"Edge AI" creates the next DX.
AISing Edge AI Technology
AiiR
AI in Real-time
Processing on the edge side
Not required much processing power and internet connection
It can realize high quality learning and prediction in few microseconds, even with low-spec computer resources.
Up-to-date Live training
Sequential and real-time learning process
It's possible to learn "inexperienced dynamic environment change" instantly in "constant calculation time".
Explainable AI “XAI”
Explainable AI
Our original algorithm has more explainability as a characteristic, comparing with "Deep Learning Black Boxing".
Awards
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Minister of Internal Affairs and Communications Award, Sales Force Award, Canal Ventures Award -
Award for Academic Startups 2018
Minister of Economy, Trade and Industry Award -
Selected as a J-Startup Company -
MUFG RiseUpFesta2018 Robot / Advanced Technology Category Grand Prize -
Innovation Leaders Summit
TOP20 -
Forbes Rising Startup
TOP20 -
SEMICON Japan2018 Innovation Village Pitch Grand Prix -
MicrosoftInnovationAward2018
Outstanding Performance Award -
SPARK! TOHOKU NICT Award -
Startup World TOP10
Japan Microsoft Award -
Marine Tech Grand Prix
Mitsui Chemicals Award, Nihon Unisys Award -
Mirai 2017 Japan Research Institute Award
Publication media
What's "Edge AI"?
At present, there is a growing need for AI that can be used by incorporating it into the edge device side, instead of the conventional AI that is processed on the cloud side, such as Deep Learning. This is called "edge AI".
As a specific technical difference, when the conventional AI learns on the cloud server side and communicates with the edge side, there may be a communication delay, whereas the "edge AI" By performing predictions completely, high-speed data processing is possible without causing communication delay. As a result, in areas where real-time control on edge devices is required, such as industrial robots and self-driving cars, it is necessary to use "edge AI".
We are professionals in this area, "Edge AI", developing original AI algorithms that can be embedded in edge devices.
As a specific technical difference, when the conventional AI learns on the cloud server side and communicates with the edge side, there may be a communication delay, whereas the "edge AI" By performing predictions completely, high-speed data processing is possible without causing communication delay. As a result, in areas where real-time control on edge devices is required, such as industrial robots and self-driving cars, it is necessary to use "edge AI".
We are professionals in this area, "Edge AI", developing original AI algorithms that can be embedded in edge devices.
