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Kiran Sreekumar: Data Governance with
Unity Catalog on Databricks

Data Governance with Unity Catalog on Databricks

Implement Data & AI Governance with Databricks Data Intelligence Platform

Quantum Computing and Machine Learning for 6G

Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions-How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.

Decoding Bias, Algorithms, and Trust

Minds, Machines, and Misinformation

Learn how to manage the risks and opportunities of agentic AI with this practical guide to ensuring the safe and beneficial developments of advanced AI systems.

Principles and Responsible Practices

Safer Agentic AI

AI Risk Management: Insights and Approaches to Man age Risks in the Machine Learning Age

Authoritative and comprehensive guide illustrating best practices for designing and building resilient and sustainable smart cities Digital Twins evaluates smart city case studies and insights from the 100 IEEE IoT Global Cities Alliance (GCA) and describes best practices and standards for designing secure architecture using IoT, IoP, and AI. Showcasing success stories while also examining common issues from smart city projects around the world, this guide unpacks lessons learned and identifies where to further integrate standards into city frameworks and processes. Featuring chapters on water, food, energy, mobility, health, waste, education, economies, and work, the environment, social wellbeing, ethics, security, and privacy, the text demonstrates the impact of smart cities on our daily lives. The authors describe the sustainable needs for our next generation and identify the challenges and changes needed to implement smart cities. Readers will learn about Smart City Digital Twins (SCDT), and international Urban Twins (UT), based on architecture, building information modeling (BIM), and big data, which support municipalities to digitally simulate 3D models and create scenarios to test strategies and plans for urban planning, mobility, and disaster management. Other topics covered in Digital Twins include: <ul> <li>Models and open data pertaining to smart city governance, and standard requirements for architectures to integrate IoT solutions in Smart Cities</li> <li>Factors and best practices for different global regions when implementing IoT Solutions and future trends and challenges as areas of opportunity</li> <li>Key discussion points to keep in mind on the digital transformations of cities, such as problem solving in relation to city similarities and differences</li> <li>Snapshots of five cities, covering their approach to becoming a sustainable smart city and undertaking their respective digital transformations</li></ul>Representing the latest developments and future trends of IoT and smart connectivity, Digital Twins is an ideal resource for municipalities and practitioners within the field of smart cities as well as those working more broadly on sustainability and technology who wish to learn about a wealth of topics intersecting with smart cities.

Digital Twins: Making Sense of Smart Cities

Prepare, design and implement a data governance framework that works for your organization with this practical guide to harnessing data successfully.

Design a Framework that Works for Your Organization

Effective Data Governance

Computational Tools for Energy Harvesting Applications presents the latest applications of energy harvesting methods for renewable energy systems. The book provides readers with the computational tools and algorithms for energy harvesting, explaining the mathematical basis behind their development and application and analyzing the latest developments. Each chapter provides a review of the fundamentals and basic theory behind each energy harvester, the working principles, and the latest practical applications. The mathematical techniques and computational tools are provided for response analysis and optimization of diverse energy harvesters, including from fixed renewable energy systems - wind, solar, etc. - and portable devices such as PEM fuel cells. This is a valuable reference for students and researchers working in the field of renewable energy harvesting and its application, as well as electrical and mechanical engineers.

Computational Tools for Energy Harvesting Applications

What is artificial intelligence? How does it work? Can we even trust AI—with computers eventually dominating man—or will it lead us into a dystopian future? You’ll learn about how AI works, its history, the science behind it, the speculative science fiction of this technology, and the very real possibilities it might hold for humanity in this enlightening book!
 
Tackling what has been, what is, and what will be—and the “what ifs”—of AI, Artificial Intelligence: Machine Learning and the Rise of Intelligent Technology sifts through the science, history and pop-culture, exploring thought-provoking ideas as well as mankind’s future. An exhilarating and sometimes troubling read, it looks at whether artificial intelligence is a menace or a boon to humanity. Its investigations include ...
<li>The history, development, impact, and challenges associated with artificial intelligence and superintelligence
</li><li>An easy-to-understand overview of the computing and science concepts behind how machines think and how modern AI works
</li><li>What science fiction got right (and wrong) from Brave New World to Star Trek to WALL-E
</li><li>What happens when AI becomes smarter than humans
</li><li>From utopian visions to apocalyptic concerns, the potential implications of AI for future generations
</li><li>And much, much more.
 
Informative, provocative, and intriguing, Artificial Intelligence: Machine Learning and the Rise of Intelligent Technology looks at this emerging technology and what the past might tell us about the future. With more than 120 photos and graphics, this tome is nicely illustrated. It also includes a helpful bibliography and an extensive index, adding to its usefulness. Ponder the potentials—and the perils—with this in-depth examination of AI!</li>

Will computers come to dominate man? Have films, books, and television foreshadowed the future of artificial intelligence? Will robots enhance or destroy our future? Will AI forever change us? You’ll learn about the history and the pop-culture view of technology—as well as possible futures—in this one-of-a-kind book!

