What is generative AI and how does it work?
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Generative AI creates new content based on data, unlike traditional AI, which only analyzes. It accelerates content creation, reduces costs, but requires verification of the generated information.
Generative artificial intelligence has already managed to become part of the daily work of businesses and ordinary users. It creates texts, images, music, videos, and even program code, helps automate processes, and saves time. UNN will tell you more about what generative AI is and how this tool can be effectively used.
What is generative AI
Generative AI is a type of artificial intelligence that does not just analyze data but creates new content based on large arrays of information. If traditional AI systems work according to clearly defined rules and help make decisions, generative models form original texts, illustrations, audio files, or videos in response to a user's request. It is this ability to create new things that has made the technology groundbreaking for creative industries and digital services.
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Most modern solutions are based on large language models and deep learning neural networks. First, the model goes through a training phase on large sets of structured and unstructured data, where it learns patterns between words, images, or sounds, and then it is configured for specific tasks, either through fine-tuning or through reinforcement learning based on human evaluations. After that, the system can generate responses based on text prompts. To increase accuracy, generation augmentation mechanisms are used, which allow using relevant data.
What is the difference between traditional and generative AI
The main difference between generative AI and traditional AI lies in the approach to tasks. Classical AI is effective in forecasting, fraud detection, analytics, and process automation. Generative AI works with open formulations, can adapt to uncertain requests, and demonstrates creativity.
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GenAI's functionalities cover several key areas. In the text sphere, this includes writing articles, product descriptions, scripts, translations, and chatbot responses. In the visual direction, it involves creating images from text descriptions, stylizing graphics, and generating videos. The technology can also generate natural language for voice assistants and create original musical compositions. A separate area is programming, where models help write and optimize code, accelerating development.
Are the tools available for free?
Today, the market is represented by dozens of solutions, among which the most famous are GPT from OpenAI, Claude from Anthropic, and Gemini from Google. Also available are Meta's LLaMA models and other open-architecture solutions. In the field of images, Midjourney and DALL·E are popular, for video work - Runway, and for programmers - GitHub Copilot X. Most of these platforms offer free versions or trial tariffs with limitations on the number of requests or functionality, which allows users to evaluate the service's capabilities without additional costs.
Benefits of using generative AI
The advantages of generative AI are obvious: it accelerates content creation, reduces costs, works around the clock, and allows scaling processes without a significant increase in resources. At the same time, there are risks associated with the possible generation of inaccurate information, data bias, and the difficulty of controlling results. That is why the implementation of GenAI necessarily requires a balanced approach and verification of the generated content.
Despite the challenges, generative artificial intelligence has already changed the approach to working with information and has become a tool that combines analytics and creativity, allows quickly testing ideas and adapting to the requirements of the digital economy.