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Attorney Uses Deep Learning to Authenticate Art | NVIDIA Blog

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.
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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]

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