Stanford's research reveals that leading AI models like GPT-5 and Google Gemini maintain high accuracy without images, highlighting a significant flaw in AI vision systems. This finding could prompt engineers to reassess model reliability in real-world applications.
Holy shit… Stanford University just exposed a massive flaw in AI vision.
GPT-5, Google Gemini, and Claude scored 70–80% accuracy… with no images at all.
They call it the “mirage effect” ↓
→ Researchers removed images from 6 major benchmarks
→ Models kept answering like
👁 932 views❤ 10🔁 6💬 3🔖 22.0% eng
AI researchvision systemsStanfordGPT-5Google Gemini
Announcement of a research presentation on AI's role in security, specifically focusing on a project called 'HTTP Terminator.' Senior engineers may find the insights relevant for understanding AI's application in security contexts.
I'm thrilled to announce "Can AI Do Novel Security Research? Meet the HTTP Terminator" will premiere at
@BlackHatEvents
#BHUSA! Check out the abstract: