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  1. Digital surveillance fiction
    dataveillance in contemporary science fiction
    Autor*in: Krause, Michael
    Erschienen: [2021]; ©2021
    Verlag:  Avinus, Hamburg

    Standort:
    Universitätsbibliothek Passau
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Dissertation
    ISBN: 9783869381541; 386938154X
    Weitere Identifier:
    9783869381541
    Schlagworte: Überwachung <Motiv>; Science-Fiction-Literatur; Neue Medien <Motiv>; Englisch
    Weitere Schlagworte: Eggers, Dave (1970-): The circle; Doctorow, Cory (1971-): Little brother; Gibson, William (1948-): Pattern recognition
    Umfang: 300 Seiten
    Bemerkung(en):

    Dissertation, Universität Potsdam, 2019
  2. Digital surveillance fiction
    dataveillance in contemporary science fiction
    Autor*in: Krause, Michael
    Erschienen: 2021
    Verlag:  AVINUS, Hamburg

    Standort:
    Universitätsbibliothek Siegen
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    21KNTL1180
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    Medientyp: Dissertation
    ISBN: 9783869381541; 386938154X
    Weitere Identifier:
    9783869381541
    DDC Klassifikation: Amerikanische Literatur in in Englisch (810)
    Schriftenreihe: Edition Medienkulturforschung ; [7]
    Schlagworte: Neue Medien <Motiv>; Überwachung <Motiv>
    Weitere Schlagworte: Doctorow, Cory (1971-): Little brother; Eggers, Dave (1970-): The circle; Gibson, William (1948-): Pattern recognition; The society of control; The Snowden leaks; crisis of subjectivity; Surveillance in fiction; Digital civil rights after 9/11; Social transparency; Demystifying the internet; Edward Snowden; Cyberpunk aesthetic; Advanced data capitalism
    Umfang: 300 Seiten, Illustrationen, 19 cm
    Bemerkung(en):

    Dissertation, Universität Potsdam, 2019
  3. Quick start guide to large language models
    strategies and best practices for using ChatGPT and other LLMs
    Autor*in: Ozdemir, Sinan
    Erschienen: [2024]; © 2024
    Verlag:  Addison-Wesley, Hoboken, New Jersey

    The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying... mehr

    Standort:
    Universitätsbibliothek der RPTU in Kaiserslautern
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    The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, hands-on exercises, and more. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, parameters, and performance. You'll find even more resources on the companion website, including sample datasets and code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and ChatGPT), Google (BERT, T5, and Bard), EleutherAI (GPT-J and GPT-Neo), Cohere (the Command family), and Meta (BART and the LLaMA family). Learn key concepts: pre-training, transfer learning, fine-tuning, attention, embeddings, tokenization, and moreUse APIs and Python to fine-tune and customize LLMs for your requirementsBuild a complete neural/semantic information retrieval system and attach to conversational LLMs for retrieval-augmented generationMaster advanced prompt engineering techniques like output structuring, chain-ofthought, and semantic few-shot promptingCustomize LLM embeddings to build a complete recommendation engine from scratch with user dataConstruct and fine-tune multimodal Transformer architectures using opensource LLMsAlign LLMs using Reinforcement Learning from Human and AI Feedback (RLHF/RLAIF)Deploy prompts and custom fine-tuned LLMs to the cloud with scalability and evaluation pipelines in mind "By balancing the potential of both open- and closed-source models, Quick Start Guide to Large Language Models stands as a comprehensive guide to understanding and using LLMs, bridging the gap between theoretical concepts and practical application."--Giada Pistilli, Principal Ethicist at HuggingFace "A refreshing and inspiring resource. Jam-packed with practical guidance and clear explanations that leave you smarter about this incredible new field."--Pete Huang, author of The Neuron Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details

     
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  4. Digital surveillance fiction
    dataveillance in contemporary science fiction
    Autor*in: Krause, Michael
    Erschienen: [2021]
    Verlag:  AVINUS, Hamburg

