Lavoisier S.A.S.
14 rue de Provigny
94236 Cachan cedex
FRANCE

Heures d'ouverture 08h30-12h30/13h30-17h30
Tél.: +33 (0)1 47 40 67 00
Fax: +33 (0)1 47 40 67 02


Url canonique : www.lavoisier.fr/livre/informatique/artificial-intelligence-and-large-language-models/descriptif_5091306
Url courte ou permalien : www.lavoisier.fr/livre/notice.asp?ouvrage=5091306

Artificial Intelligence and Large Language Models An Introduction to the Technological Future

Langue : Anglais

Auteurs :

Couverture de l’ouvrage Artificial Intelligence and Large Language Models

Having been catapulted into public discourse in the last few years, this book serves as an in-depth exploration of the ever-evolving domain of artificial intelligence (AI), large language models, and ChatGPT. It provides a meticulous and thorough analysis of AI, ChatGPT technology, and their prospective trajectories given the current trend, in addition to tracing the significant advancements that have materialized over time.

Key Features:

  • Discusses the fundamentals of AI for general readers
  • Introduces readers to the ChatGPT chatbot and how it works
  • Covers natural language processing (NLP), the foundational building block of ChatGPT
  • Introduces readers to the deep learning transformer architecture
  • Covers the fundamentals of ChatGPT training for practitioners

Illustrated and organized in an accessible manner, this textbook contains particular appeal to students and course convenors at the undergraduate and graduate level, as well as a reference source for general readers.

Preface

About the Authors

Chapter 01 – Fundamentals of Artificial Intelligence (AI)

Introduction
Short History of Artificial Intelligence
What Is Brain Turing Test?
The Objectives of AI
Problem Solving
Reasoning
Learning
Achieving General Intelligence
Planning
Deeper Insight into Data
Types of Artificial Intelligence
Types of AI Based on Functionalities
Reactive Machines
Limited Memory
Theory of Mind
Self-Aware
Types of AI Based on Capability
Artificial Narrow Intelligence (ANI)
Artificial General Intelligence (AGI)
Artificial Super Intelligence (ASI)
What Is the Structure of an Artificial Intelligence System?
Environment
Agent
Sensor
Affecters
Actuator
Different Fields of Artificial Intelligence
Cognitive Computing (CC)
Machine Learning (ML)
Deep Learning (DL)
Artificial Neural Networks (ANN)
Computer Vision (CV)
Natural Language Processing (NLP)
Expert Systems (ES)
Reinforcement Learning (RL)
Robotics
What Is Logic Used in Artificial Intelligence and Its Types?
Deductive logic
Inductive logic
Other Main Types of Logic in AI
Propositional Logic
First-Order Logic
Second-Order Logic
Third-Order Logic
Higher-Order Logic
Modal Logic
Applications of Logic in AI
Artificial Intelligence Approaches
Symbolic Approach
Connectionist Approach

Chapter 02 – Introduction to ChatGPT

Introduction
Generative Modeling
Generative Artificial Intelligence Models
Types of Generative Artificial Intelligence Models
Probabilistic Generative Models
Adversarial Generative Models
Normalizing Flow-Based Models
Introduction to Most Popular Generative Models
Problem Solving Scope of ChatGPT
History of Generative Models
A Glimpse of ChatGPT Statistics
OpenAI Conversational Model
Transfer Learning Model Used in ChatGPT
Proximal Policy Optimization (PPO)
Trust Region Policy Optimization (TRPO)
Introduction to Large Language Model (LLM)
Reinforcement Learning from Human Feedback (RLHF)
Cloud Computing and ChatGPT
Application Programming Applications (APIs)
Transformer Library
Python Programming Language for ChatGPT
Neural Network Technology in ChatGPT
Deep Learning Technology in ChatGPT
Natural Language Processing (NLP) in ChatGPT
How to Use ChatGPT Bot?
Salient Features of ChatGPT
Limitations of ChatGPT
Top Services of ChatGPT

Chapter 03 – ChatGPT Technology Stack

Introduction
Hardware Technology Stack
Graphics Processing Units (GPUs)
Tensor Processing Units (TPUs)
High Bandwidth Memory (HBM)
Compute Unified Device Architecture (CUDA)
Cloud Computing Infrastructure
Software Technology Stack
Programming Languages
Python Programming Language
C++ Programming Language
CUDA Programming Language
HTML Language
JavaScript
Deep Learning Frameworks
PyTorch Platform
Keras Platform
TensorFlow
Theano
NumPy
Anaconda
Natural Language Processing Libraries
Hugging Face Transformers
SpaCy Platform

