Japan’s LeapMind snags $3.4M to encourage deep learning use for IoT and robotics

Image credit: LeapMind

See the original story in Japanese.

Tokyo-based LeapMind, providing business solutions with deep learning technologies for enterprise users, has secured a total of 340 million yen (about $3.4 million) from Itochu Technology Ventures, Visionnaire Ventures and Archetype Ventures.

LeapMind has conducted provisioning of systems solutions using deep learning technologies and joint R&D with major companies or universities until now.

The firm holds technologies enabling calculation / compression and optimization of network even under a frugal computing environment. Making deep learning environment compact enough to work in a coin-sized CPU setting the firm aims to apply it in the IoT (Internet of Things) and robotics fields.

Black Star
Image credit: LeapMind

LeapMind developed a low-energy micro-miniature external deep learning computer called Black Star. Just by downloading prepared recipes to devices via a platform — Juiz Platform — currently under development, users can utilize deep learning technologies very quickly.

The secured fund will be spent for R&D on another platform named Juiz System in order to encourage more enterprises to use deep learning technologies. CEO of LeapMind Soichi Matsuda explains what kind of products will become available when enterprises utilizes deep learning technologies:

For example, an intelligent refrigerator can be expected; it recognizes interior contents and proposes cooking recipes for using leftover foodstuff.

Juiz System
Image credit: LeapMind

With Fujitsu (TSE:6702), LeapMind has cooperatively made a 20,000 dining photo data to marketing data by automatic analysis, so that various services becomes possible even at this stage as far as I see from case examples on the website.

The firm plans to launch the platform within this year.

Translated by Taijiro Takeda
Edited by “Tex” Pomeroy