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  5. Advances in Speech and Language Technologies for Iberian Languages
    Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings
    Beteiligt: Mamede, Nuno (Hrsg.); Teixeira, António (Hrsg.); García Mateo, Carmen (Hrsg.); Batista, Fernando (Hrsg.)
    Erschienen: 2016
    Verlag:  Springer, Cham

    This book constitutes the refereed proceedings of the IberSPEECH 2016 Conference, held in Lisbon, Portugal, in November 2016. The 27 papers presented were carefully reviewed and selected from 48 submissions. The selected articles in this volume are... mehr

    Standort:
    Universität Potsdam, Universitätsbibliothek
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    uneingeschränkte Fernleihe, Kopie und Ausleihe

     

    This book constitutes the refereed proceedings of the IberSPEECH 2016 Conference, held in Lisbon, Portugal, in November 2016. The 27 papers presented were carefully reviewed and selected from 48 submissions. The selected articles in this volume are organized into four different topics: Speech Production, Analysis, Coding and Synthesis; Automatic Speech Recognition; Paralinguistic Speaker Trait Characterization; Speech and Language Technologies in Different Application Fields Speech Production -- Analysis, Coding and Synthesis -- Automatic Speech Recognition -- Paralinguistic Speaker Trait Characterization -- Speech and Language Technologies in Different Application Fields

     
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    Quelle: Verbundkataloge
    Beteiligt: Mamede, Nuno (Hrsg.); Teixeira, António (Hrsg.); García Mateo, Carmen (Hrsg.); Batista, Fernando (Hrsg.)
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9783319491691
    Weitere Identifier:
    Schriftenreihe: Lecture Notes in Computer Science ; 10077
    Lecture Notes in Artificial Intelligence ; 10077
    Array
    Array
    Schlagworte: Computer science; Text processing (Computer science); Computational linguistics; Computer Science; Pattern recognition; Application software; User interfaces (Computer systems); Artificial intelligence; Natural language processing (Computer science).; Human-computer interaction.; Pattern recognition systems.; Digital humanities.
    Umfang: Online-Ressource (XV, 288 p. 53 illus, online resource)
  6. Digital surveillance fiction
    dataveillance in contemporary science fiction
    Autor*in: Krause, Michael
    Erschienen: [2021]; ©2021
    Verlag:  Avinus, Hamburg

    Standort:
    Staatsbibliothek zu Berlin - Preußischer Kulturbesitz, Haus Unter den Linden
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    Standort:
    Europa-Universität Viadrina, Universitätsbibliothek
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    Standort:
    Universität Potsdam, Universitätsbibliothek
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    Quelle: Staatsbibliothek zu Berlin
    Sprache: Englisch
    Medientyp: Dissertation
    ISBN: 9783869381541; 386938154X
    Weitere Identifier:
    9783869381541
    RVK Klassifikation: HU 1691
    Schlagworte: Überwachung <Motiv>; Science-Fiction-Literatur; Neue Medien <Motiv>; Englisch
    Weitere Schlagworte: Eggers, Dave (1970-): The circle; Doctorow, Cory (1971-): Little brother; Gibson, William (1948-): Pattern recognition
    Umfang: 300 Seiten
    Bemerkung(en):

    Dissertation, Universität Potsdam, 2019
  7. Frontiers in handwriting recognition
    18th International Conference, ICFHR 2022, Hyderabad, India, December 4-7, 2022, proceedings
    Beteiligt: Porwal, Utkarsh (HerausgeberIn); Fornes, Alicia (HerausgeberIn); Shafait, Faisal (HerausgeberIn)
    Erschienen: [2022]
    Verlag:  Springer, Cham

    This book constitutes the refereed proceedings of the 18th International Conference on Frontiers in Handwriting Recognition, ICFHR 2022, which took place in Hyderabad, India, during December 4-7, 2022.The 36 full papers and 1 short paper presented in... mehr

