Artwork research has long relied on human sensibility and subjective judgment, but recent developments in machine learning have enabled the quantitative assessment of features that humans could not discover. In Western paintings, comprehensive analyses have been conducted from various perspectives in conjunction with large databases, but such extensive analysis has not been sufficiently conducted for Eastern paintings. Then, we focus on Ukiyo-e, a traditional Japanese art form, as a case study of Eastern paintings, and conduct a quantitative analysis of creativity in works of art using 11,000 high-resolution images. This involves using the concept of calculating creativity from networks to analyze both the creativity of the artwork and that of the artists. As a result, In terms of Ukiyo-e as a whole, it was found that the creativity of its appearance has declined with the maturation of culture, but in terms of style, it has become more segmented with the maturation of culture and has maintained a high level of creativity. This not only provides new insights into the study of Ukiyo-e but also shows how Ukiyo-e has evolved within the ongoing cultural history, playing a culturally significant role in the analysis of Eastern art.

Robots in Japan are found on factory floors carrying out simple tasks or delivering food to restaurant patrons but researchers have now unveiled a robot capable of executing the delicate task of peeling a banana without squashing the fruit inside. While the dual-armed machine is only successful 57% of the time, banana peeling points to a future where machines undertake more subtle operations than moving metal parts or delivering coffee. Video from researchers at the University of Tokyo showed the robot pick up and peel a banana with both hands in about three minutes. Researchers Heecheol Kim, Yoshiyuki Ohmura and Yasuo Kuniyoshi trained the robot using a "deep imitation learning" process where they demonstrated the banana-peeling action hundreds of times to produce sufficient data for the robot to learn the actions and replicate it. In this case, the banana reached its success rate after more than 13 hours of training.

Yasuo Kuniyoshi is a man with an extraordinary plan. Kuniyoshi, a professor at the University of Tokyo's Graduate School of Information Science and Technology, has been attempting to produce an utterly convincing artificial being for the past 30 years. "A robot," he says, "that has developed the real ability to understand correctly what people are saying, and is able to converse and interact with them naturally, just as humans do with each other, based on its own experiences and bodily sensations." I've been thinking about Kuniyoshi's work since seeing the recent Hollywood remake of "Ghost in the Shell." The original anime from 1995 was hugely influential and, together with "Akira" and "Spirited Away," is one of the most well-known Japanese animes in the West.

"I was determined to do it precisely because I was told it was impossible." So says Yasuo Kuniyoshi, professor at the University of Tokyo's Graduate School of Information Science and Technology, in a quiet tone. However, the sharp glint in his eye betrays his grand ambition of developing a truly clever artificial intelligence to benefit humankind. Some current forms of artificial intelligence (AI), such as speech recognition and automated driving, are just as competent as humans--if not better--at carrying out their given tasks.However, just as AI developed for speech recognition cannot play chess, and chess-playing AI cannot drive a car, existing forms of AI are incapable of any actions beyond those intended by their creators. Because AI does not "think" the same way humans do, it cannot adapt to conditions besides the preconceived context it was programmed for in advance.For AI to be truly intelligent and highly adaptable, it must be able to think in the same way as humans.

Building upon his success in getting a humanoid robot to perform an action he was aiming for, Kuniyoshi has now turned his attention to how fetuses develop intelligence to explore the fundamental principles of intelligence of our species. For his studies, Kuniyoshi has modeled a virtual fetus consisting of approximately 400 muscles and a skeleton, gestating in an environment resembling a womb filled with amniotic fluid to run computer simulations. This fetus does not possess "innate behaviors," namely a pre-existing process that spawns specific movements. However, when vibrations sent through neural signals from the spinal cord to random muscles reached the body's other muscles through the skeleton or feedback of pressure from the amniotic fluid and uterine wall, the muscles and corresponding spinal circuits began coordinating their movements, leading to the emergence of actions resembling those of an actual fetus in the womb (movie 4). Recently, Kuniyoshi used a computer model of a fetus in the 32nd week of gestation with cerebral neural circuits, inside the womb of a woman, to observe how the cerebrum receives sensory information and the neural circuits learn about the body through touch and somatic sensation. Furthermore, he compared a fetus that was raised inside the womb with one raised outside it, and found that learning occurring inside the womb led to more enhanced development of neural circuits than that occurring outside it.

"I was determined to do it precisely because I was told it was impossible." So says Yasuo Kuniyoshi, professor at the University of Tokyo's Graduate School of Information Science and Technology, in a quiet tone. However, the sharp glint in his eye betrays his grand ambition of developing a truly clever artificial intelligence to benefit humankind. Existing AI (Top) Self-driving cars most likely will one day be able to take people to their destination by recognizing simple instructions like, "Take me to the University of Tokyo." Because existing AI does not think the same way humans do, it cannot adapt to situations that are not in its playbook. Some current forms of artificial intelligence (AI), such as speech recognition and automated driving, are just as competent as humans--if not better--at carrying out their given tasks (figure 1).