Tag: #llm

← All posts

• AI Prompt Engineering Complete Guide: 30 Techniques Every Developer Should Know ♪ Listenable

  From Zero-shot to Chain-of-Thought, Tree-of-Thought, ReAct, Few-shot, and Self-Consistency — 30 prompt engineering techniques for developers with practical examples. How to get maximum performance from Claude, GPT-4, and

  2026-03-22 · 25 min read #prompt-engineering#ai#llm#chatgpt#claude

• 2025 Open Source AI Models Showdown: DeepSeek R1 vs Llama 4 vs Qwen 3 vs Mistral ♪ Listenable

  DeepSeek R1 (671B/37B), Llama 4 Scout/Maverick, Qwen 3 (235B MoE), Mistral 8x22B — complete comparison of the 2025 open-source AI model leaders with benchmarks, licenses, deployment guides, and cost analysis.

  2026-03-22 · 20 min read #open-source#ai#llm#deepseek#llama

• Toss Bank ML Engineer (MLOps) Complete Guide: From MLFlow to LLM Platform — Tech Stack Deep Dive ♪ Listenable

  Complete analysis of Toss Bank ML Platform Team MLOps Engineer JD. Deep dive into MLFlow, Airflow, JupyterHub, Kubeflow, Triton Inference Server, ScyllaDB Feature Store, and LLM platform — with 30 interview questions and

  2026-03-21 · 38 min read #mlops#ml-platform#tossbank#kubernetes#mlflow

• 2025 AI Research Trends: Top HuggingFace Papers and 10 Defining Research Directions

  A developer-focused review of HuggingFace trending papers and the 10 defining AI research trends of 2025. DeepSeek-R1 pure RL reasoning, Nemotron-Cascade 30B/3B MoE, GRPO, PagedAttention, million-token context limitation

  2026-03-21 · 15 min read #ai-research#papers#huggingface#reasoning#moe

• AI Supercomputer at Home: Study LLMs on NVIDIA DGX Spark and Create Content with ComfyUI ♪ Listenable

  Run 200B-parameter LLMs locally on NVIDIA DGX Spark ($3,999) and generate FLUX/SDXL images with ComfyUI. Complete guide with specs, benchmarks, setup instructions, and cost analysis — the era of personal AI supercomputer

  2026-03-21 · 37 min read #nvidia#dgx-spark#comfyui#local-ai#llm

• [Architecture] Complete Guide to LiteLLM: Unified Serving of 100+ LLMs

  A comprehensive guide on integrating 100+ LLMs through a single API with LiteLLM, covering Proxy server setup, cost tracking, rate limiting, load balancing, and production deployment.

  2026-03-20 · 15 min read #architecture#litellm#llm#ai-gateway#mlops

• RAG vs Fine-tuning vs Prompt Engineering: The Complete Decision Framework

  A practical comparison of RAG, fine-tuning, and prompt engineering from a production engineering perspective, with a concrete decision framework, real cost calculations, and honest gotchas from building these systems in

  2026-03-18 · 7 min read #rag#fine-tuning#prompt-engineering#llm#ai-development

• Tool Calling in Practice: How AI Interacts with the World and Common Pitfalls

  Tool calling is what transforms an LLM from a text transformer into an agent that can actually do things. Full implementation of OpenAI function calling and Claude tool use, parallel execution patterns, and the five mist

  2026-03-18 · 9 min read #tool-calling#function-calling#ai-agent#llm#ai-development

• LLM Agent Design Patterns: From ReAct to Multi-Agent Orchestration

  ReAct, Chain of Thought, Plan-and-Execute, Reflection, Tree of Thoughts — a practical breakdown of which LLM agent design pattern to use and when, from an engineer who has built them in production.

  2026-03-18 · 9 min read #ai-agent#react#llm#design-patterns#ai-development

• Prompt Engineering 2025: Getting Maximum Performance from Modern LLMs

  Even the best model gives poor results with a poor prompt. Six prompt engineering techniques proven in production, with working code for GPT-4o, Claude, and open-source models.

