Neuro-Symbolic AI: Combining Learning With Logic
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...
16 Sep 202524min
LLMs in Chip Design: How AI Is Entering the Hardware Workflow
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 test...
2 Sep 202520min
How Embeddings and Vector Databases Power Generative AI
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 ...
19 Aug 202518min
Agentic AI: What Happens When Models Start Acting
In this episode, we explore agentic AI systems built to not just predict or classify, but to plan, reason, and act autonomously. We break down what makes these models different, how they use tools, me...
5 Aug 202519min
Understanding Attention: Why Transformers Actually Work
This episode unpacks the attention mechanism at the heart of Transformer models. We explain how self-attention helps models weigh different parts of the input, how it scales in multi-head form, and wh...
22 Jul 202520min
Markov Chains, Monte Carlo, and HMC: A Deep Dive
In this episode, we break down the essentials of Markov Chains, Monte Carlo simulations, and Markov Chain Monte Carlo methods. We explain key ideas like memoryless processes, stationary distributions,...
8 Jul 202523min
The Model Context Protocol (MCP): Making LLMs Actually Useful
In this episode, we dive into the Model Context Protocol, or MCP. It’s a new standard that helps large language models connect with real-world tools, data, and APIs in a more structured way. We’ll bre...
24 Jun 202516min
Generative Adversarial Networks (GANs) Explained: From DL Basics to Real-World Training Tips
This episode breaks down how GANs work by starting with deep learning basics like CNNs, gradient descent, and regularization. We then get into what actually goes wrong when training these models and h...
10 Jun 202527min
