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Ahmed Elgammal is the founder and director of the Art and Artificial Intelligence Laboratory, and a professor of computer science at Rutgers University.  He developed AICAN, an autonomous AI artist and collaborative creative partner. Dr. Elgammal’s research on knowledge discovery in art history and AI art generation, received wide international ...

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Ali Scott
812-339-1195 X204

Current News

  • 07/11/201907/11/2019

Artrendex’s ArtPI Uses Artificial Intelligence to Revolutionize Art Discovery

ArtPI (artpi.co) is a new interface or API driven by artificial intelligence that’s poised to transform the way art gets discovered, displayed, and sold. It promises to transform art discovery the way Shazam transformed music discovery.

ArtPI detects features and patterns using overarching visual style characteristics based in art theory and history. Built from the ground up specifically for art and drawing on centuries of artworks, ArtPI can find visually similar works, label styles...

Press

  • CMS Wire, Mention, 08/28/2019, Cultural Institutions Turn to Tech to Heighten Customer Experience, On-Site and Off Text
  • Mobile Marketing Magazine, Feature story, 08/05/2019, Artrendex aims to revolutionize art discovery with the launch of ArtPi Text
  • AiThority, Feature story, 08/02/2019, Artrendex’s ArtPI Uses Artificial Intelligence to Revolutionize Art Discovery Text
  • Analytics Insight, Feature story, 07/30/2019, Aretrendex's ArtPI Uses Artificial Intelligence To Revolutionize Art Discovery Text
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News

07/11/2019, Artrendex’s ArtPI Uses Artificial Intelligence to Revolutionize Art Discovery
07/11/201907/11/2019, Artrendex’s ArtPI Uses Artificial Intelligence to Revolutionize Art Discovery
Announcement
07/11/2019
Announcement
07/11/2019
ArtPI (artpi.co) is a new interface or API driven by artificial intelligence that’s poised to transform the way art gets discovered, displayed, and sold. It promises to transform art discovery the way Shazam transformed music discovery. MORE» More»

ArtPI (artpi.co) is a new interface or API driven by artificial intelligence that’s poised to transform the way art gets discovered, displayed, and sold. It promises to transform art discovery the way Shazam transformed music discovery.

ArtPI detects features and patterns using overarching visual style characteristics based in art theory and history. Built from the ground up specifically for art and drawing on centuries of artworks, ArtPI can find visually similar works, label styles and eras, recognize subject matter and artist, and find connections within a large collection.

For museums and other institutions, this means users can search their collection visually, exploring artworks in a more organic and intuitive way by looking for particular features. Curators can have the entire collection at their fingertips, finding unexpected ties and similarities that may inspire new ways to display or interpret works. For galleries, dealers, and auction houses, ArtPI can be used in conjunction with social media to uncover trends or predict market conditions.

“AI is often used to label images and objects in them, and ArtPI can also find works by subject matter,” explains Ahmed Elgammal, creator of ArtPI, Professor of Computer Science at Rutgers University, and founder of AI art startup Artrendex. “But you don’t always just want to find painting of dogs or putti. Sometimes you want a particular style of lighting or line. We’ve trained our algorithms to identify these elements and principles of art, based on foundational art historians’ approaches. By working with the visual elements instead of content labels or other metadata like artists or era, you can find art you didn’t know existed and see its connections with other works.”

ArtPI works even when images of an artwork are distorted, allowing for less-than-ideal source images or shots from a variety of angles. The AI model has been trained to correct for distortion, distilling a slanted or poorly lit image into information that can be compared to other works. This does away with the need for complicated photographic documentation, letting ArtPI work in a variety of less formal circumstances. Now, for example, you can see what work from a major exhibit won the hearts of Instagramers, even if they took a quick snapshot from the side.

AI can spot visual patterns, often better than humans. ArtPI employs neural networks to train its algorithms on images, using more than 250,000 artworks for its initial training phase. The more works encountered by the algorithm, the more nuanced the results. “Humans grasp context quickly, but AI is great at homing in on details and doing so for millions of examples in seconds or fraction of second,” says Elgammal. “Every search and every image added to ArtPI will contribute to its refinement, increasing its value over time.”

Philadelphia’s Barnes Foundation was one of the first institutions to adapt ArtPI. The Barnes first analyzed its extensive collection, which includes a great number of impressionist works. The first round of AI-powered analysis by different computer vision platforms generated some unexpected results: In one instance, the content of museum’s Renoirs were labeled as stuffed animals. However, once the museum’s works were inputted to ArtPI, some remarkable connections emerged.

“We thought this part of our process would be the hardest, yet it proved the easiest,” recalls Shelley Bernstein, the digital consultant on the Barnes project. “The visual similarities were so good, they were almost too good.” The problem: The Barnes collection had a wonderfully idiosyncratic way of displaying works together that originated with the collection’s founder. To recreate this approach online, the Barnes and ArtPI crafted a custom way to display results that better mirrors the real-life museum experience.

“Exploring art, be it for educational or valuation purposes, can be done in many ways, and AI is just another tool, another frame that helps us find new insights into the art we’re working with,” says Elgammal. “Being aware and optimized for the concepts of art, ArtPI is designed to be the infrastructure recognition engine for museums and the art market, in other words, the ‘Shazam for Art.’ I believe visual search and suggested connection can both democratize the discovery process for laypeople and renew the excitement curators, galleries, and auction houses feel as they consider the works in their domain.”

