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Generative AI and LLMs Natural Language Processing and Generative Adversarial Networks - S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 EPUB | MOBI De Gruyter BOOKS
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Generative AI and LLMs Natural Language Processing and Generative Adversarial Networks
Author: S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj
Year: 2024
Pages: 289
Format: EPUB | MOBI
File size: 10.1 MB
Language: ENG



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Book Description: Generative AI and LLMs: Natural Language Processing and Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Summary: In this groundbreaking book, we delve into the fascinating world of Generative Artificial Intelligence (GAI) and Large Language Models (LLM), exploring their evolution, capabilities, and challenges. As we navigate the rapidly evolving landscape of artificial intelligence, it is crucial to understand the development and potential of GAI and LLM to redefine innovation and productivity. However, the integration of these technologies in corporate operations may pose significant risks to data privacy, long-term competitiveness, and environmental sustainability. Introduction: Artificial Intelligence (AI) has come a long way since its inception, with machine learning algorithms driving the current era of innovation. Generative AI and LLMs are at the forefront of this revolution, leveraging pre-existing content to generate novel material. These unsupervised or semisupervised Machine Learning algorithms have the capacity to produce authentic and original content, with no constraints on the quantity of novelty they can generate.
Generative AI and LLMs: Natural Language Processing and Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Резюме: В этой новаторской книге мы углубляемся в увлекательный мир of Generative Artificial Intelligence (GAI) and Large Language Models (LLM), исследуя их эволюцию, возможности и проблемы. Поскольку мы ориентируемся в быстро развивающемся ландшафте искусственного интеллекта, очень важно понимать развитие и потенциал GAI и LLM для переопределения инноваций и производительности. Однако интеграция этих технологий в корпоративные операции может представлять значительные риски для конфиденциальности данных, долгосрочной конкурентоспособности и экологической устойчивости. Введение: Искусственный интеллект (ИИ) прошел долгий путь с момента своего зарождения, алгоритмы машинного обучения определяют нынешнюю эру инноваций. Генерирующие ИИ и LLM находятся на переднем крае этой революции, используя уже существующий контент для создания нового материала. Эти неконтролируемые или полууправляемые алгоритмы машинного обучения способны создавать аутентичный и оригинальный контент без ограничений на количество новизны, которую они могут генерировать.
Generative AI and LLMs : Natural Language Processing and Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Résumé : Dans ce livre novateur, nous nous plongeons dans le monde fascinant de l'Intelligence Artificielle Générative (GAI) et des Grands Modèles Linguistiques (LLM) en explorant leur évolution, leurs possibilités et leurs défis. Alors que nous nous concentrons sur le paysage en évolution rapide de l'intelligence artificielle, il est très important de comprendre le développement et le potentiel de GAI et LLM pour redéfinir l'innovation et la productivité. Toutefois, l'intégration de ces technologies dans les activités des entreprises peut poser des risques importants pour la confidentialité des données, la compétitivité à long terme et la viabilité environnementale. Introduction : L'intelligence artificielle (IA) a parcouru un long chemin depuis sa naissance, les algorithmes d'apprentissage automatique déterminent l'ère actuelle de l'innovation. L'IA génératrice et la LLM sont à la pointe de cette révolution, en utilisant le contenu déjà existant pour créer de nouveaux matériaux. Ces algorithmes d'apprentissage automatique non contrôlés ou semi-contrôlés sont capables de créer des contenus authentiques et originaux sans limitation de la quantité de nouveauté qu'ils peuvent générer.
Generative AI and LLMs: Natural Language Processing and Generative Adversary Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Resumen: En este libro pionero profundizamos en el fascinante mundo de la Inteligencia Artificial Generativa (GAI) y los Modelos de ngua Larga (LLM)), explorando su evolución, oportunidades y desafíos. A medida que nos centramos en un panorama de inteligencia artificial en rápida evolución, es muy importante comprender el desarrollo y el potencial de GAI y LLM para redefinir la innovación y el rendimiento. n embargo, la integración de estas tecnologías en las operaciones de las empresas puede suponer riesgos significativos para la privacidad de los datos, la competitividad a largo plazo y la sostenibilidad ambiental. Introducción: La inteligencia artificial (IA) ha recorrido un largo camino desde su origen, los algoritmos de aprendizaje automático definen la actual era de la innovación. La IA generadora y la LLM están a la vanguardia de esta revolución, utilizando contenidos preexistentes para crear nuevo material. Estos algoritmos de aprendizaje automático incontrolables o semi-controlables son capaces de crear contenidos auténticos y originales sin limitar la cantidad de novedad que pueden generar.
