Tag: #llm
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 208 posts
Open-Source LLM Landscape Guide: Models, Tools, and Deployment in 2026
A comprehensive guide to the open-source LLM ecosystem in 2026. Covers the leading model families (Llama, Mistral, Gemma, Qwen, DeepSeek), local inference tools (Ollama, llama.cpp, vLLM), fine-tuning techniques (LoRA, QL
2026-03-17 · 20 min read #open-source#llm#llama#mistral#gemmaLLM Evaluation and Benchmarking Guide: Measuring What Actually Matters
A comprehensive guide to LLM evaluation and benchmarking. Covers standard academic benchmarks (MMLU, HELM, MT-Bench), production evaluation pipelines, LLM-as-judge, human evaluation, RAG evaluation, safety testing, and b
2026-03-17 · 18 min read #llm#evaluation#benchmark#mmlu#helmLLM, Tool Calling & Embedding Benchmarks Deep Dive: What Each Benchmark Actually Measures
Complete analysis of major AI benchmarks — MMLU, HellaSwag, HumanEval, BFCL, MTEB, RAGAS and more. Understand exactly what each benchmark measures, score interpretation, limitations, and which benchmarks to use for your
2026-03-17 · 24 min read #llm#benchmarks#mmlu#mteb#bfclLLM Application Development Guide: From Prototype to Production
A comprehensive guide to building LLM-powered applications from prototype to production. Covers prompt engineering, RAG architecture, tool use, streaming, evaluation, cost optimization, and deployment patterns for real-w
2026-03-17 · 19 min read #llm#application-development#langchain#openai#prompt-engineeringDeepSpeed Complete Guide: ZeRO Optimization and Large-Scale Model Training
A complete guide to mastering Microsoft DeepSpeed. Learn ZeRO-1/2/3 optimization, Offload, pipeline parallelism, mixed precision, MoE, and DeepSpeed Inference with practical configurations and code examples.
2026-03-17 · 15 min read #deepspeed#zero-optimization#distributed-training#llm#pytorchPrompt Engineering Complete Guide: CoT, DSPy, Structured Output, and Prompt Security
A complete 2026 guide to prompt engineering — from Zero-shot and Chain-of-Thought to Tree-of-Thought, DSPy automatic optimization, Pydantic structured output, and prompt injection defense.
2026-03-17 · 25 min read #promptengineering#chainofthought#dspy#llm#structuredoutputAI Ethics, Safety, and Alignment Complete Guide: Responsible AI Development
A complete guide to understanding AI ethics, safety, and alignment. Covers hallucination, bias, privacy, RLHF, Constitutional AI, and the frontiers of AI safety research — everything an AI developer must know.
2026-03-17 · 22 min read #ai-ethics#ai-safety#alignment#responsible-ai#llmLarge-Scale Model Training Complete Guide: Strategies for Pre-training 100B+ Parameter LLMs
A complete practical guide to training hundred-billion parameter LLMs. Covers scaling laws (Chinchilla), Megatron-LM, 3D parallelism, checkpointing strategies, training stability, and data mixing with hands-on examples.
2026-03-17 · 21 min read #large-scale-training#llm#megatron-lm#distributed-training#scaling-lawsPrompt Engineering Complete Guide: From Zero-shot to Advanced Techniques
A complete guide to mastering all prompt engineering techniques. Learn Zero-shot, Few-shot, Chain-of-Thought, Tree of Thoughts, ReAct, Self-Consistency, and system prompt design through practical examples.
2026-03-17 · 32 min read #prompt-engineering#llm#chatgpt#claude#aiLLM Application Development Practical Guide: Mastering ChatGPT API, Claude API, and Gemini API
A practical guide to LLM application development covering ChatGPT API, Claude API, and Gemini API.
2026-03-17 · 22 min read #llm#openai#claude#gemini#apiDeep Learning Model Quantization Complete Guide: Master INT8, INT4, GPTQ, AWQ, GGUF
A comprehensive guide to mastering deep learning model quantization. Understand the principles from FP32 to INT8 and INT4 quantization, and master GPTQ, AWQ, GGUF, bitsandbytes, AutoGPTQ, and llama.cpp through practical
2026-03-17 · 23 min read #quantization#model-compression#gptq#awq#ggufHuggingFace Ecosystem Complete Guide: Master Transformers, Datasets, PEFT, and Accelerate
A complete guide to mastering the entire HuggingFace ecosystem. Learn Transformers, Datasets, Tokenizers, PEFT, Accelerate, Diffusers, and Hub API with hands-on examples.
2026-03-17 · 18 min read #huggingface#transformers#peft#accelerate#nlpAI System Design Complete Guide: From LLM Services to MLOps Architecture
A complete guide to designing production-grade AI systems. Learn real-world architectures for real-time inference systems, vector search infrastructure, LLM service architecture, data pipelines, and monitoring system des
2026-03-17 · 27 min read #system-design#ai-infrastructure#llm#mlops#architectureLLM Inference Optimization Complete Guide: KV Cache, Speculative Decoding, Continuous Batching
A complete guide to pushing LLM inference to its limits. Covers KV Cache, Speculative Decoding, Continuous Batching, PagedAttention, FlashInfer, multi-GPU inference, and DeepSeek MLA in depth.
2026-03-17 · 25 min read #llm#inference#optimization#kv-cache#speculative-decodingAI Agents Complete Guide: Building Autonomous AI Systems with LangChain, LangGraph, and CrewAI
A comprehensive guide to mastering AI agent systems. Build autonomous AI systems with real-world examples covering ReAct, Tool Use, and Function Calling through to LangChain agents, LangGraph workflows, and CrewAI multi-
2026-03-17 · 22 min read #ai-agent#langchain#langgraph#crewai#autonomous-aiRAG 2.0: Enterprise Knowledge Management Beyond Chatbots
RAG has evolved into the cornerstone of enterprise AI in 2026. Through hybrid search, knowledge graph integration, and multimodal processing, organizations are transforming implicit knowledge into explicit organizational
2026-03-16 · 9 min read #rag#llm#enterprise#knowledge-management#vector-databaseAI Agent Orchestration Frameworks 2026: LangGraph vs CrewAI vs AutoGen Complete Guide
Complete comparison guide for AI agent orchestration frameworks in 2026. Learn the key differences between LangGraph, CrewAI, AutoGen, and Dify with practical examples and selection criteria for your use case.
2026-03-16 · 8 min read #ai#ai-agent#langchain#llm#frameworkBitNet 1-bit LLM Inference Framework: Running Large Language Models on CPU
A guide to BitNet 1-bit LLM inference framework for running large language models on CPU hardware.
2026-03-15 · 25 min read #llm#bitnet#1-bit-llm#inference#cpu-deploymentLLM Utilization Strategies in the 1M Context Window Era: A Practical Guide to Large-Scale Context Processing
In March 2026, Anthropic announced GA of the 1M token context window for Claude Opus 4.6/Sonnet 4.6. Covers the paradigm shift from 128K-200K to 1M context, 5 practical patterns, RAG trade-offs, and cost optimization str
2026-03-15 · 41 min read #ai-platform#llm#context-window#long-context#claudeThe Complete Guide to LLM Inference Optimization: vLLM, TensorRT-LLM, Speculative Decoding
A comparative analysis of key technologies for maximizing LLM inference performance — vLLM, TensorRT-LLM, Speculative Decoding, and KV Cache optimization — with practical code examples and benchmarks.
2026-03-14 · 19 min read #llm#inference-optimization#vllm#tensorrt-llm#speculative-decoding