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real life applications of Generative AI It's quite likely that you've used generative AI in some way or form in your everyday work. Maybe you took its help to write an email. Maybe you asked it to summarize some text. Maybe you asked it to generate some code for you. Generative AI clearly has many applications. And in this video, we’ll discuss a few different use cases for generative AI. Image generation: The first is image generation. There is software and coding. There is video creation, audio generation, text generation, conversational agents, organizational collaboration, and enterprise search. We'll discuss how generative AI can be used in each of these different fields, starting with image generation. Generative AI can be used for text-to-image generation, where users can generate realistic images from textual descriptions. Users can input text prompts specifying subjects, styles, settings, locations, or objects, and AI tools can create images that match those descrip...

  general principles of generative AI In this article, we're going to discuss some general principles of generative AI, including trust, quality, diversity, continuous feedback, ownership, and correctability.  One of the first principles of generative AI is to be human-centric. This means that the AI model should be designed in a way that caters to the end user. Not only does this mean having an intuitive user interface and giving users an easy way to provide input into the model, it also means that you should avoid any kind of bias within the system. This means that the system should be accessible to as many people as possible and does not discriminate based on user group. This also means that the training data that you use needs to be trustworthy as well and not include any inherent biases because that will also lead to a discriminating model. Human Centric design: In order to accomplish this human-centric design, there needs to be some element of human judgement built into ...