Prefill is compute-bound, decode is memory-bound, and running both on one GPU wastes most of it. Splitting them into separate pools, the KV-cache transfer tax that comes with it, and when it pays off.
A synthetic dataset can pass every standard check and still lose the correlations, rare events and privacy margin that your model depends on. Here are the three checks I run before shipping one, with the Python for two of them.
A static A/B test keeps sending half your traffic to the losing variation until someone stops the test. Thompson sampling moves the traffic as the numbers come in. Here is the Beta distribution behind it and how to store the state in WordPress.
My Clippings.txt is an append-only mess, and the expanded highlights inside it will wreck any summary you generate from the raw file. Here is the parser, the deduplication logic and the local Ollama call I use instead.
An ad hoc prompt works once, then quietly stops matching the result you got the first time. Claude Code Skills wrap the workflow in a SKILL.md file, with structured JSON for the data and Python for the parts that have to be deterministic.
On EMNIST Letters, a GMVAE reached 80% accuracy from roughly three labeled samples per cluster, where XGBoost needed 35 times the supervision. Most of that comes down to soft decoding instead of hard cluster assignment.
Spry Fox has run the same WordPress blog since 2010, through hits, an acquisition and spin-outs. Why that outlasts social platforms, and how to cache a deep archive with the Transients API so an old database stays fast.
WordPress 7.0 is on pause while Real-Time Collaboration is reworked. What the April 15 dev chat said about treating the next RC as a beta, the PR tagging problem, and core-abilities moving out of React.
Bigger context payloads buy accuracy and charge you latency and tokens. How KNN-based prefiltering with scikit-learn trims an ICL payload without losing predictive accuracy, and whether to run it client side or service side.
Retrieval gets worse as the memory pool grows, while the confidence score keeps climbing. Here is what causes RAG memory decay and the four fixes I put into production systems: topic routing, semantic deduplication, relevance based eviction, and lexical reranking.