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.
What You Will Learn
· Bring a layer of accuracy to generative AI where a non-generative component behaves as guardrails
· Protect users from harmful biases as well as hallucinations.
· See how blockchain plays a role in aligning AI with human interests.
· Review use-cases and real-world applications from parties that have invested a significant amount in building technology stacks utilizing both.
Who This Book Is For
Enterprise users and policy makers in the field of Professional and Applied Computing
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Vikram Dhillon is a hematologist in Houston. Prior to this, he was an internal medicine resident at Wayne State University, Detroit Medical Center and a research fellow at the Institute of Simulation and Training, University of Central Florida (UCF). He holds a BSc in molecular biology from the University of Central Florida where his main focus was bioinformatics, a Doctor of Osteopathic Medicine, and a doctoral degree from Nova Southeastern University. He has published multiple scientific papers on computational genomics. He has worked as a software and business development coach at the Blackstone Launchpad to mentor young entrepreneurs and start-ups through the process of building technology products. He was previously funded by the National Science Foundation through the Innovation Corps program to study customer discovery and apply it to commercialize high-risk startup ideas. He is a member of the Linux Foundation and has been involved in open-source projects and initiatives forthe past several years. He often speaks at local conferences and meetups about programming, design, security, and entrepreneurship.
David Metcalf, Director, METIL.org lab at the University of Central Florida’s Institute for Simulation and Training and Managing Director at Global Blockchain Ventures. David is a serial entrepreneur who has launched multiple successful ventures and spinoff companies. He has reviewed thousands of emerging technology companies as an advisor and investor. He is the Director of the Mixed Emerging Technology Integration Lab at UCF’s Institute for Simulation and Training. His past projects involving XR and IoT span across education, health, space, cyber, and transportation. Current efforts include smart cities, blockchain, and enterprise learning transformation for government and industry. He is the co-editor/author of Voice Technology in Healthcare (2020) and Blockchain in Healthcare (2019) as part of the HIMSS Emerging Technology Series, Blockchain Enabled Applications (2018), Connected Health (2017), HIMSS mHealth Innovation (2014), and the HIMSS best-seller mHealth: From Smartphones to Smart Systems (2012).
Max Hooper, Chief Executive Officer of Merging Traffic, is responsible for the company’s management and growth strategy, serving as the corporate liaison to the financial services industry and various capital formation groups. Prior to starting the company, he was co-founder of Equity Broadcasting Corporation (EBC), a media company that owned and operated more than 100 television stations across the United States. He was responsible for activities in the cable, satellite, investment banking, and technology industries, and during his tenure, it grew to become one of the top 10 largest broadcasting companies in the country. He is a lifelong learner and has earned five doctorate degrees: PhD, DMin, PhD, ThD, and DMin from a variety of institutions. Hooper studied financial technology with cohorts at MIT, and cryptocurrency and business disruption with cohorts at the London School of Economics. As an avid runner, he has completed more than 100 marathons and an additional 20 ultra-marathons, which are 50- or 100-mile runs. He has completed the Grand Slam of Ultra Running. He is committed to his family and is a husband, father to five children, and grandfather to seven grandsons. He is active in many organizations and serves on various boards of directors. He works globally with several ministries and nonprofit aid groups and was honored to speak at the United Nations in New York in 2015.
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.
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