Chapter 04 – Natural Language Processing (NLP): Foundation Building Block of ChatGPT

Introduction
What Is NLP?
How Does NLP Technology Work?
Branches of NLP
Historical Eras of NLP
Symbolic NLP Era
Statistical NLP Era
Neural NLP Era
Applications of NLP
ChatGPT
Domain-Specific Chatbots
Language Translation
Speech Recognition
Text Processing
Spam Filtering
Sentiment Analysis
Predictive Recommendation
Smart Assistants
Data Analysis
Grammar Checker Applications
Personalized Marketing
Social Media Monitoring
What Techniques Are Used in Natural Language Processing?
Parts of Speech Tagging
Tokenization
Named Entity Recognition (NER)
Sentiment Analysis
Summarization
Topic Modeling
Text Classification
Keyword Extraction
Lemmatization and Stemming

Chapter 05 – Deep Learning Transformer Architecture

Introduction
Importance of Deep Learning Transformer
What Is Transformer Model?
What Is Pre-Trained System?
What Are Main Types of Pre-Trained Systems?
Bidirectional Encoder Representations from Transformers (BERT)
Generative Pre-Trained Transformer (GPT)
Universal Sentence Encoder (USE)
Text-to-Text Transfer Transformer (T5)
Attention Mechanism in Transformer
What Are Large Language Models?
Examples of Large Language Models
What Is Large Language Model Dataset?
Main Types of Large Language Datasets
Wikipedia Text Corpus
Web Page Text Corpus
Books Text Corpus
Other Corpora
Architecture of Different Versions of GPT
Version GPT 1.0
Version GPT 2.0
Version GPT 3.0
Version GPT 3.5

Chapter 06 – Fundamentals of ChatGPT Training

Introduction
Training Content Types
Articles
Books
Webpages
Other Sources
Training Models
Large Language Models
Techniques Used in Training Models
Masked-Language Modeling Technique
Next-Token-Prediction Technique
ChatGPT Training Process Simplified
Long-Short-Term-Memory (LSTM) Model
Supervised Fine Tuning (SFT) Model
Reward Model
Reinforcement Learning Model (RLM)
Model Evaluation

Chapter 07 – Using ChatGPT Like a Pro

Introduction
Important Tasks to Use ChatGPT Like a Pro
How to Register For ChatGPT?
How to Login ChatGPT?
Overview of ChatGPT interface
Getting Started with Your First Query
Overview of Using ChatGPT
How to Regenerate New Response?
How to Copy & Share Response?
How to Give Feedback to ChatGPT?
How to Add Customized Instructions?
How to Set Themes?
How to Turn-Off/On Your Chat History?
How to Manage Links for Sharing Chats?
How to Export Chat Data?
How to Logout of Your ChatGPT Account?
How to Delete Your ChatGPT Account?
Upgrading to ChatGPT-4
Difference between Different Versions of ChatGPT
Advanced Features of ChatGPT 4.0
How to Use ChatGPT in Software Development?
How to Use ChatGPT for Effective Text Generation?
What Are the Benefits of Using ChatGPT?
Limitations of ChatGPT

Chapter 08 – Using Different Versions of ChatGPT

Introduction
Use of the Main Versions of ChatGPT
Using ChatGPT 3.5
Main Features and Uses
Using ChatGPT 4.0
Main Features and Uses

Chapter 09 – Future of ChatGPT

Introduction
Possibilities
Challenges
Implications

Chapter 10 – Top Use Cases of GPT-Based Tools

Introduction
AI-Powered Tools Similar to ChatGPT
ChatGPT
Google Bard
Claude 2
DALL-E 2
GitHub Copilot

Bibliography

Professional Practice & Development and Undergraduate Advanced

Kutub Thakur, PhD is Associate Professor, School of Cybersecurity & IT, University of Maryland Global Campus, USA.

Helen Barker, D.M. is Professor, Cybersecurity Department Chair, University of Maryland Global Campus, USA

Al-Sakib Khan Pathan, PhD is Professor, Department of Computer Science and Engineering, United International University, Bangladesh

Date de parution :

15.6x23.4 cm

À paraître, réservez-le dès maintenant

148,11 €

Ajouter au panier