GENAI
Generative artificial intelligence (Generative AI, GenAI, or GAI) is a subfield of artificial intelligence that uses generative models to produce text, images, videos, or other forms of data. These models learn the underlying patterns and structures of their training data and use them to produce new data based on the input, which often comes in the form of natural language prompts.
Generative AI tools have become more common since the AI boom in the 2020s. This boom was made possible by improvements in transformer-based deep neural networks, particularly large language models (LLMs). Major tools include chatbots such as ChatGPT, Copilot, Gemini, Claude, Grok, and DeepSeek; text-to-image models such as Stable Diffusion, Midjourney, and DALL-E; and text-to-video models such as Veo and Sora. Technology companies developing generative AI include OpenAI, xAI, Anthropic, Meta AI, Microsoft, Google, DeepSeek, and Baidu.
Generative AI is used across many industries, including software development, healthcare, finance, entertainment, customer service, sales and marketing, art, writing, fashion, and product design. The production of Generative AI systems requires large scale data centers using specialized chips which require high levels of energy for processing and water for cooling.
Generative AI has raised many ethical questions and governance challenges as it can be used for cybercrime, or to deceive or manipulate people through fake news or deepfakes. Even if used ethically, it may lead to mass replacement of human jobs. The tools themselves have been criticized as violating intellectual property laws, since they are trained on copyrighted works. The material and energy intensity of the AI systems has raised concerns about the environmental impact of AI, especially in light of the challenges created by the energy transition.
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