Macnica begins handling TieSet's "STADLE™", a federated learning platform for the edge computing era

Macnica (Headquarters: Yokohama City, Kanagawa Prefecture, President: Kazumasa Hara, hereinafter Macnica), a total Services & Solutions provider in semiconductors, networks, cybersecurity, and AI/IoT, is a leading federated learning company, TieSet. ) Inc. (Headquarters: California, USA, Co-founder & CEO: Kiyoshi Nakayama, hereinafter referred to as TieSet) We are pleased to announce today that we have entered into a sales partnership with TieSet. This will support efficient learning of edge AI (AI technology implemented on the device side) in the use of big data, which has been difficult to achieve until now, as well as privacy protection and compliance compliance.

■ AI issues in big data utilization
There are various problems in using AI using big data, especially in the IoT environment where many devices are connected in a distributed environment, such as the following.

・Depletion of computing resources and network resources for handling huge amounts of data generated from IoT devices
・Difficulty in realizing real-time processing due to data processing delay
・Concerns about privacy protection due to information collection from customers and users

Federated learning, a distributed AI technology that performs machine learning without aggregating data, is attracting attention as a way to deal with these problems. Even if big data is not collected from the edge side, it can be used in a distributed state, reducing the amount of data processing and communication, and ensuring privacy.

<AI challenges in utilizing big data and the background of the development of the federated learning platform “STADLE™”>

■ Allied learning platform TieSet “STADLE™”
STADLE™ is a federated learning platform that realizes the world's most advanced distributed AI technology.
STADLE™ can train edge AI models without sharing raw data on the edge AI side. Specifically, gather only the parameters of the local AI model on the edge AI side, generate a global model that integrates them on the cloud AI side, and return them to the edge AI side to promote edge AI learning. is possible. Since raw data is not shared, conventional problems of pressure on computing and network resources and processing delays can be eliminated.
Another feature of STADLE™ is that it reduces the risk of personal information leakage due to data sharing and provides a high degree of privacy protection.
Combining these features, STADLE™ provides companies with an efficient and secure AI model learning environment.

<Overview of the allied learning platform “STADLE™”>

STADLE™ protects personal information, can be used in a distributed environment, and is capable of real-time processing. It is expected to be used in the automotive field.

At Macnica, we offer Splunk (data analysis platform), Databricks (data lakehouse platform), TripleBlind (privacy protection using secure calculation), and brighter AI (next-generation anonymous processing technology) as solutions to promote data utilization. We have a complete lineup of products to create an environment that meets the needs and challenges of our customers. In addition to the above, by providing TieSet's STADLE™ federated learning solution, we will improve the learning efficiency of edge AI and strengthen privacy protection, further supporting companies' data utilization.

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https://www.macnica.co.jp/business/dx/manufacturers/tieset/

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In charge of Macnica TieSet
TEL: 045-476-2010
E-mail: tieset-sales@macnica.co.jp

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*The information published in the news release (including product price, specifications, etc.) is current as of the date of announcement. Please note that the information may be subject to change without prior notice.