Gemini Embeddings 2 is in public preview: one vector space for text, images, audio and video. The preview limits, calling it from WordPress with the HTTP API, and why cosine similarity on its own still is not enough.
Prompt caching takes up to 90% off input token cost and around 80% off latency, but only when the prompt prefix never moves. Here is how the pre-fill stage works, where the 1,024-token threshold sits, and how to order a prompt so it hits the cache.
A single noisy A/B test made a client drop a feature that was working. Bayesian thinking is the correction: write down what you believed before the data arrived, then update it. Includes the mammogram problem and a five-step checklist.
I moved a 500-line prompt into a Claude Code Skill and stopped re-pasting it every morning. This covers the three loading stages, how to write a description Claude will act on, and the three implementation patterns.
Jumping straight to XGBoost hides the problems in the data. Notes from a 32,581-row credit dataset: a heavy class imbalance, quartile cuts on age and income, and what a missing loan date does to model stability.
Grace periods for the EU AI Act and the Cyber Resilience Act run out in 2026, which moves data governance out of the legal team and into the server room. What that means for provenance, SBOMs and brittle pipelines.
Vector search handles synonyms well and loses exact identifiers. Notes on pairing BM25 with vector retrieval, merging both with rank fusion, and letting the agent retry when the results come back empty.
Plugin submissions climbed from 150 a week in 2024 to more than 500 in 2026, and the review queue is staffed by volunteers. What the job involves, and the 27 March 2026 application deadline.
Cleaning the dataset will not stop LLM hallucinations. Inside a transformer the right token is there in the early layers, and the model rotates away from it in the middle ones. What that means for monitoring an AI feature in production.
A look at the quantum software stack as it stands: the three modalities you can program against, the layers from QASM up to Qiskit and Q#, and why the transpiler and the debugging story matter more than the hardware headlines.