Results for “partitioning”

Optimizes Qdrant query performance for large limits across multiple shards by using Poisson-distributed subsampling to reduce inter-shard data transfer.

Design and implement network segmentation in Operational Technology environments using VLANs, industrial firewalls, data diodes, and software-defined networking, following the Purdue Model and IEC 62443 standards.

Build and debug Retrieval-Augmented Generation pipelines — chunking, embedding, retrieval, reranking

Computer vision engineering skill for object detection, image segmentation, and visual AI systems. Covers CNN and Vision Transformer architectures, YOLO/Faster R-CNN/DETR detection, Mask R-CNN/SAM segmentation, and production deployment with ONNX/TensorRT. Includes PyTorch, torchvision, Ultralytics, Detectron2, and MMDetection frameworks. Use when building detection pipelines, training custom models, optimizing inference, or deploying vision systems.

LISA: Reasoning Segmentation via Large Language Model

Expert guidance for distributed NoSQL databases (Cassandra, DynamoDB). Focuses on mental models, query-first modeling, single-table design, and avoiding hot partitions in high-scale systems.

Load sharded datasets (npy, Parquet, HDF5, raw binary) into distributed cuPyNumeric arrays using manual partitioning and Legate task launches.

Design and implement security zones and conduits for industrial automation and control systems per IEC 62443-3-2, including zone partitioning, firewall configuration, and validation through traffic analysis and penetration testing.