The Practical AI Digest
A generative AI-powered podcast by M. Mostagir Bhuiyan. Each episode distills advanced AI/ML topics into real-world insights for practitioners.
About the Podcast
The Practical AI Digest is built using NotebookLM to synthesize research papers, technical reports, and industry developments into conversational episodes. The format is designed for engineers and technical leaders who want to stay current on AI/ML without reading every paper. Episodes cover topics from model architecture and training techniques to deployment patterns and infrastructure decisions.
Hosted by M. Mostagir Bhuiyan, the podcast draws on hands-on experience building AI infrastructure, writing research on retrieval-augmented generation and micro-containerization, and leading cloud platform teams.
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Episodes
AI for Code: How Models Write Software
March 3, 2026
This episode explores the rise of AI coding assistants. We discuss how models like OpenAI’s Codex (which powers GitHub C...
Multimodal Models: Combining Vision, Language, and More
February 17, 2026
This episode explores multimodal AI : models that can see, read, and even hear. We explain how models like OpenAI’s CLIP...
Efficient Fine-Tuning: Adapting Large Models on a Budget
February 3, 2026
This episode dives into strategies for fine-tuning gigantic AI models without needing massive compute. We explain parame...
Diffusion Models: AI Image Generation Through Noise
January 20, 2026
In this episode, we break down what diffusion models are and why they’ve become the go-to method for AI image generation...
Graph Neural Networks: Learning from Connections, Not Just Data
September 30, 2025
This episode breaks down what graph neural networks (GNNs) are and why they matter. You’ll learn how GNNs use nodes and ...
Neuro-Symbolic AI: Combining Learning With Logic
September 16, 2025
In this episode, we explain what neuro-symbolic AI is and why it matters. You’ll learn how neural networks handle patter...