What are the concerns surrounding Generative AI?
There are some major concerns regarding Generative AI that hold a greater potential for different industries.
- Ethical implications: We get ethical concerns regarding generative AI as the content created by generative AI is the same as human-created content. There is a high risk of creating or misusing the images, and videos and creating fake news with the help of generative AI.
- Security and Privacy: One can create fake-looking identities or create realistic fake identities that can harm a person’s security or privacy accordingly. Training generative AI with personal data can harm the protection of any sensitive information.
- Unemployment: There may be chances of unemployment in future as the development of Ai becomes more advanced. There is a possibility of a job replacement in various fields such as design, music, writing, design and so on.
- Rights of Ownership: With the development of AI there may be chances of creating original content, that determines ownership, copyright and complexity. It has become more challenging to differentiate between content created by humans and AI.
What is Generative AI?
Nowadays as we all know the power of Artificial Intelligence is developing day by day, and after the introduction of Generative AI is taking creativity to the next level Generative AI is a subset of Deep learning that is again a part of Artificial Intelligence.
In this article, we will explore,
What is Generative AI? Examples, Definition, Models and limitations.
Generative AI helps to create new artificial content or data that includes Images, Videos, Music, or even 3D models without any effort required by humans. The advancements in LLM have led to the development of Generative AI.
Generative AI models are trained and learn the datasets and design within the data based on large datasets and Patterns. They can generate new examples that are similar to the training data. These models are capable of generating new content without any human instructions.
In simple words, It generally involves training AI models to understand different patterns and structures within existing data and using that to generate new original data.