In the age of artificial intelligence, where vast oceans of data are generated every second, the ability to extract meaningful insights, reason over complex relationships, and deliver contextually accurate responses has become the defining challenge of our time. Large language models (LLMs) such as GPT-4, Claude, and Grok have revolutionized natural language understanding and generation, enabling machines to converse fluently, summarize documents, write code, and even compose poetry. Yet, beneath their impressive fluency lies a critical limitation: these models are fundamentally statistical engines trained on patterns in text, not on structured, verifiable truth.
They excel at prediction but falter at consistency, often producing plausible-sounding but factually incorrect statements—a phenomenon known as hallucination. This gap between linguistic proficiency and factual reliability has created an urgent need for a new paradigm in AI architecture, one that marries the expressive power of neural networks with the logical rigor of symbolic reasoning. At the center of this paradigm shift stands the knowledge graph.
"Sinopsis" puede pertenecer a otra edición de este libro.
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: New. Nº de ref. del artículo: 51860108-n
Cantidad disponible: Más de 20 disponibles
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Paperback. Condición: new. Paperback. In the age of artificial intelligence, where vast oceans of data are generated every second, the ability to extract meaningful insights, reason over complex relationships, and deliver contextually accurate responses has become the defining challenge of our time. Large language models (LLMs) such as GPT-4, Claude, and Grok have revolutionized natural language understanding and generation, enabling machines to converse fluently, summarize documents, write code, and even compose poetry. Yet, beneath their impressive fluency lies a critical limitation: these models are fundamentally statistical engines trained on patterns in text, not on structured, verifiable truth. They excel at prediction but falter at consistency, often producing plausible-sounding but factually incorrect statements-a phenomenon known as hallucination. This gap between linguistic proficiency and factual reliability has created an urgent need for a new paradigm in AI architecture, one that marries the expressive power of neural networks with the logical rigor of symbolic reasoning. At the center of this paradigm shift stands the knowledge graph. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798272001252
Cantidad disponible: 1 disponibles
Librería: California Books, Miami, FL, Estados Unidos de America
Condición: New. Print on Demand. Nº de ref. del artículo: I-9798272001252
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 51860108
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store US, Wood Dale, IL, Estados Unidos de America
PAP. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L0-9798272001252
Cantidad disponible: Más de 20 disponibles
Librería: PBShop.store UK, Fairford, GLOS, Reino Unido
PAP. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Nº de ref. del artículo: L0-9798272001252
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: New. Nº de ref. del artículo: 51860108-n
Cantidad disponible: Más de 20 disponibles
Librería: GreatBookPricesUK, Woodford Green, Reino Unido
Condición: As New. Unread book in perfect condition. Nº de ref. del artículo: 51860108
Cantidad disponible: Más de 20 disponibles
Librería: CitiRetail, Stevenage, Reino Unido
Paperback. Condición: new. Paperback. In the age of artificial intelligence, where vast oceans of data are generated every second, the ability to extract meaningful insights, reason over complex relationships, and deliver contextually accurate responses has become the defining challenge of our time. Large language models (LLMs) such as GPT-4, Claude, and Grok have revolutionized natural language understanding and generation, enabling machines to converse fluently, summarize documents, write code, and even compose poetry. Yet, beneath their impressive fluency lies a critical limitation: these models are fundamentally statistical engines trained on patterns in text, not on structured, verifiable truth. They excel at prediction but falter at consistency, often producing plausible-sounding but factually incorrect statements-a phenomenon known as hallucination. This gap between linguistic proficiency and factual reliability has created an urgent need for a new paradigm in AI architecture, one that marries the expressive power of neural networks with the logical rigor of symbolic reasoning. At the center of this paradigm shift stands the knowledge graph. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798272001252
Cantidad disponible: 1 disponibles