    Standort:
    Technische Informationsbibliothek (TIB) / Leibniz-Informationszentrum Technik und Naturwissenschaften und Universitätsbibliothek
    Signatur:
    RN 2835(13639)
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    Standort:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Bibliothek
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    This book constitutes the refereed proceedings of the 18th International Conference on Frontiers in Handwriting Recognition, ICFHR 2022, which took place in Hyderabad, India, during December 4-7, 2022.The 36 full papers and 1 short paper presented in this volume were carefully reviewed and selected from 61 submissions. The contributions were organized in topical sections as follows: Historical Document Processing; Signature Verification and Writer Identification; Symbol and Graphics Recognition; Handwriting Recognition and Understanding; Handwriting Datasets and Synthetic Handwriting Generation; Document Analysis and Processing

     
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    Quelle: Verbundkataloge
    Beteiligt: Porwal, Utkarsh (HerausgeberIn); Fornes, Alicia (HerausgeberIn); Shafait, Faisal (HerausgeberIn)
    Sprache: Englisch
    Medientyp: Konferenzschrift
    Format: Druck
    ISBN: 9783031216473
    Körperschaften/Kongresse: ICFHR, 18. (2022, Hyderabad)
    Schriftenreihe: Lecture notes in computer science ; 13639
    Schlagworte: COMPUTERS / Artificial Intelligence; COMPUTERS / Computer Vision & Pattern Recognition; COMPUTERS / Data Processing / General; COMPUTERS / Data Processing / Speech & Audio Processing; COMPUTERS / Data Processing / Storage & Retrieval; COMPUTERS / Database Management / General; Computer-Anwendungen in den Sozial- und Verhaltenswissenschaften; Data Warehousing; Databases; Datenbanken; Information retrieval; Informationsrückgewinnung, Information Retrieval; Machine learning; Maschinelles Lernen; Mustererkennung; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Pattern recognition; Society & social sciences
    Umfang: xiv, 564 Seiten, Illustrationen
    Bemerkung(en):

    Interessenniveau: 06, Professional and scholarly: For an expert adult audience, including academic research. (06)

    Historical Document Processing.- A Few Shot Multi-Representation Approach for N-gram Spotting in Historical Manuscripts.- Text Edges Guided Network for Historical Document Super Resolution.- CurT: End-to-End Text Line Detection in Historical Documents with Transformers.- Date Recognition in Historical Parish Records.- Improving Isolated Glyph Classification Task for Palm leaf Manuscripts.- Signature Verification and Writer Identification.- Impact of Type of Convolution Operation on Performance of Convolutional Neural Networks for Online Signature Verification.- COMPOSV: Light Weight Online Signature Verification Framework through Compound Feature Extraction and Few-shot Learning.- Finger-Touch Direction Feature Using a Frequency Distribution in the Writer Verification Base on Finger-Writing of a Simple Symbol.- Self-Supervised Vision Transformers with Data Augmentation Strategies using Morphological Operations for Writer Retrieval.- EAU-Net: A New Edge-Attention based U-Net for Nationality Identification.- Progressive Multitask Learning Network for Online Chinese Signature Segmentation and Recognition.- Symbol and Graphics Recognition.- Musigraph: Optical Music Recognition through Object Detection and Graph Neural Network.- Combining CNN and Transformer as Encoder to Improve End-to-end Handwritten Mathematical Expression Recognition Accuracy.- A Vision Transformer based Scene Text Recognizer with Multi-Grained Encoding and Decoding.- Spatial Attention and Syntax Rule Enhanced Tree Decoder for Offline Handwritten Mathematical Expression Recognition.- Handwriting Recognition and Understanding.- FPRNet: End-to-end Full-page Recognition Model for Handwritten Chinese Essay.- Active Transfer Learning for Handwriting Recognition.- Recognition-free Question Answering on Handwritten Document Collections.- Handwriting recognition and automatic scoring for descriptive answers in Japanese language tests.- A Weighted Combination of Semantic and Syntactic Word Image Representations.- Combining Self-Training and Minimal Annotations for Handwritten Word Recognition.- Script-Level Word Sample Augmentation for Few-shot Handwritten Text Recognition.- Towards understanding and improving handwriting with AI.- ChaCo: Character Contrastive Learning for Handwritten Text Recognition.- Enhancing Indic Handwritten Text Recognition using Global Semantic Information.- Yi Characters Online Handwriting Recognition Models Based on Recurrent Neural Network: RnnNet-Yi and ParallelRnnNet-Yi.- Self-Attention Networks for Non-Recurrent Handwritten Text Recognition.- An Efficient Prototype-based Model for Handwritten Text Recognition with Multi-Loss Fusion.- Handwriting Datasets and Synthetic Handwriting Generation.- Urdu Handwritten Ligature Generation using Generative Adversarial Networks (GANs).- SCUT-CAB: A New Benchmark Dataset of Ancient Chinese Books with Complex Layouts for Document Layout Analysis.- A Benchmark Gurmukhi Handwritten Character Dataset: Acquisition, Compilation, and Recognition.- Synthetic Data Generation for Semantic Segmentation of Lecture Videos.- Generating synthetic styled Chu Nom characters.- UOHTD: Urdu Offline Handwritten Text Dataset.- Document Analysis and Processing.- DAZeTD: Deep Analysis of Zones in Torn Documents.- CNN-based Ruled Line Removal in Handwritten Documents.- Complex Table Structure Recognition in the Wild using Transformer and Identity Matrix-based Augmentation.
  8. Perils of Progress-Navigating Dark Sides of AI
    Examining Ethical and Societal Challenges of Autonomous Systems and Intelligent Machines
    Autor*in: Strange, Herman
    Erschienen: 2023
    Verlag:  PN Books, East Grinstead, W.Sussex

