2 mins to read This is an introductory level microlearning course aimed at explaining what Generative AI is, how it is used, and how it differs from traditional machine learning methods. It also covers Google Tools to help you develop your own Gen AI apps.This course is estimated to take approximately 45 minutes to complete.
Generative AI, short for Generative Artificial Intelligence, refers to a category of artificial intelligence systems that have the capability to generate new content or data that is similar to what a human might produce. These systems use various techniques, such as neural networks and deep learning, to generate text, images, audio, or other types of content.
One of the most well-known applications of generative AI is in natural language processing (NLP), where models like GPT (Generative Pre-trained Transformer) are used to generate human-like text. These models are trained on massive datasets and can generate coherent and contextually relevant text in a wide range of languages and topics. They have applications in chatbots, content generation, language translation, and more.
In addition to NLP, generative AI has been used in computer vision to generate images and videos. Models like Generative Adversarial Networks (GANs) are particularly popular for this purpose. GANs consist of two neural networks, a generator and a discriminator, that work together to create realistic images. They are widely used in tasks such as image synthesis, style transfer, and image-to-image translation.
Generative AI also has applications in other domains, including music generation, art creation, and even drug discovery. These systems have the potential to be both creative and productive tools, as they can automate the generation of content that would otherwise require human effort and creativity.
However, the use of generative AI also raises ethical concerns, such as the potential for generating fake content, deepfakes, and the misuse of technology for malicious purposes. As a result, the development and deployment of generative AI systems are subject to ongoing discussions about responsible use and ethical guidelines.