Picture 1 of 1
Picture 1 of 1
Artificial Intelligence: Foundations, Theory, and Algorithms Ser.: Foundation Models for Natural Language Processing : Pre-Trained Language Models Integrating Media by Sven Giesselbach and Gerhard Paaß (2023, Hardcover)
AlibrisBooks (461300)
98.6% positive Feedback
Price:
US $66.91
Approximately£50.12
+ $15.51 postage
Returns:
30 days return. Buyer pays for return postage. If you use an eBay delivery label, it will be deducted from your refund amount.
Condition:
New Hard cover
- Buy it nowFoundation Models for Natural Language Processing: Pre-Trained Language Models
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
About this product
Product Identifiers
PublisherSpringer International Publishing A&G
ISBN-103031231899
ISBN-139783031231896
eBay Product ID (ePID)16058368792
Product Key Features
Number of PagesXviii, 436 Pages
Publication NameFoundation Models for Natural Language Processing : Pre-Trained Language Models Integrating Media
LanguageEnglish
SubjectIntelligence (Ai) & Semantics, Speech & Audio Processing, Linguistics / General
Publication Year2023
TypeTextbook
Subject AreaComputers, Language Arts & Disciplines
AuthorSven Giesselbach, Gerhard Paaß
SeriesArtificial Intelligence: Foundations, Theory, and Algorithms Ser.
FormatHardcover
Dimensions
Item Weight29.8 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Number of Volumes1 vol.
IllustratedYes
Table Of Content1. Introduction.- 2. Pre-trained Language Models.- 3. Improving Pre-trained Language Models.- 4. Knowledge Acquired by Foundation Models.- 5. Foundation Models for Information Extraction.- 6. Foundation Models for Text Generation.- 7. Foundation Models for Speech, Images, Videos, and Control.- 8. Summary and Outlook.
SynopsisThis open access book provides a comprehensive overview of the state of the art in research and applications of Foundation Models and is intended for readers familiar with basic Natural Language Processing (NLP) concepts. Over the recent years, a revolutionary new paradigm has been developed for training models for NLP. These models are first pre-trained on large collections of text documents to acquire general syntactic knowledge and semantic information. Then, they are fine-tuned for specific tasks, which they can often solve with superhuman accuracy. When the models are large enough, they can be instructed by prompts to solve new tasks without any fine-tuning. Moreover, they can be applied to a wide range of different media and problem domains, ranging from image and video processing to robot control learning. Because they provide a blueprint for solving many tasks in artificial intelligence, they have been called Foundation Models. After a brief introduction to basic NLP models the main pre-trained language models BERT, GPT and sequence-to-sequence transformer are described, as well as the concepts of self-attention and context-sensitive embedding. Then, different approaches to improving these models are discussed, such as expanding the pre-training criteria, increasing the length of input texts, or including extra knowledge. An overview of the best-performing models for about twenty application areas is then presented, e.g., question answering, translation, story generation, dialog systems, generating images from text, etc. For each application area, the strengths and weaknesses of current models are discussed, and an outlook on further developments is given. In addition, links are provided to freely available program code. A concluding chapter summarizes the economic opportunities, mitigation of risks, and potential developments of AI.
LC Classification NumberQA76.9.N38
All listings for this product
Be the first to write a review
