Category: Artificial Intelligence

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Artificial Intelligence Education Reading

Latest Read: The Alignment Problem

The Alignment Problem: Machine Learning and Human Values by Brian Christian.

The Alignment Problem: Machine Learning and Human Values by Brian Christian

Brian holds a BA in Computer Science and Philosophy from Brown University. And holds an MFA in Poetry from the University of Washington. He is a visiting scholar at the University of California, Berkeley. His focus is cognitive science and human-compatible AI.

He received the Eric and Wendy Schmidt Award for Excellence in Science Communication for his work on The Alignment Problem. Yes, I fully agree this is a wonderful book to read.

His previous books include The Most Human Human and Algorithms to Live By. Both address AI technology and the human experience. When AI services (ChatGPT, CoPilot, Dalle 3, etc.) attempt to execute tasks that result in errors, ethical and potential risks emerge. So, researchers call this the alignment problem.

At the book’s core, Brian is examining ethical and safety issues as machine learning technologies are both advancing into society more rapidly than projected. Perhaps the key element is the ability for machine learning services to execute tasks on behalf of humans across almost every aspect of our lives. This also markets from education, retail, supply chain, and energy to name just a few.

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Artificial Intelligence Education Innovation Reading

Latest Read: Superintelligence

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom.

Superintelligence: Paths, Dangers, Strategies by Nick Bostrom

Nick holds an MA in Philosophy and Physics from Stockholm University, an MSc in Computational Neuroscience from King’s College London, and a PhD in Philosophy from the London School of Economics.

He remains a Professor at Oxford University where he serves as the founding Director of the Future of Humanity Institute. He is a former lecturer at Yale University and British Academy Postdoctoral Fellow at Oxford.

Nick has been recognized as one of the most respected philosophers about AI safety and ethics. As a result, “Superintelligence” has been noted as a critical read for anyone to understand AI systems development.

We should not be surprised to see a respected Philosopher ask: what happens when machines surpass humans in general intelligence? With so many question surrounding this issue, he addresses a foundation for understanding our future and intelligent life. I found this book extremely fascinating.

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Artificial Intelligence Education Innovation Reading

Latest Read: The Human Cloud

The Human Cloud: How Today’s Changemakers Use Artificial Intelligence and the Freelance Economy to Transform Work by Matthew Mottola and Matthew Douglas Coatney.

The Human Cloud: How Today’s Changemakers Use Artificial Intelligence and the Freelance Economy to Transform Work by Matthew Mottola and Matthew Douglas Coatney

Matthew Mottola holds an MBA from Babson College. He is Co-Founder and CEO of The Human Cloud. He is a visiting Lecturer at the Georgia Institute of Technology College of Business. Matthew Douglas Coatney holds a Master of Science from Ohio State University. He is CIO and Thomson Hine.

Together, Mottola and Coatney are providing a good overview of how AI and the freelance economy are reshaping work dynamics. In fact, readers across the country and the world will understand one case studies as a global brand from Milwaukee Wisconsin. This organization has indeed adjusted to the new freelance economy. When this occurs in your own backyard, you’ll understand why.

You must understand that the true power of AI to alter work has yet to hit its full stride. If you’re not aware how this will certainly impact you, then you may indeed get run over. I’m not kidding and Mottola and Coatney are beginning to lay the foundation for what is coming.

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Artificial Intelligence Education Reading

Latest Read: Managing Machine Learning Projects

Managing Machine Learning Projects: From design to deployment by Simon Thompson.

Managing Machine Learning Projects: From design to deployment by Simon Thompson

Simon holds a Phd in Philosophy from the University of Oxford UK. His is the former Director of AI research at BT Labs. Today he serves as the Head of Data Science at GFT Technologies.

Simon is revealing that managing ML projects to production can seem like navigating uncharted waters.

By revealing the challenges of accounting for large data resources to tracking multiple models, machine learning has very different requirements when compared to building traditional software applications. Simon does acknowledge this challenge and asks readers to execute this on a more even scale.

Managing Machine Learning Projects is an end-to-end guide for delivering ML applications on time and under budget. Simon is revealing the tools, approaches, and processes designed to handle the challenges of machine learning project management. To help readers Simon is deploying a full case study.

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Artificial Intelligence Education Reading

Latest Read: Understanding Large Language Models

Understanding Large Language Models: Learning Their Underlying Concepts and Technologies by Thimira Amaratunga.

Understanding Large Language Models: Learning Their Underlying Concepts and Technologies by Thimira Amaratunga

Thimira holds a MS in Computer Science from the University of Colombo. A long time senior software architect at Pearson, today he is a software engineer at CloudMarc and even holds patents related to dynamic neural networks and online learning semantics.

This book is teaching underlying concepts of Large Language Models (LLMs). Thimira begins by introducing ChatGPT, and how it links to LLMs. Readers will next learn about Natural Language Processing (NLP) which led to the development of LLMs.

Thimira is striving to tackle some rather complex concepts regarding LLMs and is presenting them to readers in such a manner that is easier to understand. He is also providing insights into architecture, functions, and applications.

For more mature programmers, the book is aiming to provide a thorough understanding of LLMs in order to inspire them to implement these models in their projects.

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