大規模言語モデル (LLM) - GeeksforGeeks

Large Language Model (LLM) - GeeksforGeeks Courses Tutorials Interview Prep Artificial Intelligence Interview Questions Project Ideas Search Algorithms Local Search Algorithm Generative AI Data Science Machine Learning Deep Learning ML-Projects Robotics Large Language Model (LLM) Last Updated : 2 May, 2026 Large Language Models (LLMs) are advanced AI systems built on deep neural networks designed to process, understand and generate human-like text. LLMs Learn patterns, grammar and context from text and can answer questions, write content, translate languages and many more. By using massive datasets and billions of parameters, LLMs have transformed the way humans interact with technology. Modern LLMs include ChatGPT (OpenAI), Google Gemini, Anthropic Claude, etc. LLM Working of LLM LLMs are primarily based on the Transformer architecture which enables them to learn long range dependencies and contextual meaning in text. At a high level, they work through Working Input Embeddings : Converting text into numerical vectors. Positional Encoding : Adding sequence/order information. Self-Attention : Understanding relationships between words in context. Feed-Forward Layers : Capturing complex patterns. Decoding : Generating responses step by step. Multi-Head Attention : Parallel reasoning over multiple relationships. Popular LLMs GPT-4 and GPT-4o (OpenAI) : Advanced multimodal reasoning and dialogue capabilities. Gemini 1.5 (Google DeepMind) : Long-context reasoning, capable of handling 1M+ tokens. Claude 3 (Anthropic) : Safety-focused, strong at reasoning and summarization. LLaMA 3 (Meta) : Open-weight model, popular in research and startups. Mistral 7B / Mixtral (Mistral AI) : Efficient open-source alternatives for developers. BERT and RoBERTa (Google/Facebook) : Strong embedding models for NLP tasks. mBERT and XLM-R : Early multilingual LLMs. BLOOM : Large open-source multilingual model, collaboratively developed. Applications Code Generation : LLMs can generate accurate code based on user instructions for specific tasks. Debugging and Documentation : They assist in identifying code errors, suggesting fixes and even automating project documentation. Question Answering : Users can ask both casual and complex questions, receiving detailed, context-aware responses. Language Translation and Correction : LLMs can translate across many languages (often dozens to 100+). Prompt-Based Versatility : By crafting creative prompts, users can unlock endless possibilities, as LLMs excel in one-shot and zero-shot learning scenarios. Advantages Can perform new tasks using zero-shot and few-shot learning without retraining Efficiently process and understand large amounts of text data Adapt easily to specific domains through fine-tuning Automate repetitive language-based tasks, reducing human effort Work effectively across multiple domains like healthcare, education and business Limitations Require very high computational resources, making them expensive to train Training can take a long time, often weeks or months Depend on large amounts of high-quality and unbiased data Consume significant energy, contributing to environmental impact Can introduce bias and misinformation, raising ethical concerns Comment Article Tags: Article Tags: Artificial Intelligence data-science ChatGPT Explore Introduction to AI What is Artificial Intelligence (AI) 8 min read Types of Artificial Intelligence (AI) 4 min read Types of AI Based on Functionalities 4 min read Agents in AI 7 min read Artificial intelligence vs Machine Learning vs Deep Learning 3 min read Problem Solving in Artificial Intelligence 6 min read Top 20 Applications of Artificial Intelligence (AI) in 2025 13 min read AI Concepts Search Algorithms in AI 6 min read Local Search Algorithm in Artificial Intelligence 7 min read Adversarial Search Algorithms in Artificial Intelligence (AI) 15+ min read Constraint Satisfaction Problems (CSP) in Artificial Intelligence 10 min read Knowledge Representation in AI 5 min read First-Order Logic in Artificial Intelligence 4 min read Reasoning Mechanisms in AI 9 min read Machine Learning in AI Machine Learning Tutorial 5 min read Deep Learning Tutorial 2 min read Natural Language Processing (NLP) Tutorial 2 min read Computer Vision Tutorial 3 min read Robotics and AI Artificial Intelligence in Robotics 5 min read What is Robotics Process Automation 8 min read Automated Planning in AI 8 min read AI in Transportation 8 min read AI in Manufacturing : Revolutionizing the Industry 6 min read Generative AI What is Generative AI 7 min read Generative Adversarial Network (GAN) 10 min read Cycle Generative Adversarial Network (CycleGAN) 7 min read StyleGAN - Style Generative Adversarial Networks 5 min read Introduction to Generative Pre-trained Transformer (GPT) 4 min read BERT Model - NLP 7 min read Generative AI Applications 7 min read AI Practice Top Artificial Intelligence(AI) Interview Questions and Answers 15+ min read Top Generative AI and LLM Interview Question with Answer 15+ min read 30+ Best Artificial Intelligence Project Ideas with Source Code [2026 Updated] 15+ min read AI Courses Generative AI Course for Developers 2 min read Data Science Project Based Learning 2 min read Data Analytics Course with AI 2 min read