Agentic AI is the latest foray into big-bet promises for businesses and society at large. While promising autonomy and efficiency, AI agents raise fundamental questions about their accuracy, governance, and the potential pitfalls of over-reliance on automation. Does this story sound vaguely familiar? Hold that thought. This discussion about the over-under of certain promises is for you.Show NotesThe economics of LLMs and DeepSeek R1 (00:00:03)Reviewing recent developments in AI technologies and their implications Discussing the impact of DeepSeek’s R1 model on the AI landscape, NVIDIA The origins of agentic AI (00:07:12)Status quo of AI models to date: Is big tech backing away from promise of generative AI?Agentic AI designed to perceive, reason, act, and learnGovernance and agentic AI (00:13:12)Examining the tension between cost efficiency and performance risks [LangChain State of AI Agents Report]Highlighting governance concerns related to AI agents Issues with agentic AI implementation (00:21:01)Considering the limitations of AI agents and their adoption in the workplace Analyzing real-world experiments with AI agent technologies, like Devin What's next for complex and agentic AI systems (00:29:27)Offering insights on the cautious integration of these systems in business practicesEncouraging a thoughtful approach to leveraging AI capabilities for measurable outcomesWhat did you think? Let us know.Do you have a question or a discussion topic for the AI Fundamentalists? Connect with them to comment on your favorite topics: LinkedIn - Episode summaries, shares of cited articles, and more. YouTube - Was it something that we said? Good. Share your favorite quotes. Visit our page - see past episodes and submit your feedback! It continues to inspire future episodes.

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