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Understanding Agentic AI and Its Impact
Aug 13, 2024
AI Insights and Innovation Podcast: Agentic AI
Host: David Linthicum
Author, speaker, AI systems architect, and analyst
Overview
Discussion about Agentic AI and its evolution from traditional AI systems.
Focus on defining Agentic AI, its applications, target audience, enterprise leverage, and business benefits.
What is Agentic AI?
Agentic
: Operates autonomously and independently.
Similar to past AI systems using architectural patterns like intelligence at the edge and AI-enabled devices.
Built on traditional AI agents but with new properties and attributes.
Difference from Traditional AI
Traditional LLMs (e.g., ChatGPT) respond based on training data and are static.
Agentic AI is more dynamic, capable of tool-calling, gathering up-to-date information, and making adaptive decisions.
Attributes of Agentic AI
Built on smaller language models for targeted tasks.
Able to integrate with external tools, APIs, and databases.
Functions like a mini human, reasoning, refining thinking, and consulting with other agents.
Applications of Agentic AI
Autonomous Vehicles
: Self-driving cars, drones, and transport systems.
Healthcare
: Personalized medicine, robotic surgery, patient monitoring.
Industrial Automation
: Smart manufacturing, predictive maintenance, supply chain optimization.
Personal Assistants
: Siri, Google Assistant, etc.
Components of Agentic AI
Perception and Sensing
: Gathering environmental data via sensors and cameras.
Information Processing
: Algorithms for data analysis and decision-making.
Action Execution
: Mechanisms for executing actions (robotic actuators, software commands).
Learning and Adaptability
: Learning from feedback, adapting behavior based on experiences.
Challenges
Scalability
: Architectural considerations for scaling.
Data Integration
: Middleware for data source communication.
Computational Resources
: Needs for real-time decision-making with limited resources.
Robustness and Reliability
: Complexity and potential fragility.
Who is it for?
Product companies building smart devices like thermostats, cars, drones.
Enterprises needing tactical AI for supply chain and manufacturing.
Future of Agentic AI
Expected growth and excitement in the business world.
Seen as a more affordable and useful alternative to creating large LLMs.
Conclusion
Agentic AI offers a tactical use of AI through an adaptable architectural pattern.
Offers new capabilities for enterprises beyond traditional large LLMs.
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Full transcript