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Research summaries, applied machine learning explainers and AI industry news, newest first.
TensorFlow: What It Is, Its Real History, and How to Use It
TensorFlow is Google's "end-to-end platform for machine learning" — its own description, not marketing gloss, since the project genuinely spans training, mobile and…
PyTorch: What It Is, Its Real History, and How to Use It
PyTorch is an open-source deep learning library originally built at Facebook AI Research (now Meta AI), and since September 2022 it's governed independently by the…
Claude Code Tutorial: From First Session to Subagents and Hooks
Claude Code is Anthropic's agentic coding tool: a terminal program, IDE extension, desktop app, and web client that reads your codebase, edits files, runs commands, and…
How to Reduce LLM API Costs: A $295-to-$5.75 Worked Example
Every LLM API bill is the same equation: tokens × price per token . OpenAI's own production guidance puts it in exactly those terms — cut the number of tokens, cut the…
How to Build an AI Agent: A Working Example in 100 Lines
An AI agent is a language model that can call your code, look at what came back, and decide what to do next. That is the whole idea. Anthropic puts it plainly in…
Prompt Caching: How It Works and What It Actually Saves
Prompt caching lets a model skip work it has already done. When two requests begin with the same text — the same system prompt, the same document, the same conversation…
How to Run an LLM Locally With Ollama
Running a large language model on your own computer takes two commands. The first installs Ollama, the second downloads a model and starts a chat:
Claude Skills: What They Are and How to Write Your First Skill
A skill is a folder with a SKILL.md file in it. Inside are instructions that teach Claude how to do a particular job the way you want it done, plus any scripts,…
Vector Databases: How They Work and How to Choose One
A vector database stores embeddings, the numeric vectors that represent the meaning of text, images or audio, and finds the ones closest to a query vector. It is the…
What Is RAG? Retrieval-Augmented Generation Explained With a Working Example
Retrieval-augmented generation (RAG) is a way to make a large language model answer from information it was never trained on. Before the model responds, a search step…