Choosing Between Tableau and Power BI Business Intelligence Tools
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Agentic AI is a new AI system that can act independently to make decisions to achieve an end-goal. While generative AI has been on the tip of everyone’s tongue for its ability to create both entertaining and informative content, agentic AI takes a significant leap forward, focusing on goal-oriented, autonomous systems that can interact with and influence their environment.
Generative AI, as the name suggests, focuses on creating new content. This can include anything from text and images to music and code. Think of it as a highly advanced form of artificial creativity. Some popular examples of Generative AI models include GPT-3 for text generation and DALL-E 2 for image generation. These models learn patterns from massive datasets and then use this knowledge to generate entirely new outputs that often mimic human creativity.
Agentic AI takes AI a step further. It's decisions and systems that can independently set goals, make decisions, and take actions to achieve those goals. These systems are designed to operate in complex and dynamic environments, often with minimal human intervention.
Here's a breakdown of key characteristics of Agentic AI:
By understanding the distinctions between Generative AI and Agentic AI, you can gain a deeper appreciation for the diverse capabilities of artificial intelligence and its potential impact across various industries.
The development and deployment of agentic AI are still in their early stages, but the development process can include several steps, including:
Some of the examples we have seen of agentic AI deployment include:
One of the key aspects of agentic AI is its ability to interact with humans through natural language. The conversational patterns of agentic AI systems differ significantly from human-to-human communication:
- Round Robin: Agents and humans take turns contributing.- Manual: Participants choose when to contribute.- Random: Contributions are selected randomly.- Auto: The system determines the order of contributions.
The future of agentic AI holds immense potential and presents significant challenges:
Agentic AI represents a new frontier in artificial intelligence, moving beyond passive generation to create systems that can act, interact, and influence the world around them. While the development and deployment of agentic AI present significant challenges, the right training can serve as a path to significant potential benefits. By carefully navigating the ethical and societal implications, we can utilize agentic AI to solve challenges and createa more sustainable and equitable future.
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