machine made worldsA journal of artificial intelligence

Ideas, collected

The journal.

Essays, guides and observations. Find something worth sitting with.

33 articles

Link radar, September 15, 2026

Five reads: Anthropic's CI scaling lessons, Copilot auto-model tiers, Cloudflare per-Worker access, Cloudflare search-without-training controls, and ShadowPEFT in PEFT.

2 min read

What is Temperature?

Temperature is the sampling dial that sets how random a model's next token feels. What low and high settings do, and where builders set it for factual versus creative work.

1 min read

Link radar, September 14, 2026

Five reads: Amodei's frontier-pacing essay, OpenAI storage engineering, WeatherNext 3, VS Code Agents usage metrics, and Copilot code-review updates.

2 min read

What is Inference?

Inference turns a trained model and a fresh prompt into an answer, running the weights forward instead of learning. How serving differs from training, and where builders spend their latency and cost budget.

1 min read

Link radar, September 11, 2026

Five reads: OpenAI's Agents API, Anthropic's September threat report, Anthropic's targeting-capability evaluations, Cloudflare Containers for Codex, and GitHub's AI Scan APIs.

2 min read

What is Quantization?

Quantization shrinks a model by storing its weights in fewer bits so it fits smaller GPUs and laptops. How lower precision trades a little accuracy for speed and where builders reach for it.

1 min read

Link radar, September 10, 2026

Five reads: a default-on Node.js registry for Workers, Python 3.14 on Workers, Meta's Muse Spark 1.3 coding model, Google's Gemini 3.8 Flash tiers, and OpenAI's GPT-6 Astra flagship.

2 min read

What is Fine-tuning?

Fine-tuning keeps training a ready-made model on focused examples so it follows one task, style, or domain more reliably. What changes under the hood, what it costs, and when builders choose it over prompting alone.

1 min read

Link radar, September 9, 2026

Five reads: a machine-checked proof from a large agent run, a faster image model, a petabyte-scale variant catalogue, post-quantum origin handshakes, and a managed sandbox for coding agents.

2 min read

What is Embeddings?

Embeddings turn text, images, or rows into lists of numbers that place similar meanings close together. How the vectors are made and where builders use them for search and grouping.

1 min read

What is RAG?

RAG grounds a language model in documents retrieved at query time instead of memory alone, cutting hallucinations on facts the model never learned. How the retrieve-then-write loop works and where builders reach for it.

1 min read

What is prompt injection?

Prompt injection hides hostile instructions inside data a language model reads, steering it to disobey its real task. How the trick works and how builders counter it.

1 min read