TUNA SCOPE

Short List
TitleTUNA SCOPE
BrandSOJITZ CORPORATION
Product / ServiceTUNA SCOPE
CategoryC07. Use of Technology
EntrantDENTSU INC. Tokyo, JAPAN
Idea Creation DENTSU INC. Tokyo, JAPAN
Production INFORMATION SERVICES INTERNATIONAL-DENTSU, LTD. Tokyo, JAPAN
Production 2 DENTSU LIVE INC. Tokyo, JAPAN
Production 3 DENTSU CREATIVE X INC. Tokyo, JAPAN
Production 4 KOOZYT, INC. Tokyo, JAPAN
Production 5 AT ARMZ Osaka, JAPAN
Additional Company SOJITZ CORPORATION Tokyo, JAPAN

Credits

Name Company Position
Kazuhiro Shimura Dentsu, Inc. Creative Director
Akimichi Hibi Dentsu, Inc. Business Producer
Taira Kimura ISID General Manager
Hiroshi Morita ISID Chief Producer
Keigo Ihara ISID Project Manager
Yoshinori Tanaka ISID Project Manager
Michitaka Iida ISID Project Manager
Yasushi Miyajima Koozyt Data Scientist
Hideyuki Ono Koozyt Engineer
Amina Mim Koozyt AI Engineer
Hasanur Rashid Koozyt AI Engineer
Tomoyuki Kato Dentsu Live Director
Tatsuya Murayama DENTSU LIVE INC. Chief Producer
Masaya Ishii Dentsu Live Producer
Chisako Hasegawa Dentsu Live Producer
Tatsuo Yamano At Armz Producer
Ryosuke Kametani At Armz Production Manager
Junichi Ishikawa At Armz Production Manager
Hitoshi Nakao Dentsu Creative X Inc. Web Director
Shogo Hina AOIRO Web Designer
Katsuhiro Uto WOO inc. Graphic Designer
Jiro Watanabe WOO inc. Graphic Designer
Nobuyuki Isobe Onkio Haus Editor
Shunkichi Akutsu Freelance CG Designer
Go Aoyama Freelance CG Designer

Why is this work relevant for PR?

We developed AI that replicates the skill of experts. When the three parties publicized this project, it caused a major sensation, with more than 150 media outlets worldwide reporting on it as an initiative aimed at permanently preserving precious human skills by transplanting them into AI systems. Previously, AI and other advanced technologies have often been portrayed in a confrontational light, described using phrases such as “they will take jobs away from humans.” However, this project was significant in that it presented new possibilities for humans and AI to coexist peacefully.

Background

Tuna―one of the ocean’s greatest treasures. The Tokyo market is a global center for marine products, where tuna examiners judge the quality of fish with their eyes. However, due to a shrinking fisheries industry and Tokyo’s rapidly aging population, the number of craftsmen has fallen to less than half of the industry’s golden age. In the near future, it’s feared that there will be no successors to carry on the occupation. Sojitz is a trading company that handles tuna from fishing grounds all over the world, and is committed to managing the quality of its own tuna by unifying standards by dispatching craftsmen around the world. To keep delivering a high standard of tuna in a future when tuna examiners may not be around, the company took the challenge of creating something that could carry on the legacy of this trade by developing a new system using AI.

Describe the creative idea (20% of vote)

We focused on cross sections of the tuna’s tail, which hold all the vital information about the tuna’s flavor, freshness and so forth. Craftsmen who worked at markets had long used this technique to examine tuna, but it is said it takes at least ten years to learn to develop the acumen to perform this feat by eye. Utilizing an environment that saw a number of tuna thousands of times greater than a single examiner might see, we photographed a massive number of tuna tail cross sections, and through deep learning, we taught AI to interpret this data, and master the craft’s unexplainable nuances in a single month—an impossibly short time for humans. This project resulted in the birth of a system which could analyze and master the hidden nuances of the examination process, which practitioners themselves admitted were nearly impossible to explain.

Describe the strategy (30% of vote)

Up until now, tuna examination has been the domain of a group of individual artisans, each with their own personal nuanced methods, and as such, has been difficult to reduce into a generalized technique. Since the number of tuna each examiner could practice on is limited, it also takes a great deal of time to train. We created a system by which we introduced an AI on a mobile platform into the large network operated by the client, Sojitz, and allowed it to learn simultaneously from a huge amount of visual data from fish markets all over the world. This enabled the creation of a unified standard of tuna examination by gathering many artisans’ experiences on a single application.

Describe the execution (20% of vote)

The AI system developed for TUNA SCOPE was turned into a smartphone app and introduced to the quality inspection process in fish factories. As a result, it was able to achieve 85% accuracy compared to real tuna examiners with 35 years of experience in dividing the fish into 4-5 grades. The tuna ranked highest by the AI during this test was branded as AI Tuna and served at a sushi restaraunt in Tokyo in order to test market viability. 3/5/2019 - TUNA SCOPE introduced to factory 3/27/2019 - AI TUNA is served in Tokyo and introduced as a brand 4/2019 - Brainstorming for use in other industries (agriculture, medicine, etc.) 4/2019 - Website launches

List the results (30% of vote) – must include at least two of the following tiers:

Over two years from its conception, the developed AI system, TUNA SCOPE was implemented as a smartphone application, and introduced to the quality judgment flow in fishery factories. It achieved about an 85% consensus rate with 35 year veteran practitioners of the craft in appraisal of a 4-5 grade quality assessment. Of the several hundred tuna examined, the tuna ranked as the highest level of reliability and quality by the AI were branded and sold as “AI Tuna” at sushi restaurants in Tokyo. We achieved about 90% customer satisfaction. Going forward, we plan on deploying the system to our network. By learning data from our fishing grounds simultaneously, we will establish a uniform standard for appraisal, and aim to create a world where people everywhere can eat delicious tuna. The algorithm developed for this project has potential for use across a wide range of industries.

Links

Website URL