Leonardo da Vinci’s portrait of Jesus, known as Salvator Mundi, was sold at a British auction for nearly half a billion dollars in 2017, making it the most expensive painting ever to change hands.
However, even art history experts were skeptical about whether the work was an original of the master rather than one of his many protégés.
Steven Frank is a partner at the law firm Morgan Lewis, specializing in intellectual property and commercial technology law. He’s also half of the husband-wife team that used convolutional neural networks to determine that this painting was likely an authentic da Vinci.
He spoke with NVIDIA AI Podcast host Noah Kravitz about working with his wife, Andrea Frank, a professional curator of art images, to authenticate artistic masterpieces with AI’s help.
Key Points From This Episode:
- Authenticating art is a great challenge, as the characteristics of a painting that distinguish one artist’s work from another’s are very subtle. Determining if a piece is authentic requires an extremely fine analysis of a painting’s highly detailed variants.
- Using large datasets, the Franks trained convolutional neural networks to examine small, manageable segments of masterpieces to analyze and classify their artists’ patterns, down to their brush strokes. The model determined that the Salvator Mundi painting sold five years ago is likely the real work of da Vinci.
Tweetables:
AI might sometimes “be wrong, but it will always be objective, if you train it properly.” — Steven Frank [10:48]
“The most fascinating thing about AI research these days is that you can do cutting-edge AI research on an inexpensive PC … as long as it has an NVIDIA GPU.” — Steven Frank [22:43]
You Might Also Like:
Researchers Chris Downum and Leszek Pawlowicz Use Deep Learning to Accelerate Archaeology
Researchers in the Department of Anthropology at Northern Arizona University are using GPU-based deep learning algorithms to categorize sherds — tiny fragments of ancient pottery.
Wild Things: NVIDIA’s Sifei Liu Talks 3D Reconstructions of Endangered Species
Endangered species can be challenging to study, as they are elusive and the very act of observing them can disrupt their lives. Now, scientists can take a closer look at endangered species by studying AI-generated 3D representations of them.
Metaspectral’s Migel Tissera on AI-Based Data Management
Moondust, minerals and soil types are some of the materials that can be quickly identified and analyzed with AI, based on their images. Migel Tissera is co-founder and CTO of Metaspectral, a Vancouver-based startup that provides an AI-based data management and analysis platform for ultra-high-resolution images.
Subscribe to the AI Podcast
Get the AI Podcast through iTunes, Google Podcasts, Google Play, Castbox, DoggCatcher, Overcast, PlayerFM, Pocket Casts, Podbay, PodBean, PodCruncher, PodKicker, Soundcloud, Spotify, Stitcher and TuneIn. If your favorite isn’t listed here, drop us a note.
Make the AI Podcast Better
Have a few minutes to spare? Fill out this listener survey. Your answers will help us make a better podcast.
The post Real or Not Real? Attorney Steven Frank Uses Deep Learning to Authenticate Art appeared first on The Official NVIDIA Blog.