エピソード

  • Formal Logic - pt. 02
    2025/09/03
    We are moving past the limitations of probabilistic AI by embracing formal logic and verification. This approach allows us to mathematically prove that our AI systems will behave correctly under specific conditions, providing a new level of trust and reliability essential for critical applications in finance, healthcare, and beyond.

    This is the second and last part of the episode.
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    13 分
  • Formal Logic - pt. 01
    2025/08/26
    We are moving past the limitations of probabilistic AI by embracing formal logic and verification. This approach allows us to mathematically prove that our AI systems will behave correctly under specific conditions, providing a new level of trust and reliability essential for critical applications in finance, healthcare, and beyond.

    This is the first part of a two-part podcast
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    19 分
  • Context Engineering
    2025/08/19
    We go beyond prompt engineering to focus on context engineering, a systematic approach to building production-grade AI. By treating the agent's context as a structured, observable pipeline, we enable teams to create robust, cost-effective, and scalable AI systems that deliver real business value.
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    17 分
  • Memory
    2025/08/12
    What separates a forgetful chatbot from an AI agent that feels truly smart?

    In this episode, Root unpacks the power of memory in AI—from basic sliding windows to advanced retrieval-augmented and memory-augmented strategies inspired by neuroscience.

    Discover how the right memory architecture enables personalization, learning, and adaptability in your agents.

    Whether you’re building customer support bots, coding copilots, or next-gen assistants, you’ll get practical examples, production tips, and a glimpse into the future of multi-modal, real-time memory in AI.

    Tune in and learn how to make every interaction count!
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    17 分
  • A Bigger Context
    2025/08/05
    Dive into the evolving world of AI context windows with Rooting. This episode unpacks the surprising paradox of 'more memory' in AI models: exploring the immense benefits of larger context, the hidden limitations like reasoning degradation, and the cutting-edge engineering techniques—from positional encoding tricks to novel reasoning architectures—that are shaping how AI truly understands and remembers. Essential listening for solution architects, software developers, and data scientists navigating the complexities of large language models.
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    29 分
  • The Brain Analogy
    2025/07/29
    How much do artificial intelligence systems really resemble the human mind? In this episode of Rooting, The Podcast, host Root takes you on a deep dive into the emerging metaphor that’s reshaping our understanding of AI: the idea that modern large language models and multi-agent systems are designed with architectures that parallel human cognition.

    Explore how features like chat interfaces act as digital sensory systems, context windows mimic our short-term memory, and Retrieval-Augmented Generation (RAG) gives AI its own form of long-term recall.

    We’ll examine the practical implications of these analogies for architects, developers, and data scientists, and discuss how understanding these human-AI parallels can drive better system design, interface engineering, and collaboration between people and intelligent machines.






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    9 分
  • Meet the Host
    2025/07/28
    Welcome to Rooting, a podcast about AI, made by AI with a human touch!

    Meet Root, your AI host with a mission: cutting through the noise and hype to help technical leaders make sense of modern AI. In this special intro episode, Root pulls back the curtain and shares how an AI, trained on the latest research and guided by top human experts, is ready to become your go-to guide in the fast-changing world of artificial intelligence. Find out what makes this hybrid human-AI approach unique, why you’ll hear both clarity and candor, and how Rooting plans to take you from buzzwords to breakthroughs—one episode at a time. Tune in, because when it comes to AI, sometimes the smartest guide really is the one who never stops learning.
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    5 分