Nvidia’s GauGAN turns your crappy sketches into masterpieces
Increasingly AI is being used as a tool to help democratise creativity and unlock people's creative potential.
Key takeaways
- The ability to transfer onto a paper what one sees either in one's mind or with one's eyes is, after all, a skill that many people would love to have, but, for one reason or another, just don’t.
- GauGAN is an Artificial Intelligence (AI) Deep Learning model that lets anyone turn the most basic of sketches into photorealistic masterpieces, and it’s awesome.
Cite or link to this article
Griffin, M. (2019) 'Nvidia’s GauGAN turns your crappy sketches into masterpieces', 311 Institute, 30 April. Available at: https://www.311institute.com/nvidias-gaugan-turns-your-crappy-sketches-into-masterpieces/ (Accessed: 25 October 2026).
It’s long been known that I’m a crappy artist, despite my best efforts at school it was evident early on that I was just never cut out to be the next Picasso or Rembrandt. The ability to transfer onto a paper what one sees either in one's mind or with one's eyes is, after all, a skill that many people would love to have, but, for one reason or another, just don’t.
Anyway, now, thanks to a breakthrough from those great folks at Nvidia I no longer need to just dream about being a great artist, I can give up my aspirations of being a real futurist and become the artist I know I was always destined to be, after the company announced they’ve developed GauGAN. And yes, that's an intentional reference to the post impressionist painter Paul Gauguin. Obs.
GauGAN is an Artificial Intelligence (AI) Deep Learning model that lets anyone turn the most basic of sketches into photorealistic masterpieces, and it’s awesome.
So how does GauGAN take shapeless blobs of colour and turn them into mountains and shimmering Alpine landscapes you might ask? By using a form of AI known as a Generative Adversarial Network (GAN), the same type of AI that today is being used to create everything from films and fake celebrities, to fake news, as well as the world’s first generations of “Creative Machines," one of which just sold a painting for over $400,000, and others that are helping design Amazon’s new clothing lines, and invent products as well as helping people create their own videos just by writing what they’d like to see. And much more. In short GAN’s are helping democratise creativity and innovation and that makes them one of my top technologies to watch.
The best description of how a GAN works is "One neural network, called the generator, generates new data instances, while the other, the discriminator, evaluates them for authenticity; I.E. the discriminator decides whether each instance of data that it reviews belongs to the actual training dataset or not."
In the case of GauGAN the AI learned to create fantastic images by using a discriminator network to compare them to real images. As such, GauGAN "knows" what a field or forest would look like in whatever certain shape you provide. You make the sketch, tell GauGAN where everything should go, and then the program fills in all the details for you. Congratulations, you’re an artist, or should I say artiste!?
"It's like a colouring book picture that describes where a tree is, where the sun is, where the sky is," said Brian Catanzaro vice president of applied deep learning research at NVIDIA. "And then the neural network is able to fill in all of the detail and texture, and the reflections, shadows and colors, based on what it has learned about real images."
Take a look at the video to see more, and you can try the online demo for yourself here.
What this means for your organisation
Drawing skill is no longer the barrier.
GauGAN lets anyone turn the most basic sketch into a photorealistic image. The user marks where the tree, sun and sky go, and the program fills in detail, texture, reflections and shadows. Creative work now depends more on a clear idea than on a steady hand.
The same technique reaches far beyond images.
GANs are already used to make films, fake celebrities and fake news. Creative machines built on them have sold a painting for over $400,000 and helped design Amazon's new clothing lines. 311 rates GANs as Act now, and Creative Machines as Prepare.
Telling real from fake needs a plan.
A GAN works because one network creates new data and another judges whether it looks real. That contest is what makes the output so convincing. Organisations should decide now how they will check and label the images they use and receive.
Three questions for your next leadership meeting
- Which of our creative tasks could staff with no art training now do?
- Where would realistic synthetic images help our products, and where would they harm trust?
- How will we check whether an image we receive is real?
The trends and technologies behind this story
From the 311 Starburst, the 311 Strategic Intelligence Unit’s map of the technologies and trends shaping the next 50 years.
Analysis by the 311 Strategic Intelligence Unit, from Matthew Griffin’s article and 311 data. First published on Fanatical Futurist.
FAQ
Why does this matter?
Increasingly AI is being used as a tool to help democratise creativity and unlock people's creative potential.

About the author
Matthew Griffin Founder, President and Futurist, 311 Institute
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath."
Read full bio
Matthew Griffin is a multi-award winning Futurist and expert in Disruption and Innovation, Geopolitics, Leadership, and Technology, who NASA have described as a "walking encyclopaedia of the future" and a "futurist Polymath." 17-time best selling author of the "Codex of the Future" series, Matthew is the Founder, President and Futurist of the 311 Institute, a global Futures and Deep Futures advisory firm working with royal households, world leaders, G7, G20, and G77 governments, NGOs, and multi-national mid and mega cap firms to help them explore, shape, and lead the next 50 years of business and society.
An award-winning YouTube creator with over a million followers, with an unrivalled global reach and impact, Matthew is a highly sought-after international keynote speaker, lecturer, and mentor who collaborates with global leaders through the United Nations Alliance of Civilizations (UNAOC) and United Nations General Assembly (UNGA) to shape pivotal initiatives such as the UN’s AI for Humanity programme, the United Nations Conference of the Parties (UN COP), and the World Economic Forum in Davos.
As the former Global Head of Cloud, National Security, and Enterprise Sales for companies including Atos, Dell-EMC, and IBM, Matthew has a proven track record of building multi-billion dollar business units and turning failing divisions into market leaders. His ability to identify, analyse, and communicate the implications of hundreds of emerging technologies and trends is unparalleled, and his insights are trusted by many of the world’s most respected organisations, including ABB, Accenture, Adidas, AON, ARM, BCG, Centrica, Citi, Coca-Cola, Dentons, Deloitte, Dow Jones, EY, Google, KPMG, Lego, Legal & General, LinkedIn, Microsoft, PepsiCo, Qualcomm, RWE, Samsung, Siemens AG and Siemens Energy, T-Mobile, UBS, VISA, Walmart, Workday, Worldpay and many others.
Regularly featured in the global media including the AP, BBC, Bloomberg, CNBC, Discovery, Forbes, Khaleej Times, Telegraph, TIME, ViacomCBS, WIRED, and the WSJ, Matthews mission is to help organisations create a fair and sustainable future whose benefits are shared by everyone irrespective of their ability, background, or circumstances.
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Sources and further reading
- Ai playground nvidia.com