Carl Feynman, the son of British philosophical physicist Richard Feynman, established material model as a field of study at MIT in 1986. He was both amazed and concerned by AI’s rapid development. He shared his thoughts on X after witnessing an AI produce a fabric graphics in just a few minutes, noting how swiftly human effort is outpacing individual efforts.
” I’m outdone by an AI in a few minutes. They also pay me, but for how much”? Feynman acknowledged in a post how swiftly AI models are mastering challenging simulations that once required lengthy periods of study and strong computers.
An X customer shared their knowledge with Sonnet 3.7, an AI design with reasoning abilities, which properly produced an elaborate cloth modeling in p5. js—a work that had stumped another leading AI types, including Grok 3 and o1 Pro.
The X consumer asked,” Can you create the most intricate linen model in p5js?”
Recognizing the value of this discovery, the person said:” Wow, Sonnet 3.7 w/ Thinking only solved a difficulty no other type could solve however”.
Feynman’s response to the model quickly gained popularity, with the person pointing out Feynman’s legacy:” The person who actually invented model material in computer graphics at MIT in 1986 saw the video where Claude creates a cloth animation and says:” I’m outdone by an AI in a few minutes. They still pay me, but for how long?'”
Who is Carl Feynman?
Carl Feynman, the son of renowned physicist Richard Feynman, made significant contributions to computer graphics by developing pioneering techniques for simulating cloth movement. His research helped to create realistic fabric simulations for movies, video games, and virtual reality. In 1986, his master’s thesis,” Modeling the Appearance of Cloth”, was a pioneering achievement in the field.
Feynman remarked on that time, adding that it took library research, cunning, and originality, and months of work, and days of work, and all of those things. Now I’m outdone by an AI in a few minutes”.
Feynman’s words highlight an underlying issue: the speed with which AI is progressing, which raises questions about the development of human expertise in fields that once relied on extensive technical expertise and years of experience.