Generative AI and LLMs: Naturale Language Processing and Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Curriculum: In questo libro innovativo, stiamo approfondendo l'affascinante mondo della GAI (Generative Artistical Intelligence) e del Grand Language Models (LLM), esplorandone l'evoluzione, le opportunità e le sfide. Poiché ci concentriamo su un panorama in rapida evoluzione dell'intelligenza artificiale, è fondamentale comprendere lo sviluppo e il potenziale di GAI e LLM per ridefinire l'innovazione e la produttività. Tuttavia, l'integrazione di queste tecnologie nelle operazioni aziendali può comportare rischi significativi per la privacy dei dati, la competitività a lungo termine e la sostenibilità ambientale. Introduzione: l'intelligenza artificiale (IA) ha fatto molta strada dalla sua nascita, gli algoritmi di apprendimento automatico determinano l'era attuale dell'innovazione. I generatori di IA e LLM sono in prima linea in questa rivoluzione, utilizzando i contenuti esistenti per creare nuovo materiale. Questi algoritmi di apprendimento automatico non controllati o semideserti sono in grado di creare contenuti autentici e originali senza limitare la quantità di novità che possono generare.
Generative AI and LLMs: Natural Language Processing and Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Zusammenfassung: In diesem bahnbrechenden Buch tauchen wir in die faszinierende Welt der Generative Artificial Intelligence (GAI) und Large Language Models (LLM) ein und untersuchen deren Entwicklung, Chancen und Herausforderungen. Da wir uns in einer sich schnell entwickelnden KI-Landschaft bewegen, ist es sehr wichtig, die Entwicklung und das Potenzial von GAI und LLM zu verstehen, um Innovation und istung neu zu definieren. Die Integration dieser Technologien in den Unternehmensbetrieb kann jedoch erhebliche Risiken für den Datenschutz, die langfristige Wettbewerbsfähigkeit und die ökologische Nachhaltigkeit mit sich bringen. Einleitung: Künstliche Intelligenz (KI) hat seit ihren Anfängen einen langen Weg zurückgelegt, Algorithmen für maschinelles rnen bestimmen die aktuelle Ära der Innovation. Generierende KI und LLM stehen an der Spitze dieser Revolution und nutzen bereits vorhandene Inhalte, um neues Material zu erstellen. Diese unkontrollierten oder semi-kontrollierten Algorithmen für maschinelles rnen sind in der Lage, authentische und originelle Inhalte zu erstellen, ohne die Menge an Neuheit einzuschränken, die sie generieren können.
Generatywne AI i LLM: Natural Language Processing i Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Streszczenie: W tej przełomowej książce zagłębiamy się w fascynujący świat Generatywnej Sztucznej Inteligencji (GAI) i Dużych Modeli Językowych (LLM), badając ich ewolucję, możliwości i wyzwania. Kiedy poruszamy się po szybko rozwijającym się krajobrazie sztucznej inteligencji, kluczowe znaczenie ma zrozumienie rozwoju i potencjału GAI i LLM w celu przedefiniowania innowacji i wydajności. Włączenie tych technologii do działalności korporacyjnej może jednak stanowić poważne zagrożenie dla prywatności danych, długoterminowej konkurencyjności i zrównoważonego rozwoju środowiska. Wprowadzenie: Sztuczna inteligencja (AI) przeszła długą drogę od początku swojego istnienia, algorytmy uczenia maszynowego definiują obecną erę innowacji. Generowanie AI i LLM są w czołówce tej rewolucji, przy użyciu wcześniej istniejących treści do tworzenia nowego materiału. Te niekontrolowane lub półkontrolowane algorytmy uczenia maszynowego są w stanie produkować autentyczne i oryginalne treści bez ograniczeń co do ilości nowości, jaką mogą wygenerować.
Generative AI and LLMs: Natural Language Processing and Generative Adversarial Networks S. Balasubramaniam, Seifedine Kadry, A. Prasanth, ספר פורץ דרך, אנו מתעמקים בעולם המרתק של אינטליגנציה מלאכותית גנרטיבית (GAI) ומודלים לשוניים גדולים (LLM), בחינת האבולוציה, האפשרויות והאתגרים שלהם. כשאנו מנווטים בנוף הבינה המלאכותית המתפתח במהירות, חיוני להבין את ההתפתחות והפוטנציאל של GAI ו-LLM להגדיר מחדש חדשנות וביצועים. עם זאת, שילוב טכנולוגיות אלה בפעולות ארגוניות עלול להוות סיכונים משמעותיים לפרטיות המידע, לתחרותיות ארוכת טווח ולקיימות סביבתית. מבוא: בינה מלאכותית (AI) עברה דרך ארוכה מאז הקמתה, אלגוריתמי למידת מכונה מגדירים את עידן החדשנות הנוכחי. יצירת AI ו-LLM נמצאים בחזית המהפכה, ומשתמשים בתוכן הקיים מראש ליצירת חומר חדש. אלגוריתמי למידת מכונה בלתי מבוקרים או מבוקרים למחצה מסוגלים לייצר תוכן אותנטי ומקורי ללא הגבלות על כמות החידוש שהם יכולים לייצר.''
