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Generative vs. agentic AI: The next wave of the AI revolution
- Generative AI has been dominant in the news recently, revolutionizing various fields of work and spawning a new industry.
- Agentic AI represents the next phase of the AI revolution, set to disrupt multiple aspects of our lives with enhanced capabilities.
- While generative AI creates new data by learning from existing data, agentic AI focuses on action and autonomy, capable of independent task execution.
- Agentic AI interprets context, autonomously selects and executes goals, and continuously learns and improves its processes.
- Agentic AI works based on a core model, policy layer, memory layer, execution layer, and learning layer, enhancing its functionality and efficiency.
- Agentic AI applications span diverse areas such as AI development, inventory management, personal assistants, and customer support.
- Agentic AI can replace humans in certain tasks that are well-specified, predictable, and executable in a digital environment, but it lacks human traits like creativity and empathy.
- Leveraging agentic AI can involve automating routine tasks and integrating it into products to address predictable and digitizable customer problems.
- While agentic AI offers immense potential, understanding its limitations and combining it with human skills where necessary remains crucial for optimal utilization.
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