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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Druck
    ISBN: 9780611340061
    Schriftenreihe: Rise of Cognitive Computing: AI Evolution from Origins to Adoption
    Schlagworte: COMPUTERS / Computer Vision & Pattern Recognition; COMPUTERS / Natural Language Processing; Computer vision; Maschinelles Sehen, Bildverstehen; Mustererkennung; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Pattern recognition
    Umfang: 96 Seiten
  9. AI for Beginners
    A Practical Guide to Machine Learning
    Autor*in: Maldonado, Alanna
    Erschienen: 2023
    Verlag:  Alanna Maldonado, [Erscheinungsort nicht ermittelbar]

  10. Artificial Intelligence for Beginners
    A Beginner's Guide to Understanding AI and Its Impact on Society (2023 Crash Course)
    Autor*in: Woolery, Nathaniel
    Erschienen: 2023
    Verlag:  Nathaniel Woolery, [Erscheinungsort nicht ermittelbar]

  11. Advances in Speech and Language Technologies for Iberian Languages
    Third International Conference, IberSPEECH 2016, Lisbon, Portugal, November 23-25, 2016, Proceedings
    Beteiligt: Mamede, Nuno (Hrsg.); Teixeira, António (Hrsg.); García Mateo, Carmen (Hrsg.); Batista, Fernando (Hrsg.)
    Erschienen: 2016
    Verlag:  Springer, Cham

    This book constitutes the refereed proceedings of the IberSPEECH 2016 Conference, held in Lisbon, Portugal, in November 2016. The 27 papers presented were carefully reviewed and selected from 48 submissions. The selected articles in this volume are... mehr

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    This book constitutes the refereed proceedings of the IberSPEECH 2016 Conference, held in Lisbon, Portugal, in November 2016. The 27 papers presented were carefully reviewed and selected from 48 submissions. The selected articles in this volume are organized into four different topics: Speech Production, Analysis, Coding and Synthesis; Automatic Speech Recognition; Paralinguistic Speaker Trait Characterization; Speech and Language Technologies in Different Application Fields Speech Production -- Analysis, Coding and Synthesis -- Automatic Speech Recognition -- Paralinguistic Speaker Trait Characterization -- Speech and Language Technologies in Different Application Fields

