Generative AI is very exciting technology. It's like having a robot apprentice who can learn how to make art, music, and more! However, it still takes a lot of data, computing power, and learning for AI to match the creative abilities of people. But generative AI is getting better every day as it studies more examples of human creativity. The most amazing thing is that AI is not just copying work made by humans. It is able to take what it has learned and come up with new patterns, combinations, and innovations. Generative AI will help make art and content that has never been seen before!
Open-source generative AI
The code used to create open-source generative AI is available for everyone to look at, change, and use to build new things. It is not kept a secret by one company. Open source is about sharing and working together. Some examples of open-source generative AI projects are:
■ RunwayML: This helps people create new drawings, sounds, and videos with AI. You can change the code to customise the AI art!
■ StyleGAN: This AI makes realistic fake human faces. The code is public so new things can be generated.
■ Magenta: A tool from Google to make music with AI. You can build on it to train the AI in new ways.
■ TensorFlow: This popular programming library lets anyone build all kinds of AI models. Generative Als are created with it.
Some other cool open-source projects are GAN Lab, Mimetic, Lexica, and VQGAN. The code for all these is free to use and change! The benefit of open source is that anyone can learn from these projects, make them better, and create new innovations. You may be asking yourself, "Why should I choose open-source generative AI over closed-source?" The key advantage of open-source generative AI is the collaborative and transparent nature of its development.
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