Kia ora, I'm Fang Zhang.
I write about where meaning comes from.


If you want to know how language models actually work, why minds get stuck, or what the cosmos can teach about both, start anywhere. Each post stands alone, with its sources linked and its reasoning laid out step by step.

Fang Zhang

Recent Articles

Evaluating LLMs: Two Questions, Not One

Choosing a model and judging your own application are two different evaluation problems. Benchmarks answer the first. Error analysis, graders and a small eval set answer the second.

A Reading Map for Scientific Spaces

A map of the series on Scientific Spaces (科学空间) and a reading order for the math behind machine learning.

Don't Bring the Answer to the Question

Most of us learned to ask questions in a room where the teacher already held the answer. Why that habit follows us out of the exam hall, and what breaks it.

Communication

VHF radio procedure, sound and light signals, and why marine communication is built around strict, unambiguous formats rather than natural conversation.

Emergency and Safety

The emergency procedures Day Skipper drills hardest, and why the course treats rehearsed response over improvised heroics.

Docking and Anchoring (with Knots)

The handful of knots and the underlying principles that make docking and anchoring predictable instead of improvised.

Weather: Winds, Tides and Currents

How the course ties together three separate moving systems — wind, tide, and current — into the single practical question of what the water will actually do to your boat.

Using Radar in Invisible Fields

How marine radar builds a picture out of nothing you can see, and the discipline needed to trust it in fog, at night, or in busy traffic.

Curated Articles

I Ching 64 Hexagrams: A Quick Reference Table

A practical quick-reference table of the 64 I Ching hexagrams.

Day Skipper Notes

Working through chartwork, compass theory, tides, and collision regulations as a new blog category.

Reading List

Books, articles, and blogs I'm currently reading or want to get to.

Tools, Notes and Ideas for Building a LLM

Tools, reference code, training tips and evaluation for building a language model.