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TieSet

tie set

Federated Learning Platform for the Edge Computing Era

Do you have a problem like this?

  • high cost
    High costs due to increased computing resources and network resources for handling huge amounts of data generated from IoT devices
  • delay
    Difficulty in realizing real-time processing due to data processing delay
  • privacy
    Privacy protection concerns due to information collection from customers and users
Do you have a problem like this?

"TieSet's STADLE™", a federated learning platform that assumes learning processing in a distributed environment, solves these problems

  • STADLE™ collects only the parameters of the edge AI's local AI model, generates a global model that integrates them on the cloud AI side, and returns them to the edge AI side, making it possible to promote edge AI learning.
  • Since raw data is not shared, conventional problems of pressure on computing and network resources and processing delays are resolved.
  • Mitigate the risk of identity theft from data sharing and provide a high level of privacy protection
Overview of STADLE™ (associative learning framework)
Do you have a problem like this?

[Point 1] Multiple functions to accelerate AI learning

Features of TieSet STADLE™


Features of TieSet STADLE™

[Point2] Overwhelming intelligence

Compared to AI estimation with edge alone, it can reach the optimal solution faster.


[Point2] Overwhelming intelligence

[Point 3] Application areas where the use of TieSet's STADLE™ is expected

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


Features of TieSet STADLE™

Core features of STADLE™

Core features of STADLE™

Distributed horizontal scaling with Kubernetes

Common federated learning platforms cannot scale horizontally and end up constructing a single global model (aggregation of cluster models) for all devices. However, the global model may not be suitable for some attributes. TieSet's STADLE™ allows you to flexibly form multiple semi-global models to improve model performance.

AI機能を地域属性で最適化
AI機能をユーザ属性で最適化

company description

company name TieSet Inc.
Established 2020
location Santa Clara, California, United States
representative Kiyoshi Nakayama
website https://tieset.com/

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In charge of Macnica TieSet Co., Ltd.

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