Why human skills are the secret ingredient in generative AI
Rethinking AI development — from code to human intelligence When most people think of artificial intelligence, they imagine complex algorithms and machine logic. But Sigma
How red teaming AI reveals gaps in global model safety
Red teaming goes global Red teaming — intentionally probing AI models for weaknesses — has long been a key practice in AI safety. But most
Building LLMs with sensitive data: A practical guide to privacy and security
Know your data: what “sensitive” means in practice Why this matters for LLMs: leakage is real Modern models can memorize and later regurgitate rare or
When “uh… so, yeah” means something: teaching AI the messy parts of human talk
A quick primer: what’s what (and why it matters) Signals, not noise: disfluency carries meaning A sentence like, “I — I can probably help …
Bias detection in generative AI: Practical ways to find and fix it
Protection: Adversarial testing surfaces unfair behavior Common bias patterns: Prompt-induced harms (e.g., stereotyping a profession by gender), jailbreaks that elicit unsafe content about protected classes,
FAQs: Human data annotation for generative and agentic AI
What is human data annotation in generative AI? Human data annotation is the process of labeling AI training data with meaning, tone, intent, or accuracy