Tag: deep learning

Categories
Artificial Intelligence Education Innovation Reading

Latest Read: The Deep Learning Revolution

The Deep Learning Revolution by Terrence Sejnowski. He holds both a Masters and PhD in physics from Princeton University. Today he is a professor at The Salk Institute for Biological Studies and directs the Computational Neurobiology Laboratory.

The Deep Learning Revolution by Terrence Sejnowski

He is also Professor of Biological Sciences and Adjunct Professor in the Departments of Neurosciences, Psychology, Cognitive Science, and Computer Science and Engineering at the University of California, San Diego where he is Director of the Institute for Neural Computation.

Terry was an Investigator at the Howard Hughes Medical Institute from 1991 to 2018. In addition, he founded Neural Computation, a journal in neural networks and computational neuroscience published by the MIT Press. He is also the President of the Neural Information Processing Systems Foundation.

In fact, Terry is only one of three living people to have been elected to all four of the national academies: The National Academy of Medicine, Member of the National Academy of Sciences, The National Academy of Engineering and the National Academy of Inventors.

So, Terry is sharing his story how deep learning began and is today used in driverless cars to personal assistants. Deep Learning is changing our lives and transforming the world. Deep learning can play poker better than professional poker players and has also defeated a world champion at Go. It should be noted when Google’s Deep Mind defeated Ke Jie, it served as China’s Sputnik moment.

Continue reading “Latest Read: The Deep Learning Revolution”
Categories
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.

Continue reading “Latest Read: GANs in Action”
Categories
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.

Continue reading “Latest Read: Deep Learning”
Categories
Artificial Intelligence Education Innovation Network Reading Technology

Latest Read: What Algorithms Want

What Algorithms Want: Imagination in the Age of Computing by Ed Finn. Ed is an associate professor at Arizona State University’s School for the Future of Innovation in Society and the School of Arts, Media and Engineering. He also serves as the academic director of Future Tense, a partnership between ASU, New America, and Slate Magazine.

What Algorithms Want: Imagination in the Age of Computing by Ed Finn

I really appreciate reading this book as a follow up to The AI Delusion. What Algorithms Want takes a liberal arts approach. This is very appealing and brings a valued perspective.

Ed is communicating that society innocently believes magical algorithms as a tool to a better life. For this purpose, Ed shares that Eric Schmidt indicated that people do not want Google to just provide search results. Rather, they “want Google to tell them what they should be doing next.” I find this difficult to believe.

However, Ed also is viewing this from a practical perspective. His view is that algorithms are not only for mathematical logic, but rather for philosophy, cybernetics, and creative thinking.

Accordingly, there is a gap that Ed identifies between theoretical ideas and pragmatic instructions. This is a view outside of traditional computer science books.

Clearly, most users are not aware of how Facebook’s timeline and Google search queries are executions that benefit their data collection and profits. Many would not even consider the impact of Facebook’s timeline as nothing more than the latest news from friends, when in reality it is far from that idea.

Machine Learning

What Algorithms Want takes a deeper dive on Google’s efforts to drive profits from the data mining services across every service they deploy. What is also emphasized is the automatic assumptions by society that Google has their own interests protected because of a flimsy “do no evil” pledge.

Continue reading “Latest Read: What Algorithms Want”
Categories
Artificial Intelligence Education Google Innovation Reading Technology

Latest Read: A Brief History of Artificial Intelligence

A Brief History of Artificial Intelligence: What It Is, Where We Are, and Where We Are Going by Michael Wooldridge. Michael is Head of Department of Computer Science and Professor of Computer Science at the University of Oxford.

A Brief History of Artificial Intelligence Michal Wooldridge

Is artificial intelligence intimidating to you? Above all this is a very easy, enjoyable book. So, Michael states in his introduction “I’m writing a popular science introduction to artificial intelligence.”

Accordingly, Michael has researched artificial intelligence for over 30 years. He is focusing on multi-agent systems drawing upon ideas from game theory, logic, computational complexity, and agent-based modeling.

A short history begins with Alan Turing’s work in 1935 at Cambridge during World War II. This is beyond America’s cultural understanding of Turing’s life from the 2014 movie The Imitation Game. Alan Turing actually defined artificial intelligence.

Machine Learning

Chapter 5: Deep Breakthroughs, addresses why Google acquired DeepMind Technologies, a British-based research laboratory in 2014. Founded in September 2010, DeepMind was introducing a term bounced around a lot: Machine Learning.

There is certainly a great misunderstanding regarding machine learning and deep learning. Additionally, Micheal’s efforts are to be complimented in making this topic understandable.

Continue reading “Latest Read: A Brief History of Artificial Intelligence”