'Picasso,' we explore the potential for unique, crowd-sourced styles that could provide deep insights into the collective creative psyche of users

Like many people who saw designer Daniel Voshart's Roman emperor portraits created in Artbreeder and Photoshop, I was impressed with the results. Using the neural-net tool Artbreeder, Photoshop and historical references, I have created photoreal portraits of Roman Emperors. For this project, I have transformed, or restored (cracks, noses, ears etc.) 800 images of busts to make the 54 emperors of The Principate (27 BC to 285 AD). Artbreeder uses a machine learning method called generative adversarial network (GAN) to manipulate images. Voshart tweaked images from Photoshop to Artbreeder and back again until he got what he wanted.

Artificial intelligence (AI) is not only affecting industries like business and healthcare. It is also playing an increasing role in the creative industries by ushering in a new era of AI-generated art. AI technologies and tools are often widely accessible to anyone, which is helping to create an entirely new generation of artists. We often hear that AI is going to automate away or take over all human tasks, including those in art, film, and other creative industries. But this is far from the case. AI is a supplemental tool that artists can use to explore new creative territory.

With the rise of artificial intelligence (AI), we have heard how it will begin taking over many human tasks. This conversation has been largely focused around industries like manufacturing, customer service, and healthcare, where machines can carry out tasks incredibly efficiently. The creative realm was thought to be mostly off limits to machines, at least for now. Many believed they would not be able to paint a picture, create music, or write a book like us. These are tasks that absolutely require the free and creative human mind, and art is fundamental to the human experience.

We all love the fact that computers can execute annoying work for us. Work we already know how to do, work that is repeatable and, often, also repetitive. For the past few decades, new processes such as procedural generation have been helping us achieve diverse results with minimal input, leaving us to focus on being creative. Be it in the shape of procedural level generation of early rogue-like games, procedural nature such as Speedtree or, lately, the vast possibilities of procedural texturing with noise procedurality as seen in Substance Designer. Neural networks that generate new data and in the case of so called StyleGAN's it creates images or sequences. These machine learning frameworks are making two AI's play against each other to test and learn what would be considered to be a realistic result. This is based on the library you are feeding the network.

Human-computer image generation using Generative Adversarial Networks (GANs) is becoming a well-established methodology for casual entertainment and open artistic exploration. Here, we take the interaction a step further by weaving in carefully structured design elements to transform the activity of ML-assisted imaged generation into a catalyst for large-scale popular dialogue on complex socioscientific problems such as the United Nations Sustainable Development Goals (SDGs) and as a gateway for public participation in research.

Ancient Roman emperors' faces have been brought to life in digital reconstructions; the unnervingly realistic image project includes the Emperors Caligula, Nero and Hadrian, among others. The features of these long-dead rulers have been preserved in hundreds of sculptures, but even the most detailed carvings can't convey what these men truly looked like when they were alive. To explore that, Canadian cinematographer and virtual reality designer Daniel Voshart used machine learning -- computer algorithms that learn through experience -- in a neural network, a computing system processes information through hierarchies of nodes that communicate in a manner similar to neurons in a brain. In the neural net, called Artbreeder, algorithms analyzed about 800 busts to model more realistic facial shapes, features, hair and skin, and to add vivid color. Voshart then fine-tuned Artbreeder's models using Photoshop, adding details gleaned from coins, artworks and written descriptions of the emperors from historical texts, to make the portraits really come to life.

Some people have spent their quarantine downtime baking sourdough bread. But others -- namely Toronto-based artist Daniel Voshart -- have created painstaking portraits of all 54 Roman emperors of the Principate period, which spanned from 27 BC to 285 AD. The portraits help people visualize what the Roman emperors would have looked like when they were alive. Included are Voshart's best artistic guesses of the faces of emperors Augustus, Nero, Caligula, Marcus Aurelius and Claudius, among others. They don't look particularly heroic or epic -- rather, they look like regular people, with craggy foreheads, receding hairlines and bags under their eyes. To make the portraits, Voshart used a design software called Artbreeder, which relies on a kind of artificial intelligence called generative adversarial networks (GANs).

If you make a purchase, My Modern Met may earn an affiliate commission. Please read our disclosure for more info. They are Roman emperors who lived long ago, but they remain embedded in popular imagination since the fall of the last ruler in 476 CE. They've been immortalized as busts and statues in museums, but a new project is helping to visualize what these people would've really looked like while alive. Daniel Voshart, a Toronto-based cinematographer and designer, has created photorealistic portraits of the 54 emperors of the Principate period (27 BC to 285 CE).