How your LLM is silently hallucinating company revenue

Understanding the LLM Bubble

If there is no path to superintelligence by 2028, and there is little prospect of the dramatic product improvements needed to drive major short-term revenue growth (including solutions to inaccuracy and unreliability issues), it will be impossible to sustain either the investment boom or the LLM industry, as currently organized and operated. Continue reading Understanding the LLM Bubble on American Affairs Journal.

How your LLM is silently hallucinating company revenue

LLMs are accelerating work across engineering disciplines, from generating React components and building backend APIs to noodling with SQL. But we all know LLMs make mistakes, and the nature of those mistakes varies dramatically across domains. Using LLMs with databases is deceptively error-prone. When an LLM generates a React component, errors tend to surface quickly. The code either fails to compile or renders something visibly wrong: a button…

Why LLMs Make Terrible Databases and Why That Matters for Trusted AI

Large language models (LLMs) are now embedded across the SDLC. They summarize documentation, generate code, explain vulnerabilities, and assist with architectural decisions. The post Why LLMs Make Terrible Databases and Why That Matters for Trusted AI appeared first on Security Boulevard.