This technique can be used to create things like images, music, and text that look like they were made by real people but were actually created by the neural network. This can be very useful for artists and designers who need inspiration or to create characters for games and movies.
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Generative Artificial Intelligence in content creation
GANs are an active area of ​​research in artificial intelligence and have the potential to transform the way we create and consume digital content. However, they also raise ethical and privacy concerns, especially when it comes to creating fake images that can be used for malicious purposes. As a result, it is important that researchers and developers carefully consider the potential impact of GANs and work to develop responsible and ethical technologies.
Sometimes Generative Artificial Intelligence can be used in a bad way to create fake things like fake news or misleading images. So it's important that the people who create these things are careful and use technology responsibly and ethically.
*The text of this article was partially generated by ChatGPT, an artificial intelligence-based language model developed by OpenAI. Text entries were created by Curto News and responses intentionally reproduced in full. The answers from ChatGPT are automatically generated and do not represent the opinions of OpenAI or people associated with the model. All responsibility for published content rests with Curto News.
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References:
- Goodfellow, I., Pouget-Abadie, J., Mirza, M., Xu, B., Warde-Farley, D., Ozair, S., … & Bengio, Y. (2014). Generative adversarial nets. In Advances in neural information processing systems (pp. 2672-2680).
- Castro, PS, & Gomes, HM (2018). Generative Adversarial Networks: An Overview. Journal of Theoretical and Applied Informatics, 25(1), 23-34.
- Liu, J., Wang, G., Tao, D., & Song, M. (2019). Generative adversarial networks: A survey and taxonomy. IEEE Transactions on Neural Networks and Learning Systems, 30(11), 3453-3484.
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