     
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    Volltext (lizenzpflichtig)
    Quelle: Verbundkataloge
    Beteiligt: Mamede, Nuno (Hrsg.); Teixeira, António (Hrsg.); García Mateo, Carmen (Hrsg.); Batista, Fernando (Hrsg.)
    Sprache: Englisch
    Medientyp: Ebook
    Format: Online
    ISBN: 9783319491691
    Weitere Identifier:
    Schriftenreihe: Lecture Notes in Computer Science ; 10077
    Lecture Notes in Artificial Intelligence ; 10077
    Array
    Array
    Schlagworte: Computer science; Text processing (Computer science); Computational linguistics; Computer Science; Pattern recognition; Application software; User interfaces (Computer systems); Artificial intelligence; Natural language processing (Computer science).; Human-computer interaction.; Pattern recognition systems.; Digital humanities.
    Umfang: Online-Ressource (XV, 288 p. 53 illus, online resource)
  12. 'Careers in Information Technology
    Artificial Intelligence (AI) Robotics Engineer'
    Autor*in: Mukosha, Patrick
    Erschienen: 2024
    Verlag:  Patrick Mukosha, [Erscheinungsort nicht ermittelbar]

  13. LLMS AND GENERATIVE AI FOR HEALTHCARE
    the next frontier
    Autor*in: HOLLEY, KERRIE
    Erschienen: 2024
    Verlag:  O'REILLY MEDIA, [S.l.]

    This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of large language models (LLMs) and generative AI today and in the future, using storytelling and illustrative use cases in healthcare mehr

     

    This practical book shows healthcare leaders, researchers, data scientists, and AI engineers the potential of large language models (LLMs) and generative AI today and in the future, using storytelling and illustrative use cases in healthcare

     
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  14. Artificial Intelligence and Society
    Navigating the Road Ahead
    Autor*in: Sreekumar, V T
    Erschienen: 2024
    Verlag:  Sreekumar V T, [Erscheinungsort nicht ermittelbar]

  15. Deep Learning
    Computer Vision, Python Machine Learning And Neural Networks
    Autor*in: Botwright, Rob
    Erschienen: 2024
    Verlag:  Pastor Publishing Ltd, [Erscheinungsort nicht ermittelbar]

  16. AI for Everyone
    A Non-Technical Introduction to Artificial Intelligence
    Autor*in: Sreekumar, V T
    Erschienen: 2023
    Verlag:  Sreekumar V T, [Erscheinungsort nicht ermittelbar]

  17. Pattern Recognition and Machine Learning
    Exploring the Power of Data Analysis and Prediction through Cutting-Edge Technology
    Autor*in: Williams, Conor
    Erschienen: 2023
    Verlag:  Oleksandr Rumianstev, [Erscheinungsort nicht ermittelbar]

  18. 'Careers in Information Technology
    Machine Learning Engineer'
    Autor*in: Mukosha, Patrick
    Erschienen: 2024
    Verlag:  Patrick Mukosha, [Erscheinungsort nicht ermittelbar]

  19. Quick Start Guide to Large Language Models
    Autor*in: Ozdemir, Sinan
    Erschienen: 2024
    Verlag:  Pearson Education (US), Boston

    The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like Llama 3, Claude 2, and the GPT family are demonstrating breathtaking capabilities, but their size and complexity have deterred many... mehr

