MIT graduate student reduced painting restoration from 230 to 3.5 hours
MIT graduate student Alex Kachkin developed a cool method for painting restoration using artificial intelligence. Reducing work time from many months to several hours. As a demonstration, he restored a work by an unknown Dutch master of the 15th century that had seriously suffered from time.
The restoration process included several technological stages. First, algorithms created a digital copy, filling small cracks based on analysis of neighboring colors and restoring ornaments. To preserve historical authenticity, the researcher refused generative neural networks. Instead, he supplemented lost elements like faces with fragments from other works by the artist, using traditional graphic editors. The final step is truly genius. The restored digital elements were printed on ultra-thin transparent polymer and overlaid on the original. This film is invisible to the human eye but can be easily removed without the slightest harm to the painting. The entire application process took only 3.5 hours, while traditional restoration would require more than 230 hours of painstaking work. This technology will open access to many paintings around the world. Because it turns out that 70% of all museum paintings are not displayed. Due to damage.
Autor: AIvengo
For 5 years I have been working with machine learning and artificial intelligence. And this field never ceases to amaze, inspire and interest me.
Dongfeng deploys 1.7m tall Walker S robots with 41 servosDongfeng Motor joins forces with Ubtech Robotics to integrate innovative Walker S robots into production lines. These technological marvels standing 1 meter and 70 centimeters tall are ready to transform traditional automobile assembly processes. Dongfeng Motor's general manager emphasizes that implementing artificial intelligence in these robots will significantly improve the quality of component inspection and assembly.
MIT graduate student reduced painting restoration from 230 to 3.5 hoursMIT graduate student Alex Kachkin developed a cool method for painting restoration using artificial intelligence. Reducing work time from many months to several hours. As a demonstration, he restored a work by an unknown Dutch master of the 15th century that had seriously suffered from time.
AI prosthetic from Canada analyzes objects and decides how to grasp themArtificial intelligence gives prosthetics independence! Scientists from Memorial University of Newfoundland created a revolutionary arm prosthetic that literally "thinks" for itself. Unlike traditional models that require reading muscle signals through sensors, the new device is completely autonomous.
DeepSeek packed LLM engine into 1200 lines of Python codeThe DeepSeek team presented nano-vLLM. This is a lightweight and compact engine for running large language models. Which could change perceptions about code efficiency. Amazingly, all functionality fit into just 1200 lines of Python code! This is true technological minimalism in the world of artificial intelligence. Traditional engines like this, for all their power, often suffer from an overloaded codebase. Which makes their modification a real trial for developers. Nano-vLLM solves this problem by offering a simple but powerful tool without unnecessary complexity. The code is open.
Tesla robotaxi failure: 11 traffic violations in first days from 20 carsThe dream of robotaxis faces harsh reality! Tesla launched public tests of autonomous taxis in Austin, but the results were far from the promised technological miracle. In the first days of testing, at least 11 serious traffic violations were recorded. And this with only 20 vehicles selected for a limited circle of bloggers. Philip Koopman, professor at Carnegie Mellon University and expert on autonomous technologies, doesn't hide his surprise: "This is terribly fast for so many videos with unstable driving to appear".
