Recently, the application of machine learning techniques is promoted as an approach to AI in research and academia, however challenges such as the following exist:
-Prohibitive Initial Cost
-How to efficiently share knowledge across different fields / institutions
-How to optimize Social Implementation
JSOL's Peers.Lab addresses these challenges. Peers.Lab serves as an inexpensive yet high-speed machine learning solution run on Google Cloud Platform™. JSOL's Deep Learning know-how and intuitive sharing functions streamline knowledge sharing in collaborative research allowing greater value to reach society faster.
Solution Overview
To utilize machine learning it is important to verify the results of learning by repeating trial & error at an early stage and make use of it to your own research and work. In JSOL, we will provide high-speed processing environment for machine learning with a view to social implementation of research results.
Service Features
Use Cases
Applicable industries
- governments / extra-governmental organizations(research institutions, educational institutions)
Customers
| Industry: Research institution / Educational institution Research Institute A |
Project Development of on-site detection technology of hazardous materials using AI |
Background of Implementation / Aim In collaboration with A laboratory, Deep Learning was applied to gas type identification of gas detector, and it was possible to specify with higher precision than conventional method. |
|
Installed functionalities / Distinctive Features Gas type identification was carried out at machine learning platform "Peers.Lab".
|
|
|
*This initiative was published in the Nihon Keizai Shimbun (morning edition) on March 11, 2017 |
