Core Viewpoint - The article discusses a groundbreaking method developed by Alex Kachkine for restoring damaged paintings using AI algorithms, significantly reducing the time required for restoration from months or years to just a few hours [1][7]. Group 1: Restoration Method - Kachkine's method allows for the physical restoration of paintings rather than just digital repairs, breaking the traditional approach of merely patching up digital scans [2][5]. - The restoration process involves applying a thin plastic film as a "mask" on the original painting, which allows for repairs without damaging the original artwork [6][18]. - The AI algorithm identifies 5612 damaged areas requiring 57314 different colors, completing the restoration in 3.5 hours, which is approximately 66 times faster than traditional methods [7][20]. Group 2: Restoration Process - The restoration process includes cleaning the original painting, scanning and analyzing it to create a digital version, and then using proprietary software to identify repair areas and colors [9][24]. - A dual-layer "mask" is created, consisting of a colored layer and a white layer, which must be perfectly aligned for effective restoration [13][14]. - After applying the mask, a thin layer of traditional varnish is sprayed to secure the repairs, and the mask can later be removed to restore the painting to its original state [17][18]. Group 3: Background of Alex Kachkine - Alex Kachkine has a strong engineering background, coming from a family of engineers and pursuing degrees in mechanical engineering and economics [27][32]. - His early interest in art was sparked by a school visit to an art museum, leading him to explore efficient methods for restoring damaged artworks [38][41]. - Kachkine aims to make more damaged artworks accessible to the public through his innovative restoration techniques [44].