Announcement
07/11/2019

02/13/2018, Portrait of an Algorithm: AICAN and Ahmed Elgammal Present First Solo Gallery Show by AI-Human Artistic Team at HG Contemporary, New York
02/13/201802/13/2018, Portrait of an Algorithm: AICAN and Ahmed Elgammal Present First Solo Gallery Show by AI-Human Artistic Team at HG Contemporary, New York
Announcement
02/13/2018
Announcement
02/13/2018
For the first time in the New York City art scene, an entire gallery show of works will be displayed created solely by an artist-AI collaboration: AICAN and Elgammal, a computer scientist by training who directs the Art & AI Lab at Rutgers University. MORE» More»
For the first time in the New York City art scene, an entire gallery show of works will be displayed created solely by an artist-AI collaboration: AICAN and Elgammal, a computer scientist by training who directs the Art & AI Lab at Rutgers University. HG Contemporary in Chelsea is hosting “Faceless Portraits Transcending Time.” The show will be open to the public February 13- March 5, 2019. This marks the primary art market opening its door to this new genre of art. 
 
For the HG Contemporary show, Elgammal unpacks the concept of the portrait, creating images with AICAN in two distinct ways, one surreal, one abstracted from Renaissance portraits. AICAN generated possible portraits and Elgammal curated them, selecting the most compelling images. A face is shrouded in a flurry of color, blurred as it emerges or disappears into an unsteady background. There is a recognizable humanity and an eerie estrangement in the featureless, yet expressive figures. The tension feels fitting.
 
“For the abstract portraits, I selected images that were abstracted out of facial features yet grounded enough in familiar figures. I used titles such as portrait of a king and portrait of a queen to reflect generic conventions,” notes Elgammal. “For the surrealist collection, I selected images that intrigue the perception and invoke questions about the subject, knowing that the inspiration and aesthetics all are solely coming from portraits and photographs of people, as well as skulls, nothing else.” 
 
The process and the results provoke questions about the nature of the portrait--and by extension of the human individual. “Usually portraits capture something about the people depicted. Here the image has no reference to a specific person or a historical point. It’s totally faceless. The portrait becomes a very abstract concept that doesn't have a particular meaning or context.” Yet these portraits evoke emotion, a sense of movement and moment, that allows viewers to connect deeply. It’s a thought-provoking suggestion of the blurry edges at the intersection of machine process and human creativity.
 
Though the results are astounding, AI is not what you think, and its role in creating art is not to replace the artist. “All the data comes from people. The machine only sees the data of people,” Elgammal explains. “And in the end, interpretation is up to people.” 
 
AICAN + Ahmed Elgammal: “Faceless Portraits Transcending Time”
HG Contemporary 527 W. 23rd Street, New York
 
The series of carefully trained algorithms is a medium, and this medium was front and center at a recent show at SCOPE Miami Beach, when artists Tim Bengel and Devin Gharakhanian used AICAN to generate new works, pieces shown alongside AICAN’s autonomously created images, one of which was featured prominently in the Wall Street Journal’s coverage of the art fair.

AICAN has been trained on five centuries of European canonical art. Training eschewed emphasis on a single style, period, or aesthetic, allowing for a broad range of potential outcomes. Modeled from psychological theories of the brain’s response to aesthetics, AICAN generates images based on the more than 100,000 works it has learned, giving its new image a title. The generation process can be adjusted, and Elgammal and his team have figured out how to quantify uniqueness, a number used to push the AI to get farther away from expected results. 
 
“We give the machine a dilemma, a tension to explore between two opposing forces,” explains Elgammal. “On one hand, AICAN weighs what happened in art history, the movements and styles. On the other hand, we push it enough to come up with novel art. By these two forces, we make sure the machine doesn’t do anything that is totally out of the realm of art and incomprehensible. I believe that great artists find the sweet spot between being innovative and avoiding complete viewer rejection.” 
 
The exhibition is presented in collaboration with Jessica Davidson, founder of Davidson Art Advisory LLC.
 
“So why are so many of these images so alluring? What does it know about me that I don’t? Why do I like them? And why do I feel like this is just the beginning?”
- Michael Brodeur, Boston Globe
 
“The biggest artistic achievement of the year” 
- Rene Chun, Artsy


About Ahmed Elgammal

Ahmed Elgammal is the founder and director of the Art and Artificial Intelligence Laboratory, and a professor of computer science at Rutgers University.  He developed AICAN, an autonomous AI artist and collaborative creative partner. Dr. Elgammal’s research on knowledge discovery in art history and AI art generation, received wide international media attention, including reports on the Washington Post, New York Times, NBC News, CBS News, the Guardian, the Daily Telegraph, Science News, New Scientist, and many others. In 2017, an Artsy editorial acclaimed AICAN as “the biggest artistic achievement of the year”. In 2016, a TV segment about his research, produced for PBS, won an Emmy award. AICAN art has been shown in several technology and art venues in Los Angeles, Frankfurt, San Francisco, and New York City. 
Announcement
02/13/2018