A practical comparison of local and cloud AI models across privacy, latency, quality, operating cost, deployment complexity, and hybrid architectures.
A practical explanation of AI API usage billing, including input tokens, output tokens, model prices, relay multipliers, cache discounts, minimum charges, and batch-job estimates.
A practical explanation of AI context windows, 128K and 1M token limits, long-context caveats, RAG, and how to manage context in real AI workflows.
A plain-language explanation of AI tokens, with examples for chat, long-document summaries, coding, context windows, and API billing.