Generative AI is a kind of artificial intelligence that creates new content, including text, images, audio, and video, based on patterns it has learned from existing content. Today’s generative AI models have been trained on enormous volumes of data using deep learning, or deep neural networks, and they can carry on conversations, answer questions, write stories, produce source code, and create images and videos of any description, all based on brief text inputs or “prompts.”
Generative AI is called generative because the AI creates something that didn’t previously exist. That’s what makes it different from discriminative AI, which draws distinctions between different kinds of input. To say it differently, discriminative AI tries to answer a question like “Is this image a drawing of a rabbit or a lion?” whereas generative AI responds to prompts like “Draw me a picture of a lion and a rabbit sitting next to each other.”
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This article introduces you to generative AI and its uses with popular models like ChatGPT and DALL-E. We’ll also consider the limitations of the technology, including why “too many fingers” has become a dead giveaway for artificially generated art.
The emergence of generative AI
Generative AI has been around for years, arguably since ELIZA, a chatbot that simulates talking to a therapist, was developed at MIT in 1966. But years of work on AI and machine learning have recently come to fruition with the release of new generative AI systems. You’ve almost certainly heard about ChatGPT, a text-based AI chatbot that produces remarkably human-like prose. DALL-E and Stable Diffusion have also drawn attention for their ability to create vibrant and realistic images based on text prompts.
Output from these systems is so uncanny that it has many people asking philosophical questions about the nature of consciousness—and worrying about the economic impact of generative AI on human jobs. But while all of these artificial intelligence creations are undeniably big news, there is arguably less going on beneath the surface than some may assume. We’ll get to some of those big-picture questions in a moment. First, let’s look at what’s going on under the hood.
How does generative AI work?
Generative AI uses machine learning to process a huge amount of visual or textual data, much of which is scraped from the internet, and then determines what things are most likely to appear near other things. Much of the programming work of generative AI goes into creating algorithms that can distinguish the “things” of interest to the AI’s creators—words and sentences in the case of chatbots like ChatGPT, or visual elements for DALL-E. But fundamentally, generative AI creates its output by assessing an enormous corpus of data, then responding to prompts with something that falls within the realm of probability as…
2023-08-07 04:24:03
Article from www.infoworld.com