Machine Learning Explained
Plain-English explainers of ML concepts like embeddings, RAG and intent recognition.
- AI Tokens and Context Windows Explained: How They Shape Cost, Limits and AccuracyWhat tokens are, how many fit in a context window, why hidden reasoning tokens raise your bill and why bigger windows are not always better, using the figures OpenAI, Google and Anthropic publish, plus practical ways to count and cut token use.
- Cognitive Intent Recognition: The Evolution Beyond Keyword MatchingExploring vector space embeddings and neural semantic routing for ultra-low latency intent resolution.