近日,由前Stability AI音频副总裁Ed Newton-Rex创立的Fairly Trained计划,开始为使用受版权保护的训练数据的AI模型公司颁发认证。该计划的第一个认证称为“许可模型认证”(Licensed Model certification),旨在证明获得认证的公司已申请使用受保护数据来训练其模型。

据悉,目前已对9家从事图像、音乐和语音生成业务的生成式人工智能公司进行了认证。这意味着,获得认证的公司在训练AI模型时,已经获得了受版权保护的数据的使用许可。这一举措有助于规范AI模型行业,保护版权,同时也为用户提供更放心、更有保障的AI模型服务。

Fairly Trained计划的实施,标志着AI模型行业开始重视版权问题,并采取实际行动加以规范。这对于保护创作者的权益,推动AI模型行业的健康发展,具有重要意义。未来,随着更多公司参与到这一计划中来,有望推动整个行业的版权意识的提升,为AI模型的发展创造更好的环境。

Title: Fairly Trained Program Issues Copyright Certification for AI Models
Keywords: AI models, copyright certification, Licensed Model certification

News content:
Recently, the Fairly Trained program, founded by Ed Newton-Rex, former vice president of audio at Stability AI, has started to issue certifications for AI model companies that use training data protected by copyright. The first certification offered by this program is the “Licensed Model certification,” which aims to verify that certified companies have applied for the use of protected data to train their models.

It is understood that currently, nine generative AI companies involved in image, music, and speech generation have received this certification. This means that certified companies have obtained the necessary license to use copyrighted data for training AI models. This initiative helps to regulate the AI model industry, protect copyrights, and provide users with more reliable and secure AI model services.

The implementation of the Fairly Trained program signifies that the AI model industry is starting to take copyright issues seriously and taking concrete actions to address them. This is of great significance for protecting the rights of creators and promoting the healthy development of the AI model industry. In the future, with more companies participating in this program, it is expected to enhance the awareness of copyright issues within the industry and create a better environment for the development of AI models.

【来源】https://www.theverge.com/2024/1/17/24041518/generative-ai-copyright-violation-fair-training-label-certification

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