
This episode breaks down what graph neural networks (GNNs) are and why they matter. You’ll learn how GNNs use nodes and edges to represent relationships and how message passing lets models make sense of social, biological, and networked data. We’ll a... more
In this episode, we explain what neuro-symbolic AI is and why it matters. You’ll learn how neural networks handle patterns, how symbolic systems handle rules, and how combining the two can help models reason more reliably. We also cover real examples... more
In this episode, we look at how large language models are being used in chip and hardware design. We break down what LLM-aided design actually means, how models can generate HDL code, assist with testbench creation, and even support formal verificati... more
This episode explains how embedding models turn language into numerical vectors and how vector databases like Pinecone, FAISS, or Weaviate store and search those vectors efficiently. You'll learn how this system enables GenAI models to retrieve relev... more
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This podcast provides insights into artificial intelligence (AI) and machine learning (ML) by breaking down complex concepts into practical knowledge that can be easily understood. Topics discussed range from foundational technologies like generative adversarial networks and large language models to newer advancements such as neuro-symbolic AI and agentic AI. Each episode aims to demystify AI methodologies and explore their applications and implications across various fields, including healthcare, marketing, and hardware design. The unique approach avoids jargon and focuses on making technical subjects accessible to a wider audience, appealing particularly to both professionals in the tech industry and curious listeners interested in the ev... more
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