All Episodes

AI Hardware: GPUs, TPUs and Beyond

Synthetic Data: Artificial Data for Real Insights

Explainable AI: Opening the Black Box

Aligning AI with Human Intent: RLHF in Action

AI for Code: How Models Write Software

Multimodal Models: Combining Vision, Language, and More

Efficient Fine-Tuning: Adapting Large Models on a Budget

Diffusion Models: AI Image Generation Through Noise

Graph Neural Networks: Learning from Connections, Not Just Data

Neuro-Symbolic AI: Combining Learning With Logic

LLMs in Chip Design: How AI Is Entering the Hardware Workflow

How Embeddings and Vector Databases Power Generative AI

Agentic AI: What Happens When Models Start Acting

Understanding Attention: Why Transformers Actually Work

Markov Chains, Monte Carlo, and HMC: A Deep Dive

The Model Context Protocol (MCP): Making LLMs Actually Useful

Generative Adversarial Networks (GANs) Explained: From DL Basics to Real-World Training Tips

Bayesian vs. Frequentist Thinking in Marketing Mix Modeling