#Infographics: The market size in the #GenerativeAI market is projected to reach US$62.72bn in 2025.

The market size is expected to show an annual growth rate (CAGR 2025-2030) of 41.53%, resulting in a market volume of US$356.10bn by 2030.

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https://www.statista.com/outlook/tmo/artificial-intelligence/generative-ai/worldwide

Among the #GenAI innovations #Gartner expects will reach mainstream adoption within 10 years, two technologies have been identified as offering the highest potential - domain-specific GenAI models and autonomous agents.

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https://www.gartner.com/en/newsroom/press-releases/2024-09-09-gartner-predicts-40-percent-of-generative-ai-solutions-will-be-multimodal-by-2027

Unlike general-purpose GenAI models (like GPT-4), domain specific GenAI models are trained on data from a specific field or industry. This makes them experts in that area.

Examples include: #BloombergGPT (Trained on financial data for tasks like market analysis), or models like #AlphaFold that are used in biology to understand and generate protein structures.

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https://knowledgezone.co.in/trends/browser?topic=AlphaFold

AlphaFold

AlphaFold is an artificial intelligence (AI) program developed by Google's DeepMind which performs predictions of protein structure. The program is designed as a deep learning system

Knowledge Zone

Autonomous generative AI (GenAI) agents are complex AI systems that can perform tasks independently. They can learn, adapt, and make decisions to achieve specific goals.

For example, LLM-powered agents can use an LLM to reason through a problem, create a plan to solve the problem, and execute the plan with the help of a set of tools.

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https://knowledgezone.co.in/posts/Language-Model-Agent-659a395fc667ae7cbf67268c

Language Model Agent

LLM agents are software tools that enable LLMs to interact with the world to accomplish some tasks.

Knowledge Zone