The Practical AI Digest

The Practical AI Digest

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

Tämä podcast on lisätty Podme-palveluun avoimen RSS-syötteen kautta eikä se ole Podmen omaa tuotantoa. Siksi podcastin jaksot saattavat sisältää mainontaa.

Jaksot(25)

The Evaluation Crisis: We Do Not Know How Good Our Models Actually Are

The Evaluation Crisis: We Do Not Know How Good Our Models Actually Are

MMLU is saturated. Chatbot Arena is gameable. Public benchmarks leak into training data. The only eval that matters is the one you build yourself, on your data, for your task.

30 Heinä 20min

Mixture of Experts at the Edge: Running 30B Parameter Models on Your Laptop

Mixture of Experts at the Edge: Running 30B Parameter Models on Your Laptop

A 30B parameter model runs on a MacBook because only 3B parameters fire per token. Mixture of Experts splits memory cost from compute cost, and that changes everything about where AI can run.

16 Heinä 20min

The Agent Interoperability Problem: Why Your AI Agents Can Not Talk to Each Other

The Agent Interoperability Problem: Why Your AI Agents Can Not Talk to Each Other

90% of enterprises deploy AI agents. Only 23% scale them. The gap is interoperability. Three protocols, MCP, A2A, and ACP, are racing to build the connective tissue before the ecosystem fragments.

2 Heinä 21min

KV Cache Compression: The Memory Wall Nobody Talks About

KV Cache Compression: The Memory Wall Nobody Talks About

Your GPU is not compute-bound. It is memory-bound. The KV cache is eating half your inference budget, and two ICLR 2026 breakthroughs KVTC and TurboQuant are about to change the math entirely.

18 Kesä 21min

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 Kesä 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 Touko 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 Touko 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 Huhti 25min