AI has captured the attention of tech enthusiasts and industry experts for quite some time.
Firstly, generative AI is part of the AI field. While AI mainly focuses on automating or optimising human tasks, generative AI focuses on creating different objects. Typical AI tasks such as building conversational or decision-making agents, intelligent automation, image recognition and processing, as well as translation, can be enhanced with GenAI. It allows the generation of text and reports, images and designs, speech and music, and more.
As a result, the integration of generative AI into everyday tasks and workflows has become increasingly seamless and impactful. One might wonder which type of data generation is the most popular. However, the answer is not straightforward.
Multimodal models allow the generation of different types of data based on diverse input. So, even if we had usage statistics, it would be challenging to determine the most popular type of data being generated. However, based on current business needs, large language models are among the most popular. These models can process both text and numerical information and can be used for tasks like question-answering, text transformation (translation, spell-checking, enrichment), and generating reports. This functionality is a significant part of operational activities for enterprises across industries, unlike image or video generation, which is less common.
Large language models: from text generation to modern giants
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