Ring Attention and Context Parallelism: How Long-Context LLMs Are Trained Across GPUs A single GPU cannot hold the activations of a one-million-token sequence, no matter how clever your kernel is.…
Document AI OCR in 2026: Pipelines vs Vision-Language Models Most retrieval-augmented generation (RAG) systems fail long before the language model gets involved. They fail at the PDF. A two-column paper…
Model Merging for LLMs: mergekit, TIES, DARE, SLERP and Evolutionary Merging Most teams that need a model with two skills assume they must train for both: more data, more GPU…
NGSI-LD FIWARE Context Brokers vs Unified Namespace: Which Fits Your Twin? Two communities have spent a decade solving what looks like the same problem, and they have barely read each…
Modelica Digital Twin vs Simulink: Physics-Based Models, OpenModelica and FMI (2026) Most digital twin projects do not fail because the data pipeline is wrong. They fail because the physics model…