1.

Record Nr.

UNINA9911015967503321

Autore

Dhillon Vikram

Titolo

AI Frameworks Enabled by Blockchain : Creating Trustworthy and Responsible AI Using Distributed Ledger Technology / / by Vikram Dhillon, David Metcalf, Max Hooper

Pubbl/distr/stampa

Berkeley, CA : , : Apress : , : Imprint : Apress, , 2025

ISBN

979-88-6881-402-0

Edizione

[1st ed. 2025.]

Descrizione fisica

1 online resource (0 pages)

Altri autori (Persone)

MetcalfDavid

HooperMax

Disciplina

005.74

Soggetti

Blockchains (Databases)

Artificial intelligence

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Introduction -- 1. AI Enabled Blockchain -- 2.Behold the Dreamers -- 3.The Gold Rush: Mining Bitcoin -- 4.Foundations of a blockchain beyond Bitcoin -- 5. Unpacking Ethereum -- 6.Decentralized organizations -- 7. The DAO Hacked -- 8.High-Performance Decentralized Computing -- 9.Blockchain in Funding for Science -- 10.Large Language Multimodesl and Autonomous Agents -- 11.Generative AI in Healthcare -- 12.Technological Revolutions and Financial Capital -- 13.Blockchain-based Consortia as a Service -- 14.Blockchain-based Standards for Healthcare and AI -- 15.Blockchain in Government and Enterprise -- 16.Beyond AI and Blockchain: A roundtable conversation.

Sommario/riassunto

Blockchain technology offers a powerful foundation for building trust, privacy and verifiability into AI frameworks. This book will focus on how a blockchain can enable AI frameworks and applications to scale in a responsible fashion, reshaping the future of numerous industries from financial markets to healthcare and education. You’ll see that in the next wave of AI products, blockchain can provide a “Trust Layer,” a fundamental feature previously only implemented for parties within a blockchain network. The provable consensus algorithms and oracles previously implemented in blockchains can be extended to autonomous agents that are integrated with large language models (LLMs) and future applications. Finally, you’ll learn that safety is a major concern



for practical applications of AI and blockchain can help mitigate threats due to the decentralized nature. As such, there will be significant discourse on how blockchain can provide enhanced security against prompt injections, LLM-hijacking for dangerous information and privacy. These ideas were studied rigorously when large financial institutions were releasing their own blockchains and distributed ledger protocols with a heavy focus privacy. AI is undergoing a Cambrian explosion this year with foundational models emerging for all major domains of study, however, most such models lack the capacity to externally validate for the “correctness” of a fact, or reply made by the LLM. Similarly, there are no definitive methods to distinguish between meaningful insights and hallucination. These challenges remain at the forefront of AI research, and AI Frameworks Enabled by Blockchain aims to translate technical literature into actionable and practical tips for the AI domain.