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Japanese deep learning startup LeapMind secures $10M series B led by Intel Capital

Masaru Ikeda Masaru Ikeda
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See the original story in Japanese. According to the press release published by Intel Capital on Friday, Tokyo-based LeapMind, the Japanese startup developing and offering deep learning solutions for enterprises, has secured about 1.15 billion yen (about $10 million US) in a series B round. This round was led by Intel Capital with participation from GMO Venture Partners, NTT Data (TSE:9613), Innovative Venture (run by NEC Capital Solution and SMBC Venture Capital), Itochu Technology Ventures, Visionnaire Ventures (whose chairman is Taizo Son) and Archetype Ventures. For LeapMind, this follows their series A round raised $3.4 million back in August of last year. For Itochu Technology Ventures and Visionnaire Ventures, as well as Archetype Ventures, this is the second investment in LeapMind following their participation in the series A round.   Since its launch back in December of 2012 under the previous name of AddQuality, LeapMind has been developing deep learning solutions for embedded systems called Juiz, which is practically essential for edge computing. The company recently released Blackstar SDK (software developer kit), a deep learning development environment for edge computing back in August. Prior to the rebranding, the company was qualified as participants in the KDDI Mugen Labo accelerator’s 7th…

CEO Soichi Matsuda (left) stands in front of their booth at Intel FPGA Technology Day earlier this month.
Image credit: LeapMind

See the original story in Japanese.

According to the press release published by Intel Capital on Friday, Tokyo-based LeapMind, the Japanese startup developing and offering deep learning solutions for enterprises, has secured about 1.15 billion yen (about $10 million US) in a series B round. This round was led by Intel Capital with participation from GMO Venture Partners, NTT Data (TSE:9613), Innovative Venture (run by NEC Capital Solution and SMBC Venture Capital), Itochu Technology Ventures, Visionnaire Ventures (whose chairman is Taizo Son) and Archetype Ventures.

For LeapMind, this follows their series A round raised $3.4 million back in August of last year. For Itochu Technology Ventures and Visionnaire Ventures, as well as Archetype Ventures, this is the second investment in LeapMind following their participation in the series A round.

LeapMind’s proprietary software- and hardware-based solutions (click to enlarge)
Image credit: LeapMind

 

Since its launch back in December of 2012 under the previous name of AddQuality, LeapMind has been developing deep learning solutions for embedded systems called Juiz, which is practically essential for edge computing. The company recently released Blackstar SDK (software developer kit), a deep learning development environment for edge computing back in August.

Prior to the rebranding, the company was qualified as participants in the KDDI Mugen Labo accelerator’s 7th batch with Ingram, a mobile app that allows users to find a similar product based on a photo taken with their mobile camera. After the rebranding, they were selected as a partner for the Nvidia Inception Program in addition to EY Innovative Startup 2017 (AI startup category) back in February.

LeapMind says it will use the funds to enhance research and development of software- and hardware-based solutions, then hire more talents from around the world while strengthening business development and sales forces in Japan and the rest of the world.

Edited by “Tex” Pomeroy

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

Junya Mori Junya Mori
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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. 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…

leapmind_featuredimage
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.

leapmind-blackstar
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.

leapmind-juiz-system
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

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