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    Technische Universität Bergakademie Freiberg, Bibliothek 'Georgius Agricola'
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    The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like Llama 3, Claude 2, and the GPT family are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, Second Edition, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, hands-on exercises, and more. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, prompting, fine-tuning, performance, and much more. The resources on the companion website include sample datasets and up to date code for working with open and closed source LLMs such as those from OpenAI (GPT-4 and GPT-3.5), Google (BERT, T5, and Gemma), X (Grok), Anthropic (the Claude family), Cohere (the Command family), and Meta (BART and the LLaMA family). Learn key concepts: pre-training, transfer learning, fine-tuning, attention, embeddings, tokenization, and moreUse APIs and Python to fine-tune and customize LLMs for your requirementsBuild a complete neural/semantic information retrieval system and attach to conversational LLMs for building retrieval-augmented generation (RAG) chatbots and AI AgentsMaster advanced prompt engineering techniques like output structuring, chain-of-thought prompting, and semantic few-shot promptingCustomize LLM embeddings to build a complete recommendation engine from scratch with user data that out performs out of the box embeddings from OpenAIConstruct and fine-tune multimodal Transformer architectures from scratch using open source LLMs and large visual datasetsAlign LLMs using Reinforcement Learning from Human and AI Feedback (RLHF/RLAIF) to build conversational agents from open source models like Llama 3Deploy prompts and custom fine-tuned LLMs to the cloud with scalability and evaluation pipelines in mindDiagnose and optimize LLMs for speed, memory, and performance with quantization, probing, benchmarking, and evaluation frameworks

     
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    Quelle: Verbundkataloge
    Sprache: Englisch
    Medientyp: Buch (Monographie)
    Format: Druck
    ISBN: 9780135346563
    Schriftenreihe: Addison-Wesley Data & Analytics Series
    Schlagworte: Artificial intelligence; COMPUTERS / Artificial Intelligence; COMPUTERS / Computer Vision & Pattern Recognition; COMPUTERS / Data Processing / Optical Data Processing; COMPUTERS / Expert Systems; COMPUTERS / Natural Language Processing; COMPUTERS / Programming Languages / General; Computer vision; Expert systems / knowledge-based systems; Künstliche Intelligenz; Maschinelles Sehen, Bildverstehen; Mustererkennung; Natural language & machine translation; Natürliche Sprachen und maschinelle Übersetzung; Pattern recognition; Programmier- und Skriptsprachen, allgemein; Programming & scripting languages: general; Wissensbasierte Systeme, Expertensysteme
    Umfang: 352 Seiten
    Bemerkung(en):

    Foreword to the First EditionPrefaceAcknowledgmentsAbout the Author Part I: Introduction to Large Language ModelsChapter 1: Overview of Large Language ModelsChapter 2: Semantic Search with LLMsChapter 3: First Steps with Prompt EngineeringChapter 4: The AI Ecosystem--Putting the Pieces Together Part II: Getting the Most Out of LLMsChapter 5: Optimizing LLMs with Customized Fine-TuningChapter 6: Advanced Prompt EngineeringChapter 7: Customizing Embeddings and Model ArchitecturesChapter 8: AI Alignment: First Principles Part III: Advanced LLM UsageChapter 9: Moving Beyond Foundation ModelsChapter 10: Advanced Open-Source LLM Fine-TuningChapter 11: Moving LLMs into ProductionChapter 12: Evaluating LLMs Part IV: AppendixesAppendix A: LLM FAQsAppendix B: LLM GlossaryAppendix C: LLM Application Archetypes Index
  20. How to Speak Whale: A Voyage into the Future of Animal Communication
    A Voyage into the Future of Animal Communication
    Autor*in: Mustill, Tom
    Erschienen: 2023
    Verlag:  HarperCollins Publishers, London

    Wildlife filmmaker Tom Mustill had always liked whales. But when one breached onto his kayak, nearly killing him, he became obsessed. This book traces his extraordinary investigation into the deep ocean and the cutting-edge science of animal... mehr

     

