Graph RAG represents a shift from text-centric retrieval to structure-aware understanding to enable: 1. More consistent answers 2. Better global context 3. Reduced hallucination 4. Stronger reasoning over relationships Rather than asking LLMs to guess structure from text at generation time, Graph RAG makes structure explicit upfront.

"Machine-learning Method on Vectorized Three-Dimensional Model and Learning System Thereof" describes a novel method for utilizing vectorized 3D models to generate synthetic data of real-world objects for AI training. It can be applied for various applications, including object identification and anomaly detection, where training data are difficult or economically infeasible to acquire, and the robotic agents need these capabilities to function and swiftly interact with the p

Marketers have more performance data than ever, yet trust in that data isn’t really improving. The fix lies in performance measurement using Marketing Mix Modeling.

In the highly regulated and patient-centric world of pharmaceutical launches, gaining a rapid, nuanced understanding of public perception is no longer optional—it is a critical necessity. Social listening has evolved from a simple monitoring tool into a sophisticated intelligence engine, providing real-time data that directly informs safety monitoring, brand strategy, and commercial success.

The future of Physical AI isn't just about better technology—it's about smarter SDG implementation. Organizations that understand how to match SDG strategies with their specific Physical AI needs will gain significant competitive advantages.

Polus is an AI-driven solution for pharmaceutical medical affairs. It analyzes MSL (Medical Science Liaison) engagements with HCPs (Healthcare Professionals) to provide insights beyond traditional, periodic ATU (Awareness, Trial, and Usage) studies. The product uses sentiment analysis, topic analysis, and summarization to give a real-time understanding of HCP perceptions. This continuous feedback loop helps commercial and marketing teams to refine their strategies pre-launch,