Is technology running amok or is it serving as a helping hand? Artificial Intelligence, Robots, and the Future of Humanity puts a pop-culture and historic spin on some serious questions about mankind’s future. An exhilarating and troubling read, it looks at whether robots are a menace or a boon to humanity. Its investigations include …
<li>The history of robots constructed hundreds of years ago
</li><li>How movies informed the classic image of the robot—and what they got right and wrong
</li><li>Clones, modified humans, cyborgs, designer babies, and half-human robots
</li><li>The sentient internet
</li><li>The advancements in robotics starting in the 1960s
</li><li>Science fiction and science fact—and how science fiction foreshadowed the future
</li><li>Robots replacing people in the workplace
</li><li>The prospect of uploading our minds into computers to ensure immortality
</li><li>Robots becoming indistinguishable from humans
</li><li>Whether robots will rise up and cause humans to become extinct
</li><li>And much, much more.

Exciting and worrisome, Artificial Intelligence, Robots, and the Future of Humanity 
looks at what the past tells us about the future. With more than 120 photos and graphics, this tome is nicely illustrated. It also includes a helpful bibliography and an extensive index, adding to its usefulness. Ponder the possibilities with this examination of robots of the past, present, and future!</li>

Machine Learning and the Rise of Intelligent Technology

Artificial Intelligence

Medical Robots and Devices: New Developments and Advances

Medical Imaging Application in Health Assessment and Disease Management is an all-encompassing book that explores the transformative power of medical imaging in various fields of medicine. It showcases the latest advancements and applications of medical imaging modalities, ranging from neurology and oncology to audiology and osteoporosis. The book highlights the role of medical imaging in understanding and treating neurological conditions, assessing bone health, unraveling hearing disorders, and diagnosing and treating oncological conditions. It also delves into the potential of artificial intelligence and machine learning in improving cancer diagnosis and treatment. The book explores the use of medical imaging in observing mental health conditions such as autism spectrum disorder and stress-related behavioral changes. This comprehensive resource is essential for researchers and professional engineers in the fields of medical image computing/processing, computer science, artificial intelligence, radiology, neuroscience, and biomedical research.

Medical Imaging Application in Health Assessment and Disease Management

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time. Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Observatory is an in-depth beginner’s guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions. You’ll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. You’ll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Meta's and ByteDance's defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, you’ll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, you’ll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface.&nbsp; Along the way, you’ll learn to: <ul><li>Use Python and RabbitMQ to retrieve Telegram data from a remote API</li><li>Store data with PostgreSQL and query it with SQLAlchemy</li><li>Analyze the data you’ve retrieved with Pandas, NetworkX, Gephi, and other tools</li><li>Use state-of-the-art AI tools to transcribe audio and classify text</li><li>Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Let’s Encrypt</li><li>Containerize your apps with Docker and provision infrastructure with Pulumi</li></ul> Whether you’re a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Observatory is an essential blueprint for building your window into online worlds.

Learn to build a web app that can monitor millions of posts across all social media platforms to chart public opinion in real time. Social media has become our modern-day agora, the place where we get our news and engage in political discourse. With disinformation, hate speech, foreign interference, authoritarianism, market monopolization, and political polarization all on the rise, monitoring social media in the public interest has never been so difficult nor so urgent. Social Media Observatory is an in-depth beginner’s guide to coding full-stack web applications in Python to track and analyze social media activity at scale, giving you unparalleled insights into the cultural and political conversations of our time, then empowering you to reach your own conclusions. You’ll start by coding a web app to monitor Russian disinformation channels discussing Ukraine on Telegram, then learn more adversarial methods to scrape the Wayback Machine, Instagram, and TikTok. You’ll detect Twitter bots following Saudi influencers, extract text-embedded URLs to reveal a white supremacist blogosphere, parse archived tweets to reveal the discourse leading up to the January 6 insurrection, and learn to circumvent Meta's and ByteDance's defenses to scrape Instagram and TikTok, collecting evidence of war crimes in the Middle East. Finally, you’ll write an API and deploy your observatory to a cloud server to collaborate with other investigators. By the end of the book, you’ll have a working website that allows collaborators to log in, request data collection, and perform analysis of collected data, via a point-and-click interface.&nbsp; Along the way, you’ll learn to: <ul><li>Use Python and RabbitMQ to retrieve Telegram data from a remote API</li><li>Store data with PostgreSQL and query it with SQLAlchemy</li><li>Analyze the data you’ve retrieved with Pandas, NetworkX, Gephi, and other tools</li><li>Use state-of-the-art AI tools to transcribe audio and classify text</li><li>Deploy a website with an interactive dashboard using FastAPI, Dash, Cytoscape, Uvicorn, Gunicorn, Nginx, AWS, and Let’s Encrypt</li><li>Containerize your apps with Docker and provision infrastructure with Pulumi</li></ul> Whether you’re a citizen scientist, a security researcher, a journalist, an activist, or a scholar, Social Media Observatory is an essential blueprint for building your window into online worlds.

Social Media Observatory

New Directions in Contemporary Art

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual's capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

The field of AI Art is a hotbed for strange, uneasy partnerships between big tech, big art and critical culture. Not since Walter Benjamin's Age of Mechanical Reproduction has there been a similar challenge to humanist art criticism. This book examines how a contemporary critic should best engage with, contextualise and effectively critique machine-learning-based art. In considering this question, Nora Khan looks at the rush of institutions to place AI Art within an art-historical lineage while they simultaneously accept significant funding from technology companies. She discusses the scale and speed at which technological production, machine learning, and AI have abraded the individual’s capacity for critical evaluation, moving us to consider what a shared, collective criticism of AI might sound like.

AI Art, Machine Learning and the Stakes for Art Criticism

Integrating Immersive Technology (AR, VR, MR, XR) in Digital Learning

Data Governance with Unity Catalog on Databricks

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