Walking back from a business meeting, management consultant Emilia Higashi quickly developed blisters on her feet. She figured there had to be better way to make women's shoes – ones more comfortable and also sustainable, made from plants instead of animal or petroleum products. Soon, she was researching in Italy at the world's biggest footwear trade show. She fell in love with a design called Saccheto, or little sack, that has minimal seams and fits almost like a sock. Then, she looked worldwide for sustainable plant-based materials, including "leathers" made from wine residues, pineapple fibers, cactus and even algae.

A new challenge for knowledge graph reasoning started in 2018. Deep learning has promoted the application of artificial intelligence (AI) techniques to a wide variety of social problems. Accordingly, being able to explain the reason for an AI decision is b ecoming important to ensure the secure and safe use of AI techniques. Thus, we, the Special Interest Group on Semantic Web and Ontology of the Japanese Society for AI, organized a challenge calling for techniques that reason and/or estimate which character s are criminals while providing a reasonable explanation based on an open knowledge graph of a well - known Sherlock Holmes mystery story . This paper presents a summary report of the first challenge held in 2018, including the knowledge graph construction, t he techniques proposed for reasoning and/or estimation, the evaluation metrics, and the results. The first prize went to an approach that formalized the problem as a constraint satisfaction problem and solved it using a lightweight formal method; the secon d prize went to an approach that used SPARQL and rules; the best resource prize went to a submission that constructed word embedding of characters from all sentences of Sherlock Holmes novels; and the best idea prize went to a discussion multi - agents model . We conclude this paper with the plans and issues for the next challenge in 2019.

SAPPORO – The development of artificial intelligence software that can write haiku based just on images is underway, with researchers hoping the project will improve how technology understands human emotion. A team of researchers and software developers led by Hidenori Kawamura, a 44-year-old professor at Hokkaido University's graduate school, is aiming to create AI that can analyze a vast amount of poetry to generate a haiku written about a subject or scene. The AI has been learning masterpieces composed by renowned Japanese poets such as Kobayashi Issa (1763-1827) and Masaoka Shiki (1867-1902), and analyzing pictures picked by volunteers that correspond to the poems. According to the team, the AI checks whether it is following structural rules and is using appropriate seasonal references. Haiku are defined by the use of a set number of syllables and traditionally use words that describe the season in which the work is set.

The Liberal Democratic Party wants to legalize professional gaming tournaments, joining a groundswell that started last summer amid speculation that video games will become an Olympic medal sport by 2024. Arcane laws meant to stop illegal gambling have prevented paid video game tournaments in the country, stunting the domestic market even as esports has become a multibillion-dollar global industry. Over the past few months, negotiations between four esports groups and the consumer protection agency have yielded a workaround to exempt professional gamers from the rules. Takeo Kawamura, a lawmaker from Prime Minister Shinzo Abe's LDP, said the ruling party might be willing to go further, by amending laws to ensure people's rights to earn a living playing games. The goal, he said, is to remove impediments and make it possible to win Olympic medals someday.

In a decade or so, people may not have to tidy their house, clean up after the dog, or even nag their spouse to do chores. A friendly, human-like robot will take care of routine tasks, and it won't whine or fight back. If technologists' predictions bear out, this second coming of robots could be more pervasive than the first in the '60s, when industrial robots revolutionized manufacturing. Designed to mimic the look and gestures of humans, the new breed of personal robots eventually may have artificial skin and muscles, as well as eye and facial expressions, and they might speak more naturally. But for this rapidly evolving field to take off, scientists will have to improve the quality and reliability of electronics first, and companies will have to find the application that every household must have.

The problem of designing optimal trajectory for redundant manipulators has attracted many researchers for the last three decades. One of the main reasons is the use of kinematically redundant robots is expected to increase in the future due to their increased flexibility. Some of the extra capabilities include the ability to avoid internal singularities or exte rnal obstacles over their entire workspace (Parket et al.,1989). Also, the inverse kinematics problem is underdetermined and admits an infinite number of distinct feasible solutions, meaning that a given end-effector pos es can be realized by an infinite number of distinct manipulator configurations (McAvoy, et al, 2000). In order to overcome the shortcomings inherent in non-redundant robots, redundant robots have been utilized in industrial applications to increase fl exibility and dexterity around a restricted task space in pres ence of obstacle.