Tag: llm

GraphRAG enhances retrieval-augmented generation by grounding LLM responses in structured knowledge graphs instead of flat vector embeddings.

Build AI-powered applications with Neo4j as the knowledge layer — from graph-backed RAG to autonomous graph agents.

Run 3 specialised LLMs on a single DGX Spark in under 2 minutes with 100+ tok/s throughput. Production orchestration patterns revealed.

DeepSeek V4 ships two open-weight MoE models — a 1.6T Pro and a 284B Flash — with novel sparse attention, FP4 quantisation, 1M token context, and validated Huawei Ascend NPU support. Here's what actually changed.

Alibaba released Qwen3.6-35B-A3B on 16 April 2026, the first open-weight model in the Qwen3.6 series. The benchmarks show real gains in agentic coding, but the architecture is unchanged from Qwen3.5 and the red flags warrant scrutiny.

How CoreCoder reverse-engineered Anthropic's Claude Code from 512K lines into a minimal 950-line implementation, revealing the essential architecture of modern AI coding agents.

A 26-person startup spent $20M training a 400B MoE model on 2,048 B300 GPUs — and produced the strongest open reasoning model outside China. Trinity-Large-Thinking ranks #1 on τ²-Airline at 1/28th the cost of Claude Opus 4.6.

A technical comparison of vLLM and SGLang, the two leading open-source LLM inference engines, covering architecture, performance, and when to pick each one.

Gemma 4 brings frontier-level multimodal intelligence to open-source — with models ranging from 2B to 31B parameters, MoE efficiency, and native audio support for edge devices.

Professional guide to implementing LiteLLM proxy for multi-provider LLM integration in GraphWiz.AI, featuring production deployment, cost optimization, and advanced routing strategies.

A practical guide to engineering prompts for autonomous AI systems that plan, act, and iterate toward goals.

Deploy Qwen's latest agentic coding model with vLLM on NVIDIA DGX Spark. Complete configuration for tool calling, extended context, and optimal performance on the GB10 Grace Blackwell Superchip.

A practical guide to deploying production-ready LLM inference using vLLM on NVIDIA DGX Spark hardware, covering configuration, troubleshooting, and performance optimization.

Comprehensive guide to prompt engineering techniques that work reliably in production environments, including chain-of-thought, few-shot learning, and output formatting strategies.

Comprehensive guide on training artificial intelligence for software testing: architectures, pedagogical strategies, and validation frameworks

Interactive exploration of prompt engineering techniques for Knowledge Graph generation using LLMs