few words. The app, which Bloomberg reported Thursday is currently under development, will have two functions: users can construct cities with its "City Dreamer" function, or customize a family-friendly cartoon monster with its "Wobble" feature. The tools will be available through Google's AI Test Kitchen app, Douglas Eck, a lead scientist at Google, said at the company's AI@ event in New York on Wednesday. The release date for the new app has not yet been announced. The features will use AI imaging technologies to generate hyper-specific images from even short text descriptions.

I explain Artificial Intelligence terms and news to non-experts. Meta AI's new model make-a-video is out and in a single sentence: it generates videos from text. It's not only able to generate videos, but it's also the new state-of-the-art method, producing higher quality and more coherent videos than ever before! You can see this model as a stable diffusion model for videos. Surely the next step after being able to generate images.

Next week, we will start a new series about text-to-image synthesis models. In the last year, this deep learning discipline has seen an astonishing level of progress. You probably heard about OpenAI DALL-E 2, but plenty of other impressive text-to-image generation models have been created in the last few months. We have seen Google coming up with models like Imagen and Parti; Meta has done amazing work with Make-A-Scene; OpenAI created GLIDE and, of course, DALL-E 2. All these models push the boundaries of text-to-image synthesis in ways that challenge human imagination. However, the innovation is not only coming from the big AI labs but also from startups in the space.

I recently started an AI-focused educational newsletter, that already has over 125,000 subscribers. TheSequence is a no-BS (meaning no hype, no news etc) ML-oriented newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Artificial intelligence(AI) research in text-to-image synthesis has gone off the charts in recent months. Models like OpenAI's DALL-E 2, GLIDE or Google's Parti or Imagen have shown the possibilities of emulating creative expression using deep learning.

Meta Platforms Inc. today unveiled an advanced "generative artificial intelligence system" that's designed to help artists better showcase their creativity. The system, called "Make-A-Scene," is meant to demonstrate how AI has the potential to empower anyone to bring their imagination to life. The user can simply describe and illustrate their vision through a combination of text descriptions and freeform sketches, and the AI will come up with a stunning representation of it. As the company explains in a blog post, generative AI is already used by a number of artists to augment their creativity. Examples include expressive avatars, animating children's drawings, creating virtual worlds in the metaverse and producing digital artworks using only text-based descriptions.

Text-to-image generation is the hot algorithmic process right now, with OpenAI's Craiyon (formerly DALL-E mini) and Google's Imagen AIs unleashing tidal waves of wonderfully weird procedurally generated art synthesized from human and computer imaginations. On Tuesday, Meta revealed that it too has developed an AI image generation engine, one that it hopes will help to build immersive worlds in the Metaverse and create high digital art. A lot of work into creating an image based on just the phrase, "there's a horse in the hospital," when using a generation AI. First the phrase itself is fed through a transformer model, a neural network that parses the words of the sentence and develops a contextual understanding of their relationship to one another. Once it gets the gist of what the user is describing, the AI will synthesize a new image using a set of GANs (generative adversarial networks).