[RECORDED] Agent Based LLM Applications: Separating the Hype from Practical Applications

There is significant excitement about Large Language Models, but the hype continues to outpace the reality. The latest entry into the AI lexicon that is getting increasing attention is that of agent-based approaches where autonomous agents operate and make decisions without human intervention. While this framework has promise in the future, and some thought leaders project billions of agents operating for organizations and individuals, there are some challenges that current approaches need to overcome before widespread adoption of more ambitious visions of highly functional, safe, reliable “agents for all” can be realized.

Topics Covered:

What kinds of processes can LLMs automate?

What is the difference between Chatbots, Assistants and Agents?

Templated Prompts: Incorporating additional context.

What is an agent-based approach?

How does this differ from typical LLM powered applications?

How can agent based, and non-agent-based approaches be used for data remediation?

AI governance, and the role of ethical guidelines

Speakers

    • Seth Earley
      CEO and Founder, Earley Information Science
    • Sanjay Mehta
      Principal Solution Architect, Earley Information Science
    • Alexander Kline
      Founding Partner, Arcana Concept
    • Dominique Legault 
      Founder, ReliableGenius





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Earley Information Science Team

We're passionate about managing data, content, and organizational knowledge. For 25 years, we've supported business outcomes by making information findable, usable, and valuable.