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Mvaak

Insights

Thinking about AI data.

What we have learned about specification, annotation and quality — written for the people who have to make these decisions.

LatestDataset Quality

What actually makes training data usable

Volume is the easiest property to measure and the least predictive of whether a dataset improves a model. Here is what tends to matter instead.

3 min read

All articles

8 articles

Data Annotation

Annotation guidelines are the real deliverable

Two annotators disagreeing about the same example is not a training problem. It is a definitions problem, and it is far cheaper to solve before collection than after.

3 min read

AI Data

How to scope a first dataset

The most common mistake is committing to volume before the specification has been tested. A small end-to-end pass costs less and tells you more.

3 min read

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