Introduction to LLM

Total of 5 articles available. Currently on page 1 of 1.

7.2 Resource-Efficient Training

A preview from Chapter 7.2: Learn how techniques like distillation, quantization, distributed training, and data efficiency make LLMs faster, cheaper, and greener.

2024-10-08

4.4 How LLMs Write Code: The Rise of AI-Powered Programming Assistants

Explore how large language models (LLMs) generate and complete code from natural-language prompts, and what it means for the future of software development.

2024-09-27

4.3 LLMs in Translation and Summarization: Enhancing Multilingual Communication

Learn how Large Language Models (LLMs) leverage Transformer architectures for accurate translation and summarization, improving efficiency in business, media, and education.

2024-09-18

4.2 Enhancing Customer Support with LLM-Based Question Answering Systems

Discover how Question Answering Systems powered by Large Language Models (LLMs) are transforming customer support, search engines, and specialized fields with high accuracy and flexibility.

2024-09-17

4.0 Applications of LLMs: Text Generation, Question Answering, Translation, and Code Generation

Discover how Large Language Models (LLMs) are used across various NLP tasks, including text generation, question answering, translation, and code generation. Learn about their practical applications and benefits.

2024-09-15

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améliorations 1009 Aufgabenverwaltung 1008 interface do usuário 1004 2FA 984 colaboración 973 modèles de tâches 968 AI-powered solutions 958 language support 958 Produktivität 956 interfaz de usuario 955 atualizações 952 búsqueda de tareas 949 Aufgaben suchen 901 ActionBridge 898 joindre des fichiers 897 Version 1.1.0 878 Aufgabenmanagement 874 Transformer 874 busca de tarefas 873 new features 867 Teamaufgaben 857 feedback automation 857 anexar arquivos 854 modelos de tarefas 848 customer data 832 interface utilisateur 829 Two-Factor Authentication 820 Google Maps review integration 817 CS data analysis 816 mentions feature 779

Authors

SHO

CTO of Receipt Roller Inc., he builds innovative AI solutions and writes to make large language models more understandable, sharing both practical uses and behind-the-scenes insights.