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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Episoder(29)

Context Rot: Why Million-Token Windows Quietly Fail

Context Rot: Why Million-Token Windows Quietly Fail

Models advertise million-token windows but accuracy degrades well before the limit. Three recent studies, the mechanisms behind the rot, and a practitioner playbook for what to do Monday.

4 Jun 21min

LLMOps: Operating Large Language Models in Production

LLMOps: Operating Large Language Models in Production

Building an AI model is one thing: keeping a large language model running reliably in the real world is another. In this episode, we discuss LLMOps, the emerging set of practices and tools for deployi...

26 Mai 28min

TinyML & Edge AI: Machine Learning on Devices

TinyML & Edge AI: Machine Learning on Devices

In this episode, we explore how AI is moving from the cloud to tiny devices. TinyML is the field of optimizing models and algorithms to run on microcontrollers, smartphones, and other edge devices wit...

12 Mai 25min

AI Hardware: GPUs, TPUs and Beyond

AI Hardware: GPUs, TPUs and Beyond

This episode is all about the specialized hardware that makes modern AI possible. We explain how GPUs became the workhorses of deep learning by offering massive parallelism for matrix math, and how co...

28 Apr 25min

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 Apr 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 Mar 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 Mar 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 Mar 30min

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