  2026-03-18 · 7 min read #prompt-engineering#llm#ai-development#gpt-4o#claude

• LLM Hallucination: Why AI Makes Things Up and 5 Strategies to Prevent It

  A technical deep-dive into why LLMs hallucinate, covering all four hallucination types and five practical prevention strategies including RAG, self-critique pipelines, Chain of Verification, and temperature tuning — all

  2026-03-18 · 9 min read #hallucination#llm#ai-reliability#ai-development#rag

• 1 Million Token Context Windows: Is RAG Becoming Obsolete?

  With Gemini 1.5 Pro's 1M token context and Claude's 200K, many developers ask: why bother with RAG? We compare real costs, latency, and quality to give you an honest answer.

  2026-03-18 · 6 min read #context-window#rag#llm#long-context#ai-development

• Fine-tuning in Practice: Building Your Own Model with LoRA and QLoRA

  You don't need 7 H100s. With LoRA and QLoRA, you can fine-tune a 70B model on a single consumer GPU. A practical end-to-end guide with working code.

  2026-03-18 · 7 min read #fine-tuning#lora#qlora#llm#ai-development

• Complete Guide to Open Source LLMs: Llama 3, Mistral, DeepSeek, Qwen, and Gemma

  A comprehensive overview of the open source LLM landscape covering Llama 3, Mistral, DeepSeek, Qwen, and Gemma.

  2026-03-17 · 14 min read #llm#llama#mistral#deepseek#qwen

• Complete Guide to LLM Evaluation and Benchmarking: MMLU, MT-Bench, RAGAS, LM-Eval

  A complete guide to evaluating LLMs correctly. Covers standard benchmarks such as MMLU, MT-Bench, and HumanEval, evaluating RAG systems with RAGAS, practical use of LM-Evaluation-Harness, and building production LLM eval

  2026-03-17 · 17 min read #llm#evaluation#benchmark#ragas#lm-eval

• Building LLM from Scratch: Complete Guide to Understanding GPT through Code ♪ Listenable

  A complete guide to building and understanding Large Language Models from scratch. Implement a full GPT architecture in PyTorch — from tokenizer to Transformer, pretraining, and fine-tuning.

  2026-03-17 · 21 min read #llm#gpt#transformer#from-scratch#deep-learning

• LLM Fine-tuning Complete Guide: Master LoRA, QLoRA, RLHF, and DPO ♪ Listenable

  A complete guide covering every LLM fine-tuning technique. From Full Fine-tuning to LoRA, QLoRA, RLHF, DPO, and Instruction Tuning — master them all with HuggingFace PEFT and hands-on examples.

  2026-03-17 · 21 min read #llm#fine-tuning#lora#qlora#rlhf

• Complete Guide to Korean NLP and LLM: Mastering KoBERT, KLUE, HyperCLOVA, and EXAONE ♪ Listenable

  A comprehensive guide to Korean NLP and LLM covering KoBERT, KLUE, HyperCLOVA, and EXAONE.

  2026-03-17 · 27 min read #korean-nlp#kobert#klue#hyperclova#exaone

• Torch-Titan Complete Guide: Everything About Large-Scale Distributed Training with PyTorch ♪ Listenable

  A complete guide to mastering large-scale LLM distributed training with PyTorch Titan (torchtitan). Covers FSDP2, pipeline parallelism, tensor parallelism, 4D parallelism, Flash Attention, and mixed precision with hands-

  2026-03-17 · 19 min read #torch-titan#distributed-training#pytorch#fsdp#deep-learning

• Deep Learning Recommendation Systems Complete Guide: From Collaborative Filtering to LLM-based RecSys

  A complete guide to recommendation systems from foundations to the latest deep learning techniques. Master collaborative filtering, Matrix Factorization, NCF, Two-Tower models, sequential recommendation, GNN-based approa

  2026-03-17 · 18 min read #recommendation-system#collaborative-filtering#deep-learning#two-tower#llm