    Wildlife filmmaker Tom Mustill had always liked whales. But when one breached onto his kayak, nearly killing him, he became obsessed. This book traces his extraordinary investigation into the deep ocean and the cutting-edge science of animal translation. What would it take to speak with a whale? Are we ready for what they might say? MORE PRAISE FOR HOW TO SPEAK WHALE 'One of the most exciting and hopeful books I have read in ages' SY MONTGOMERY, AUTHOR OF THE SOUL OF AN OCTOPUS 'A narrative that will expand your concept of language and deepen your understanding of the many ways there are to be alive ... It left me inspired' MERLIN SHELDRAKE, AUTHOR OF ENTANGLED LIFE 'A must-read ... a hugely engaging personal story of a journey into the future of human-animal communication facilitated by delving into its past' NEW SCIENTIST 'Fascinating and deeply humane' GRETA THUNBERG 'A rich, enthralling, brilliant book that opens our eyes and ears to worlds we can scarcely imagine' GEORGE MONBIOT, AUTHOR OF REGENESIS 'Tantalizing ... Think how transformative it would be if we could chat with whales about their love lives or their sorrows or their thoughts on the philosophy of language' ELIZABETH KOLBERT, NEW YORKER

     
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  21. Quick start guide to large language models
    strategies and best practices for using ChatGPT and other LLMs
    Autor*in: Ozdemir, Sinan
    Erschienen: [2024]; © 2024
    Verlag:  Addison-Wesley, Hoboken, New Jersey

    The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying... mehr

    Standort:
    Universitätsbibliothek Clausthal
    Signatur:
    2024 A 87
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe

    Standort:
    Staats- und Universitätsbibliothek Hamburg Carl von Ossietzky
    Signatur:
    ST 306 O99 89715
    Fernleihe:
    keine Fernleihe

    Standort:
    Deutsche Universität für Verwaltungswissenschaften Speyer, Universitätsbibliothek
    Signatur:
    D II s 3925
    Fernleihe:
    keine Ausleihe von Bänden, nur Papierkopien werden versandt

    Standort:
    UB Weimar
    Signatur:
    Hp 2400/6
    Fernleihe:
    keine Fernleihe

    Standort:
    Ostfalia Hochschule für angewandte Wissenschaften, Bibliothek
    Signatur:
    IT Dh 014
    Fernleihe:
    uneingeschränkte Fernleihe, Kopie und Ausleihe

     

    The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like ChatGPT are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, hands-on exercises, and more. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, parameters, and performance. You'll find even more resources on the companion website, including sample datasets and code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and ChatGPT), Google (BERT, T5, and Bard), EleutherAI (GPT-J and GPT-Neo), Cohere (the Command family), and Meta (BART and the LLaMA family). Learn key concepts: pre-training, transfer learning, fine-tuning, attention, embeddings, tokenization, and moreUse APIs and Python to fine-tune and customize LLMs for your requirementsBuild a complete neural/semantic information retrieval system and attach to conversational LLMs for retrieval-augmented generationMaster advanced prompt engineering techniques like output structuring, chain-ofthought, and semantic few-shot promptingCustomize LLM embeddings to build a complete recommendation engine from scratch with user dataConstruct and fine-tune multimodal Transformer architectures using opensource LLMsAlign LLMs using Reinforcement Learning from Human and AI Feedback (RLHF/RLAIF)Deploy prompts and custom fine-tuned LLMs to the cloud with scalability and evaluation pipelines in mind "By balancing the potential of both open- and closed-source models, Quick Start Guide to Large Language Models stands as a comprehensive guide to understanding and using LLMs, bridging the gap between theoretical concepts and practical application."--Giada Pistilli, Principal Ethicist at HuggingFace "A refreshing and inspiring resource. Jam-packed with practical guidance and clear explanations that leave you smarter about this incredible new field."--Pete Huang, author of The Neuron Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details

     
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  22. Generative AI on Aws
    Building Context-Aware Multimodal Reasoning Applications
    Autor*in: Fregly, Chris; Barth, Antje; Eigenbrode, Shelbee
    Erschienen: 2023
    Verlag:  O'Reilly Media, Sebastopol

    Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and... mehr

    Standort:
    Universität des Saarlandes, Wirtschaftswissenschaftliche Seminarbibliothek, Betriebswirtschaftliche Abteilung
    Signatur:
    BF-5-831 / MIS
    Fernleihe:
    keine Ausleihe von Bänden, nur Papierkopien werden versandt

     

    Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTSs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images

     
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