Articles and insights in AI & Machine Learning (3 posts)
LLM API costs scale with token usage, and unoptimized prompts can make costs 5-10x higher than necessary. This guide covers prompt engineering for efficiency, caching strategies, model routing, and the trade-offs of each approach.
A critical, evidence-based examination of customer privacy risks across every major AI provider — American and Chinese. What data they collect, what they could be collecting, and what the real cost of using these services is to your privacy. Includes actionable strategies for protecting sensitive information.
LLM applications fail in ways traditional software does not: prompt injection, jailbreaks, data extraction, and confident wrong answers. This guide covers systematic red-teaming approaches for AI systems built by product teams, not ML researchers.