This article details how a leading OTA transformed its hotel review pipeline with multimodal large‑language models, real‑time event‑driven architecture, and automated static‑info correction, achieving sub‑second moderation, 99.6% accuracy, and measurable cost and user‑experience gains.
This article explores how modern video AI techniques—ranging from transformer‑based classification to semi‑supervised retrieval and token‑halting acceleration—enable efficient, accurate detection of prohibited content and fast, scalable video search in the era of short‑form media.
This article documents a step‑by‑step case study of applying GPT‑4 to automatically review and filter game dialogue, detailing the initial challenges, iterative prompt refinements, added safety rules, and the resulting improvements compared with earlier models.
AI-powered porn detection leverages deep neural networks to classify images, but faces serious hurdles such as visual similarity with benign content, subjective standards of obscenity, and vulnerabilities stemming from training data, making human moderators indispensable for reliable content safety.
AI-based porn detection uses deep neural networks to classify images, but faces tough hurdles such as visual similarity with benign content, subjective standards for nudity, and vulnerabilities from training‑data dependence, meaning human moderators remain essential for reliable safety.
The article examines the NBA's China controversy, the massive Chinese backlash, the subsequent suspension of partnerships, and explores how artificial intelligence tools like Facebook's Rosetta are being used—and limited—in moderating online speech, highlighting the balance between automated detection and human review.
