OpenAI,这家开发了知名的聊天机器人ChatGPT的公司,发出警告称,如果禁止使用受版权保护的新闻和书籍来训练人工智能,那么人工智能的发展将会受到严重阻碍。OpenAI强调,依赖这些受版权保护的作品来进行人工智能训练是至关重要的,如果没有这样的训练,他们将“不可能”创造出像ChatGPT这样的服务。

这一警告凸显了人工智能发展中的一个重要问题:如何平衡版权保护和个人隐私权。虽然版权保护是鼓励创作和创新的重要手段,但是过于严格的版权保护可能会阻碍技术的进步和创新。

对于OpenAI来说,他们认为使用受版权保护的作品来训练人工智能是合法的,因为他们在使用这些作品时,并不会侵犯作者的署名权和改编权。他们只是使用这些作品作为训练数据,来提高人工智能的性能和准确性。

这一问题引起了广泛的关注和讨论。一方面,人们担心如果过于严格的保护版权,将会阻碍人工智能的发展,因为人工智能需要大量的数据来进行训练,而这些数据往往来源于受版权保护的作品。另一方面,人们也担心如果对版权保护过于宽松,将会侵犯作者的权益,影响创作和创新。

AI development hindered if copyrighted works ban enforced, OpenAI warns
Keywords: OpenAI, copyright, AI development

News content:
OpenAI, the company behind the renowned chatbot ChatGPT, has issued a warning that the development of artificial intelligence (AI) will be severely hindered if the use of copyrighted works for AI training is banned. OpenAI emphasizes that training AI with these copyrighted works is crucial, and without such training, it would be “impossible” to create services like ChatGPT.

This warning highlights an important issue in the development of AI: balancing copyright protection and personal privacy rights. While copyright protection is an essential means to encourage creation and innovation, overly strict copyright protection may hinder technological progress and innovation.

For OpenAI, they believe that using copyrighted works to train AI is legal, as they do not infringe on the author’s rights to attribution and adaptation when using these works. They simply use these works as training data to improve the performance and accuracy of AI.

This issue has sparked widespread concern and discussion. On the one hand, people are worried that if copyright protection is too strict, it will hinder the development of AI, as AI requires a large amount of data for training, much of which comes from copyrighted works. On the other hand, people are also concerned that if copyright protection is too loose, it will infringe on the rights of creators and affect creativity and innovation.

【来源】https://www.zhitongcaijing.com/content/detail/1051320.html

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