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Artificial Intelligence Education Innovation Network Reading

Latest Read: GANs in Action

GANs in Action: Deep learning with Generative Adversarial Networks by Jakub Langr and Vladimir Bok. Vladimir is a Data Product Manager at Intent. In addition, I really welcome his statement: Why I Donate All of My Book’s Proceeds to Girls Who Code. Jakub is Co-Found of Hypermile, a UK startup deploying AI across transportation solutions.

GANs in Action by Jakub Langr and Vladimir Bok

Jakub and Vladimir have certainly written a wonderful book on machine learning algorithms that generate realistic imaging. However, this book is really intended for readers who already have some experience with machine learning and neural networks.

Whereas many consumers view new imaging services as a kind of magic, super computing power delivered by AI. There are indeed large machine learning datasets in play that even make this imaging possible.

GANs in Action is a very worthy followup to John Kelleher’s Machine Learning, Melanie Mitchell’s excellent book Artificial Intelligence: A Guide for Thinking Humans, and Sean Gerrish’s How Smart Machines Think. Each author is in fact, addressing in various scales, the introduction to Neural Networks and GANs. Thankfully, Jakub and Vladimir have taken the necessary next step in delivering a wonderful introduction and coding deep dive to GANs.

In fact, for many consumers the Grokking series of books are a must read. Grokking Algorithms: An Illustrated Guide For Programmers and Other Curious People by Aditya Bhargava and Grokking Artificial Intelligence Algorithms: Understand and apply the core algorithms of deep learning and artificial intelligence by Rishal Hurbans. Thus, both are wonderfully illustrated books to begin anyone’s journey into understanding Artificial Intelligence, Machine Learning, and Deep Learning.

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Artificial Intelligence Education Innovation Reading

Latest Read: Deep Learning

Deep Learning by John D. Kelleher. John is the Academic Leader of the Information, Communication and Entertainment research institute at the Technological University Dublin. He has previously taught at Dublin City University, Media Lab Europe, and DFKI (the German Centre for Artificial Intelligence Research).

Deep Learning by John D. Kelleher

This is a very good introduction to specific subsets of artificial intelligence that are indeed powering imaging, speech recognition, machine translation, and autonomous cars today.

Consumers may forget as they are engaging various technologies, their interactions are via Deep Learning systems. This includes interactions with Siri on iPhones, and Alexa on all things from Amazon. To a lesser extent is Cortana from Microsoft. Actually, John provides a wonderful glossary. This serves the reader well in helping to further develop their understanding of Deep Learning systems.

Likewise, his introduction illustrates how Deep learning delivers data-driven decisions from very large datasets. The key is Deep Learning deliver immediate ‘learning’ as the large datasets grow.

In addition, his insights on autoencoders, recurrent neural networks, and Generative Adversarial Networks (GAN) are very stimulating. At the same time, addressing gradient descent and especially backpropagation is amazing in of itself.

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Artificial Intelligence Education Reading

Latest Read: The Myth of Artificial Intelligence

The Myth of Artificial Intelligence Why Computers Can’t Think the Way We Do by Erik Larson. Erik is an entrepreneur and former research scientist at the University of Texas at Austin where he focused in machine learning and natural language processing.

The Myth of Artificial Intelligence by Erik Larson

In addition, Erik founded two DARPA-funded AI startups and works on core issues in natural language processing and machine learning. Erik has written for The Atlantic.

Artificial Intelligence seems to be the buzzword of the last twenty years, for better or for worse. For some it is the savior of humanity. For others, the spawn of the devil.

So, does AI actually deliver on superior knowledge systems surpassing human capabilities? Actually, there are valid points by Erik to reveal quite the opposite.

The real challenge proposed by Erik is that so many noted authors on AI, and all their books promising AI’s coming revolution have really all missed their target dates. All of those noted experts made bold predictions to delivery dates of systems that surpass all human knowledge and the downstream effect AI will play upon both markets and society. So why in 2022 have they all missed the mark?

The book is broken into three parts: The Simplified World, the Problems of Inference, and the Future of the Myth. These opening chapters should be considered mandatory reading for every middle school student as Part 1 is certainly well researched. At less than seventy pages, Erik provides a grounded explanation to the early foundation that brought AI forward. From Chapter Two, Turing at Bletchley, to Chapter Five, Natural Language Understanding.

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Artificial Intelligence Education Innovation Reading

Latest Read: AI Ethics

AI Ethics by Mark Coeckelbergh. Mark is Professor of Philosophy of Media and Technology at the University of Vienna.

AI Ethics by Mark Coeckelbergh

In addition, he is the President of the Society for Philosophy and Technology, member of the High Level Expert Group on Artificial Intelligence for the European Commission, member of the Austrian robotics council.

Mark is also a member of the editorial advisory boards of AI and Sustainable Development, The AI Ethics Journal, Cognitive Systems Research, Science and Engineering Ethics, and Journal of Information, Communication and Ethics in Society.

In addition, Mark brings a wealth of ethics experience to address Artificial intelligence (AI). This book is directed at new audiences to AI, showing how there is a real need to understand the impact of bias surrounding these technologies.

One will certainly appreciate Mark’s academic approach to explaining history’s many attempts to create knowledge in various forms. Indeed, Mark creates a good foundation for AI and it’s downstream technologies including Neural Networks, Deep Learning, Machine Learning, and ultimately Trustworthy AI.

Artificial intelligence (AI) is the biggest buzzword in the marketplace today. For those pushing AI-based solutions, we are living in the best time for humanity. However, many even within IT, mathmetmatics, and researchers are able to forecast the worst things possible.

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Blockchain Education Innovation Network Reading Technology Virtual Reality

Latest Read: AI 2041

AI 2041: Ten Visions for Our Future by Kai-Fu Lee and Chen Qiufan. Kai-Fu is a leading AI researcher. with a Ph.D. from Carnegie Mellon University. He landed at Apple in 1990 for a decade, then went to SGI.

AI 2041: Ten Visions for Our Future by Kai-Fu Lee

Kai-Fu has previously served as the founding director of Microsoft Research Asia, then president of Google China, He departed to launch Sinovation Ventures, a venture capital firm in Beijing.

Over the course of my career I have grown rather confident that technology predications never really develop as projected. Hence, AI 2041 is no exception. While I do appreciate Chen’s writing skills, these predications are a real miss on the AI front.

In addition, each story begins with a brief note by Kai-Fu followed by Chen’s story. I must admit that I am certainly not really a fan of fiction, yet the detail writing by Chen is striking. Kai-Fu then closes each story with an accurate analysis of AI technologies key to the story.

Chapter Three: Twin Sparrows

Twin Sparrows, is certainly the best written chapter IMHO. The implementation of natural language processing, self-supervised training, and AI education made for a unique story, although straining at times.