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Topic: AI hype cycle

The AI hype cycle refers to the cyclical pattern of enthusiasm, disillusionment, and eventual stabilization in the adoption and perception of AI technologies.

More on: AI hype cycle

The podcast episodes discuss the AI hype cycle and the current state of AI adoption and impact. Several episodes, such as AI Is The Fastest Adopted Work Tech Ever, But Still Not Fast Enough for Some, AI Hype Cycle: How to Find Real and Practical vs. Shiny | OpenAI's Louis Brandy, and Prof G Markets: Raspberry Pi's London IPO & Mistral's $640M Funding Round, analyze the gap between the hype surrounding AI and its practical usefulness, emphasizing the need for realistic expectations and alignment with business goals.

The episodes also touch on the challenges in navigating the hype cycle, such as distinguishing between general AI systems and more practical, task-specific applications, as discussed in Building Predibase: AI, Open-Source, and Commercialization with Dev Rishi and Travis Addair. The host in Is the AI Revolution Losing Steam? argues that the core AI revolution remains robust, despite more tempered narratives.

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