AIとデータを取り巻く様々な課題の解決

従来の分析で外部データを活用するのと異なり、AI、機械学習の場合は、

外部データが形を変え学習結果として永続する事でその持つ価値が大きく異なります。

当協議会はアノテーション含めAIを取り巻く様々な課題に取り組んでいきます。

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Data Platform WG

Building a service base for the distribution and sharing of data is one of the key activities of the consortium. The data delivery infrastructure includes catalog services for searching for the data you need, datastore brokerage services for different types of data (structured data, unstructured data, streaming, etc.), This includes building and providing machine learning and deep learning. Provides services that facilitate data analysis and smart contract mechanisms for data delivery.

In addition, solutions using deep learning (AI) and ML (machine learning) are also responsible for the products. A number of requirements are required for the foundation, including data transparency, historical management, cleansing, worker review, and work recording. To meet these requirements, you must not only build a strong security, identity management, and other authentication infrastructure, but also build a system of validation and assurance for data providers and editors who work with certification authorities. The Data Infrastructure WG considers the underlying architecture to meet these various requirements and works with its members to implement them. In addition, we will establish a foundation for open source only for members, enabling the realization of a data distribution and utilization base within the organization.

Necessity of data platform which is capable to handle various risks

The importance of building a data platform that addresses various issues and risks surrounding data, such as intellectual property and data provenance, is increasing. The AI Data Consortium builds the foundation for realizing appropriate data control and licenses subsystems that can be deployed within the organization to members free of charge.

Data transaction model this consortium supports

Provide flexible transaction mode which satisfy the needs of data holders

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