Ep. 7 What is Agentic AI, and Why Should We Care About It? | AI Insights and Innovation

This week’s episode of AI Insights and Innovation, David Linthicum, principal analyst at theCUBE Research, explores the cutting-edge components of agentic AI, including perception, data processing, decision-making frameworks and adaptability.
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Linthicum tackles critical challenges such as scalability, data integration and computational demands while also highlighting key technologies like reinforcement learning, natural language processing and graph search.
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Linthicum unravels the complexities of deploying agentic AI in real-world applications, from autonomous vehicles and healthcare to industrial automation and personal assistants. Additionally, he addresses the vital ethical and safety considerations necessary for responsible AI development.
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[@kwesiafful8050]

I find this helpful as it starts to separate out specific identifiers for GenAI uses. The overarching GenAI label does group different operations under one umbrella which isn’t always helpful. To each their own though 👍🏾

[@EffectiveMuscle]

What you describe at <a href="#" class="seekto" data-time="595">9:55</a> doesnt sound like agentic AI. It sounds like how heavy machinery has worked for decades. Like a car's ECU that constantly tracks an engine's RPMs, fuel flow, oil pressure, etc and constantly adjusts camshafts, throttle body position, and even shifts gears for the driver. It tells the driver when there's an issue via a check engine light. How is the decision making in the pump jack software any different from the algorithms of an ECU or a power plant control system?

[@user-wr4yl7tx3w]

i don't think there is any new info here...