AI reliability
AI & Automation
TrustScale’s Argus: A $70 Billion Problem Gets a Real-Time Fact-Checker
TrustScale launched Argus, a real-time AI hallucination detector that verifies claims 135x faster than manual checks. AI hallucinations cost firms $70B yearly.
AI & Automation
AI Hallucinations: The Most Dangerous Problem in Modern AI
AI hallucinations cause real harm in healthcare, law, and finance. Detection techniques, RAG mitigation, grounding methods, and sector-specific risks explained.
AI & Automation
The AI Alignment Problem: Why Making AI Systems Reliable Matters
The AI alignment problem is the challenge of making sure AI systems reliably do what humans intend. Here is why it is harder than it seems.
AI & Automation
LLM Evaluations: The Hidden Discipline Behind Reliable AI
Testing large language models is becoming a core engineering discipline. Here is how companies evaluate AI reliability, accuracy, and safety before deployment.
AI & Automation
Multi-Model Consensus: Why the Future of AI Isn’t a Single Oracle
Perplexity's Model Council queries Claude, GPT, and Gemini simultaneously for consensus answers. Why multi-model AI beats relying on a single system.
