#large language model
6032 related articles
·3 min
Should the ACM Digital Library Open Up to Large Language Models? The Battle Between Academic Corpora and AI Training
Exploring whether the ACM Digital Library should open to LLM training. Analyzing the value of academic corpora for AI, data exhaustion concerns, copyright battles, and pragmatic paths including licensing and RAG.
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·3 min
Learning AI Large Language Models: A Complete Roadmap from Beginner to Practitioner
A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy to Help You Fully Understand
Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy That Makes Everything Click
LLMs aren't search engines — they're more like super compressors. This article explains how large models compress corpora to learn semantic patterns, and explores the principles and limitations of emergent intelligence.
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·3 min
Introduction to AI Large Language Models: A Must-Read Guide for Test Engineers
A thorough explanation of the essence of AI large language models: from conceptual hierarchy and Transformer mechanics to probabilistic nature, helping test engineers understand LLM strengths and weaknesses.
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From Word Vectors to Large Language Models: The Complete Evolution of AI 2.0 Technology
From word vectors and embeddings to RNNs, BERT, Transformers, and ChatGPT — a complete guide to the technical evolution of large language models and the AI 2.0 era.
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·3 min
Is a Large Language Model Just a Function? AI Principles Explained with Middle School Math
LLMs explained through the lens of functions: input is x, output is y, training solves for parameters, inference computes results. Trillion parameters, next-token prediction — no advanced math needed.
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·3 min
What Is a Large Language Model, Really? The Core Principles Explained Through the Lens of Functions
Demystify large language models using middle-school math: LLMs are complex functions, training solves for parameters, and inference predicts next-token probabilities.
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·3 min
Understanding Large Language Models from Scratch: The Complete AI Evolution from Deep Blue to DeepSeek
A beginner-friendly guide clarifying AI, machine learning, deep learning, and LLMs — tracing the evolution from Deep Blue to AlphaGo, ChatGPT, and DeepSeek.
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·2 min
OpenSpiel 2.0 Released: Reinforcement Learning Framework Fully Embraces Large Language Models
OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.
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·4 min
Getting Started with AI Test Development: Core Principles and Underlying Logic of Large Language Models
New to AI test development? This article breaks down the differences between machine learning and traditional programming, the origins of AI hallucinations, and the core principles of NLP/NLU/NLG to help test engineers build a solid AI knowledge framework.
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GODMODE Project Deep Dive: AI Jailbrea…
·2 min
GODMODE Project Deep Dive: AI Jailbreaking Techniques and the Security Arms Race in Large Language Models
GODMODE (G0DM0D3) has 9,300+ GitHub stars fueling debate on AI jailbreaking vs. safety alignment. A deep technical dive into LLM guardrails, prompt injection, and AI security governance.
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·2 min
GPT-5.6 Launches With a Warning: Compute Capacity Is the Real Test for Large Language Models
Altman warned of possible GPT-5.6 service disruptions at launch, highlighting compute capacity as the true bottleneck for LLMs. Here's what it means for users.
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·3 min
AI Large Language Models for Beginners: Core Concepts and Chinese Model Landscape
New to AI? This guide clarifies AI, machine learning, deep learning, and LLMs, traces milestones from Deep Blue to DeepSeek, and maps out China's LLM landscape.
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·3 min
AI Large Language Models Explained: Principles, Strengths, Weaknesses, and a Testing Guide
A complete beginner's guide to AI large language models: principles, the Transformer architecture, strengths, weaknesses, and practical tips for testers.
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·4 min
AI Large Language Models for Beginners: Core Concepts, History, and China's Model Landscape
A beginner's guide to AI large models: clarify the relationships between AI, ML, deep learning, and LLMs, trace the journey from Deep Blue to ChatGPT and DeepSeek, and explore China's model landscape.
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·2 min
Deep Dive into MCP: How Large Language Models Connect to the Outside World
MCP (Model Context Protocol) is the standardized protocol connecting AI models to external tools and data — the 'USB-C port' of the AI era. Learn its origins and value.
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·2 min
Learning AI Large Language Models from Scratch: A Complete Roadmap That Avoids the Three Biggest Mistakes
90% of AI beginners struggle with large language models due to misdirection, poor Prompt logic, and lack of real-world deployment skills. This guide covers the complete learning path from zero to practice.
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Loving LLMs, Hating the Hype: How Engi…
·2 min
Loving LLMs, Hating the Hype: How Engineers Rationally Evaluate Large Language Models
Engineers love LLMs for real productivity gains but hate the hype around AGI narratives, glossed-over hallucinations, and valuation bubbles. Here's how to find the rational balance.
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Can AI Prove Mathematical Conjectures?…
·5 min
Can AI Prove Mathematical Conjectures? The Truth Behind the GPT-5.6 Incident and the Limits of Large Language Models
A PDF claiming GPT-5.6 Sol Ultra proved the Cycle Double Cover Conjecture sparked debate on Hacker News. We unpack the truth and the limits of LLMs in math proofs.
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