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Category: AI

AI, AI in WordPress, Development

Drift detection: why a live ML model quietly gets worse

The difference between data drift and concept drift, the two tests I reach for first (K-S and PSI), and how I wire the check into a WP-CLI command so a drifting model triggers an alert instead of a bad quarter.

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AI, AI in WordPress, Development

AI coding agent context: give it a map, not your whole repo

Three habits that stop a coding agent inventing hooks and tables: an AGENTS.md file it has to keep updated, real documentation and schema files in the context, and a fresh thread when the task changes.

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AI, Development

Fourier features and the spectral bias problem in MLPs

A neural network trained on the Mandelbrot set comes out blurry because of spectral bias. Multi-scale Gaussian Fourier Features fix that by putting the high frequencies into the input instead of asking the model to find them.

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AI, AI in WordPress, Development

Retrieval-augmented forecasting: giving models a memory

Retrieval-augmented forecasting adds a search step to a time-series model, so it can pull similar windows out of history instead of leaning on frozen training weights. Covers embeddings, FAISS indexing and four ways to fuse retrieval with a forecaster.

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AI, Development

Why small-scale credit scoring cannot be private and fair

Differential privacy noise hides the fairness gap when a bank only has a few thousand records. Across half a million records a federated model reached 96.94% accuracy with a 0.069% fairness gap, which is the case for joining a consortium.

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AI, Development

Why visual anomaly detection models fail in production

High AUROC on MVTecAD does not mean a model survives a production line. Notes on input resolution, center cropping, background masking, and where early stopping usually goes wrong.

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AI, AI in WordPress

Where AI in UX actually saves me time

Two years of daily use, boiled down: AI in UX is good at sorting research transcripts, flagging the obvious usability problems and drafting copy from client bullets. The judgment stays with you.

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AI, Development

RAG chunk size is the variable most people never tune

Small chunks lose context, medium chunks produce near identical similarity scores, large chunks are stable but noisy. How RAG chunk size affects retrieval, plus a PHP splitter that respects word boundaries.

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AI, Development

Reinforcement learning for LLM reasoning: proofs over vibes

Part 2 of the vibe proving series: how an RL loop built around a hard proof checker teaches a model to follow logic rules, and where it still falls over on nested proofs.

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AI, AI in WordPress

Hugging Face Transformers for NLP without the API bill

Running NLP locally with Hugging Face Transformers instead of paying per API call: the pipeline API, zero-shot tagging, chunking text past a 512 token limit, and where to host the model.

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