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This episode of Techsplainers introduces the concept of agentic AI, explaining how it differs from traditional AI models. Agentic AI, consisting of AI agents, operates autonomously and adaptively, using LLMs to function in dynamic environments. The episode discusses the benefits of agentic AI, including autonomy, proactivity, specialization, adaptability, and intuitiveness. Despite its potential, there are still some challenges, such as misaligned rewards, self-reinforcing behaviors, and cascading failures. Examples of real-world applications are provided, such as AI-powered trading bots, autonomous vehicles, healthcare chatbots, cybersecurity, and supply chain management.
Find more information at https://www.ibm.com/think/podcasts/techsplainers
Narrated by Alice Gomstyn
By IBMThis episode of Techsplainers introduces the concept of agentic AI, explaining how it differs from traditional AI models. Agentic AI, consisting of AI agents, operates autonomously and adaptively, using LLMs to function in dynamic environments. The episode discusses the benefits of agentic AI, including autonomy, proactivity, specialization, adaptability, and intuitiveness. Despite its potential, there are still some challenges, such as misaligned rewards, self-reinforcing behaviors, and cascading failures. Examples of real-world applications are provided, such as AI-powered trading bots, autonomous vehicles, healthcare chatbots, cybersecurity, and supply chain management.
Find more information at https://www.ibm.com/think/podcasts/techsplainers
Narrated by Alice Gomstyn