2 min read
Human Judgments and LLM-as-a-Judge Evaluations for LLM
Human Judgments and LLM-as-a-Judge Evaluations for LLM
All Posts
Large Language Models
Large Language Models & LLM Insights
Explore large language model architectures, fine-tuning strategies, prompt engineering, and how LLMs power modern AI applications.
2 min read
Standardized Test Cases to Assess AI Model Performance
Standardized Test Cases to Assess AI Model Performance
3 min read
How Do You Really Know If Your LLM Is Good Enough? A Guide to Controlled Evaluation Metrics
How Do You Really Know If Your LLM Is Good Enough? A Guide to Controlled Evaluation Metrics
2 min read
What is Controlled Evaluation for Large Language Models?
Assessing LLM Performance: Strategies to Evaluate and Improve Your App.
7 min read
How to Choose the Right LLM for Your Application: A 6-Step Framework
A practical 6-step framework for selecting the best large language model for your application based on performance, cost, latency, and business requirements.
5 min read
How to Evaluate LLMs: 3 Evaluation Types Every AI Team Needs in 2026
Learn the three critical LLM evaluation methods — controlled, human-centered, and field evaluation — that separate production-ready AI systems from demos.
6 min read
Your GPU vRAM Isn't the Problem: How KV Cache Management Fixes LLM Crashes
When LLMs crash during long conversations, the culprit is often the KV cache, not GPU vRAM. Learn the tiered memory management strategy that scales LLM inference.
5 min read
ByteDance Seed-OSS-36B-Instruct: 512K Context, Open Source, and Thinking Budget Control
ByteDance's Seed-OSS-36B-Instruct brings 512K context, Apache 2.0 licensing, and a unique thinking budget feature. A deep dive into the model that challenges proprietary LLMs.
5 min read
OpenAI GPT-OSS: Open-Weight LLM Models Under Apache 2.0 — What You Need to Know
OpenAI released GPT-OSS, open-weight models with 120B and 21B parameters under Apache 2.0 licensing. Learn about the architecture, capabilities, and what this means for AI development.
5 min read
What Is LLM Reasoning and How Does It Apply to AI Agents?
LLM reasoning enables AI agents to solve complex problems through chain-of-thought, ReAct, and self-reflection techniques. Learn how reasoning scales test-time compute for better results.
5 min read
What Is RLHF and How Does It Improve LLM Performance?
Reinforcement Learning from Human Feedback (RLHF) aligns LLMs with human values through three training stages. Learn how RLHF works, why it matters, and how it produces better AI.
5 min read
8 Techniques to Debug and Refine LLM Prompts for Consistent Results
Eight practical strategies for improving LLM prompt consistency — from prompt decomposition and few-shot examples to temperature tuning and output format specification.
7 min read
Understanding LLM Terminology: A Beginner-to-Pro Glossary for 2026
A comprehensive glossary of LLM terminology covering core concepts, training, fine-tuning, RAG, inference, evaluation, and deployment. Essential reference for AI practitioners.
4 min read
GPT-4 Explained: Architecture, Capabilities, and Practical Applications
A technical overview of GPT-4's transformer architecture, pre-training approach, multimodal capabilities, and practical applications for developers and businesses.