TechnicalAI glossary
Step-by-step reasoning (chain-of-thought)
Getting the model to spell out its intermediate reasoning steps before concluding, rather than answering in one go. Recent models do this on their own with their "reasoning tokens" or "reflection mode", which noticeably improves maths, code, and logic.
In other words
Do the calculation on a draft rather than doing it all in your head: you make far fewer mistakes.
Alyriaz articles that mention it
- OpenAI releases 372 maths results at once
A secret OpenAI model produced 722 manuscripts, 372 families of results, posted online. How to check them, and why it divides.
- An AI made of light spots deepfakes
An AI from the University of California uses light to analyse 15 videos at once and spots deepfakes with near-98% accuracy. Its limitations too.
- The scam that went through Microsoft's real page
Microsoft has dismantled EvilTokens, an AI-driven email scam. How it hacked 12,000 mailboxes, and how to protect yourself.
- How do you monitor thirty thousand agents?
Monitoring agents that act continuously requires a precise technical setup. We explain how this control layer works, what it catches and what it lets through.
- Kimi K3 burns through twelve times more reasoning tokens than Claude Opus: the hidden cost of thinking
An analysis of Kimi K3's reasoning traces reveals it consumes more than twelve times as many reasoning tokens as Claude Opus 4.8. This is both the secret to its performance and its biggest economic flaw. We explain the mechanism, and why the price per token says nothing about the real cost.
- What is a "reasoning model"? These AIs that take the time to think before answering
Deep Think mode, reasoning effort, sub-agents: recent models no longer respond immediately, they think first. We explain what a reasoning model is, what actually happens during that pause, why it improves answers, and why it sends the bill through the roof.