Engineering Insights
Practical knowledge from decades of engineering experience across AI systems, embedded development, power distribution, and software architecture.
Google and Microsoft have jointly released WebMCP, a W3C standard that lets websites expose structured tools to AI agents through the browser. What this means for web development and engineering applications.
How consulting multiple AI models simultaneously produces more reliable results for engineering decisions, reducing hallucinations and blind spots through structured consensus building.
How Anthropic's Model Context Protocol (MCP) enables seamless integration between AI assistants and engineering tools by providing a standardized translation layer between natural language and structured API calls.
How vector embeddings and semantic memory systems enable AI assistants to maintain context across sessions, accumulate knowledge over time, and provide increasingly valuable assistance for engineering projects.
A practical methodology for training robust neural networks that generalize well, using Minimum Description Length criterion, Nguyen-Widrow initialization, and committee-based ensemble methods.
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