The Practical AI Digest

The Practical AI Digest

Distilling AI/ML theory into practical insights. One concept at a time. No jargon.

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Jaksot(25)

Synthetic Data: Artificial Data for Real Insights

Synthetic Data: Artificial Data for Real Insights

In this episode, we explore how synthetic data is created and used to improve AI models. Synthetic data refers to artificial datasets generated by models (like GANs or language models) that mimic real...

14 Huhti 30min

Explainable AI: Opening the Black Box

Explainable AI: Opening the Black Box

In this episode, we look at how researchers are making AI models more transparent and interpretable. We discuss techniques like SHAP values and LIME that explain model predictions by attributing impor...

31 Maalis 24min

Aligning AI with Human Intent: RLHF in Action

Aligning AI with Human Intent: RLHF in Action

In this episode, we demystify how researchers teach AI models to behave helpfully and safely using Reinforcement Learning from Human Feedback (RLHF). We discuss why even very large models can generate...

17 Maalis 24min

AI for Code: How Models Write Software

AI for Code: How Models Write Software

This episode explores the rise of AI coding assistants. We discuss how models like OpenAI’s Codex (which powers GitHub Copilot) are trained on millions of code repositories to generate software from n...

3 Maalis 30min

Multimodal Models: Combining Vision, Language, and More

Multimodal Models: Combining Vision, Language, and More

This episode explores multimodal AI : models that can see, read, and even hear. We explain how models like OpenAI’s CLIP learn joint representations of images and text (by matching pictures with their...

17 Helmi 28min

Efficient Fine-Tuning: Adapting Large Models on a Budget

Efficient Fine-Tuning: Adapting Large Models on a Budget

This episode dives into strategies for fine-tuning gigantic AI models without needing massive compute. We explain parameter-efficient fine-tuning methods like LoRA (Low-Rank Adaptation), which freezes...

3 Helmi 28min

Diffusion Models: AI Image Generation Through Noise

Diffusion Models: AI Image Generation Through Noise

In this episode, we break down what diffusion models are and why they’ve become the go-to method for AI image generation. You’ll learn how these models gradually add and remove noise to transform rand...

20 Tammi 24min

Graph Neural Networks: Learning from Connections, Not Just Data

Graph Neural Networks: Learning from Connections, Not Just Data

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 ...

30 Syys 202531min