Üretken AI ve LLM'ler: Doğal Dil İşleme ve Üretken Düşmanlık Ağları S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 289 De Gruyter Özet: Bu çığır açan kitapta, büyüleyici dünyaya dalıyoruz Üretken Yapay Zeka (GAI) ve Büyük Dil Modelleri (LLM), evrimlerini, olasılıklarını ve zorluklarını araştırıyor. Hızla gelişen AI manzarasında gezinirken, GAI ve LLM'nin inovasyon ve performansı yeniden tanımlamak için gelişimini ve potansiyelini anlamak çok önemlidir. Bununla birlikte, bu teknolojilerin kurumsal operasyonlara entegre edilmesi, veri gizliliği, uzun vadeli rekabet gücü ve çevresel sürdürülebilirlik için önemli riskler oluşturabilir. Yapay zeka (AI) kuruluşundan bu yana uzun bir yol kat etti, makine öğrenme algoritmaları mevcut inovasyon çağını tanımlıyor. AI ve LLM üretmek, yeni malzeme oluşturmak için önceden var olan içeriği kullanarak bu devrimin ön saflarında yer alıyor. Bu kontrolsüz veya yarı kontrollü makine öğrenme algoritmaları, üretebilecekleri yenilik miktarı üzerinde kısıtlama olmaksızın özgün ve orijinal içerik üretme yeteneğine sahiptir.
الذكاء الاصطناعي المولد و LLMs: معالجة اللغة الطبيعية وشبكات الخصومة التوليدية S. Balasubramaniam، Seifedine Kadry، A. Prasanth، Rajesh Kumar Dhanaraj 2024 289 DGGملخص uyter: في هذا الكتاب الرائد، نتعمق في العالم الرائع للذكاء الاصطناعي التوليدي (GAI) ونماذج اللغات الكبيرة (LLM)، لاستكشاف تطورها وإمكانياتها وتحدياتها. بينما نتنقل في مشهد الذكاء الاصطناعي سريع التطور، من الأهمية بمكان فهم تطوير وإمكانات GAI و LLM لإعادة تعريف الابتكار والأداء. ومع ذلك، فإن دمج هذه التكنولوجيات في عمليات الشركات يمكن أن يشكل مخاطر كبيرة على خصوصية البيانات والقدرة التنافسية طويلة الأجل والاستدامة البيئية. مقدمة: لقد قطع الذكاء الاصطناعي (AI) شوطًا طويلاً منذ إنشائه، وتحدد خوارزميات التعلم الآلي العصر الحالي للابتكار. يعد توليد الذكاء الاصطناعي و LLM في طليعة هذه الثورة، باستخدام المحتوى الموجود مسبقًا لإنشاء مواد جديدة. إن خوارزميات التعلم الآلي غير المنضبطة أو شبه المنضبطة هذه قادرة على إنتاج محتوى أصلي وأصلي دون قيود على مقدار الحداثة التي يمكن أن تولدها.
생성 AI 및 LLM: 자연 언어 처리 및 생성 적대적 네트워크 S. Balasubramaniam, Seifedine Kadry, A. Prasanth, Rajesh Kumar Dhanaraj 2024 De Gruyter 요약: 이 획기적인 책에서 우리는 GAI) 및 대형 모델 탐색 진화, 가능성 및 도전. 빠르게 진화하는 AI 환경을 탐색함에 따라 GAI 및 LLM의 개발과 잠재력을 이해하여 혁신과 성능을 재정의하는 것이 중요합니다. 그러나 이러한 기술을 기업 운영에 통합하면 데이터 개인 정보 보호, 장기 경쟁력 및 환경 지속 가능성에 심각한 위험을 초래할 수 있습니다. 소개: 인공 지능 (AI) 은 처음부터 먼 길을 왔습니다. 머신 러닝 알고리즘은 현재 혁신 시대를 정의합니다. 기존 컨텐츠를 사용하여 새로운 자료를 만드는 AI 및 LLM 생성이이 혁명의 최전선에 있습니다. 이러한 제어되지 않거나 반 제어되는 머신 러닝 알고리즘은 생성 할 수있는 참신함의 양에 제한없이 정통 및 독창적 인 컨텐츠를 생성 할 수 있습니다.
Generative AIとLLM:自然言語処理とGenerative Adversarial Networks S。 Balasubramaniam、 Seifedine Kadry、 A。 Prasanth、 Rajesh Kumar Dhanaraj 2024 289 De Gruyter概要:この画期的な本では、GAI (Generative Artificial Intelligence)とLarge Language Models (LLM)の魅力的な世界を掘り下げ、その進化、可能性、課題を探ります。急速に進化するAI環境をナビゲートする際には、GAIとLLMの開発と可能性を理解し、イノベーションとパフォーマンスを再定義することが重要です。しかし、これらの技術を企業の業務に統合することは、データプライバシー、長期的な競争力、環境の持続可能性に大きなリスクをもたらす可能性があります。はじめに:人工知能(AI)は、機械学習アルゴリズムがイノベーションの現在の時代を定義して以来、長い道のりを歩んできました。AIとLLMの生成は、既存のコンテンツを使用して新しい素材を作成する、この革命の最前線にあります。これらの制御されていないまたは半制御の機械学習アルゴリズムは、生成可能な新規性の量を制限することなく、本物のオリジナルのコンテンツを生成することができます。

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