4 posts
How is LLM hallucination prevented? A production guide to verification layers: RAG grounding, citations, guardrails, self-verification, output checks, and human oversight.
What is an LLM? How do Large Language Models (LLMs) work, what does Transformer architecture solve, what are tokens, embeddings, and context windows, and how do GPT-5, Claude Opus 4.7, Gemini 3, and Llama 4 compare? A comprehensive 2026 reference covering Turkish LLM performance, training stages, hallucination control, and cost modeling.
The most comprehensive 2026 Turkish LLM benchmark: MMLU-TR, Belebele-TR, TruthfulQA-TR, Turkish HumanEval, MGSM-TR, and hallucination tests. Score tables for GPT-5, Claude Opus 4.7, Gemini 3, Mistral Large 3, Llama 4, DeepSeek V3, Qwen 2.5, and local Turkish models (Cezeri, BERTurk, Trendyol-LLM), with use-case mapping and transparent methodology.
A comprehensive reference for designing, scaling, and shipping Retrieval-Augmented Generation (RAG) systems in production with KVKK compliance. Covers Turkish-capable embedding model selection, vector DB comparison, chunking, hybrid search, re-ranking, hallucination control, eval harness, and three anonymized Turkish enterprise case studies — end-to-end production architecture.