A 2026 technical overview of image segmentation models: semantic, instance, and panoptic segmentation, U-Net to SAM 2, with a comparison and applications.
An applied defense-in-depth pattern for agentic AI security: the indirect prompt injection kill-chain, OWASP LLM/Agentic Top 10, and layered mitigations.
Corrective RAG (CRAG) and Self-RAG explained for 2026: retrieval grading, query rewriting, self-reflection loops, a reference design, and when each pays off.
A 2026 benchmark analysis of MiniMax M3: open-weight coding, 1M-token context, and multimodality — methodology caveats, results, and how to read the numbers.
A comparative analysis of state-of-the-art object detection models, updated for 2026: YOLO11/12, RT-DETR, transformer detectors, accuracy, latency, and trade-offs.
The LLM semantic router pattern in 2026: route requests by intent and cost to the right model, with vLLM Semantic Router, embeddings, and a reference design.
A 2026 benchmark of LLM JSON mode and constrained decoding: throughput, latency, and accuracy across grammar-based methods, with reproducible methodology.
A 2026 text-to-SQL benchmark methodology: execution accuracy, schema linking, latency, and cost across model tiers - plus where generated SQL goes wrong.
How LLM prompt caching works in 2026: provider-side vs self-hosted KV reuse, cache-aware prompt design, hit-rate economics, and where it quietly breaks.
A 2026 architecture guide to semantic caching for LLM apps: embedding similarity lookup, cache invalidation, hit-rate tuning, and where it quietly breaks.