The Evolution of AI: From Agents to Agencies
In the AI landscape, a groundbreaking shift is occurring with the emergence of “Agencies,” a new paradigm in task execution that goes beyond traditional Agents. While Agents operate as single intelligences, Agencies orchestrate multiple specialized intelligences to tackle complex tasks more efficiently.
Key Highlights:
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Transition from Agents to Agencies:
- Agents: Single intelligence handling all aspects of a task.
- Agencies: Coordinated systems that leverage varied intelligences, optimizing subtasks.
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Three Core Components of Agencies:
- Task Context Management: Unifies task-related data for seamless updates.
- Intelligence Allocation System: Dynamically selects the best intelligence for each subtask.
- Orchestration Logic: Breaks tasks down while ensuring cohesive integration.
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Future Implications:
- Shifting from “What’s the best model?” to “What’s the best combination of intelligences?”
The capability to integrate diverse intelligences can lead to more cost-effective, high-quality outputs.
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