Articles

Compare YOLO, RT-DETR, RF-DETR, and D-FINE for object detection, including COCO accuracy, T4 latency, and license differences.

Learn how to set up hybrid search in RAG with BM25 and vectors, including chunk IDs, RRF merging, weight tuning, and testing.

Agent Skills and Open Responses moved to the Agentic AI Foundation. Learn what this change may mean for company AI agents and next steps.

Step-by-step guide to labeling a support ticket archive with Mistral Batch API, including source tables, JSONL, Studio, errors, and custom_id matching.

Learn what LLM distillation means, how teacher and student models work, key approaches, and how it compares with quantization and fine-tuning.

Learn how to choose an embedding model for Russian-language RAG with a practical checklist covering testing, recall, vector size, and licensing.

What FSTEC Order No. 117 requires for AI in state information systems, including data transfer limits, requests, errors, and contractors.

Compare vLLM, Ollama, llama.cpp, and SGLang for self-hosting an LLM on your own server, including hardware, APIs, quantization, and use cases.

Learn how to set up document chunking for RAG, including chunk size, token overlap, metadata, tables, contracts, and testing.

On October 21, NVIDIA released Kumo Relational, which aims to predict churn, demand, and fraud across related tables without model training.

Update a RAG knowledge base in Qdrant with a practical checklist for release content, validation, alias switching, caching, and rollback.

Learn what LLM quantization means, how 8-bit and 4-bit compression reduces GPU memory use, and how GPTQ, AWQ, GGUF, and FP8 differ.

A practical ML model A/B test checklist for U.S. teams covering hypothesis, metrics, sample size, SRM checks, analysis, and rollout decisions.

Can your business use Llama, Qwen, Gemma, DeepSeek, YandexGPT, and GigaChat commercially? Learn the key license questions to review.

How to diagnose Claude API cache misses by checking usage, cache_control boundaries, prefix length, TTL, and tool changes.

Compare PDF parsers for RAG by license, hardware needs, Russian support, and scanned documents to choose the right tool.

Learn how to label computer vision data with a step-by-step process, annotation guidelines, pilot checks, and a reusable template.

Meta’s Muse Spark Open raises practical questions for businesses: hardware needs, license terms, and whether to run it on your own servers.

Why n8n shows Success while a lead never reaches the CRM. FAQ on AI workflow errors, Retry On Fail, Error Trigger, reruns, and recovery.

Learn what a vector database is, how embeddings and semantic search work, and when to use pgvector or a separate database.

What to check in an AI implementation contract: acceptance criteria, data rights, third-party models, costs, and exit terms before you sign.

Fine-tuning LLMs on company data: what it changes, how much data you need, privacy concerns, ownership, costs, and where to fine-tune in 2026.

Learn how to extract application fields with a local LLM and Ollama, define a JSON Schema, handle missing values, and validate results in Python.

Compare GigaAM, Whisper, and Parakeet for local meeting transcription, including Russian speech testing, a two-model cascade, and hands-on evaluation.