Top 10 of 2019: AI and Deep Learning Content Recommended by Experts

How often do you have the time to pick up a book, or listen to a podcast whilst giving it your complete undivided attention? The summer is definitely that time of year when you’ve got a little more time on your hands to relax in the sun, and make the most of those long evenings to get stuck into a new book. This summer we’ve had some great conversations with experts in our AU and Deep Learning community about some of their favourites, as well as videos, podcasts and research papers…there’s enough to keep you going through the summer and beyond, into the chillier evenings.

As part of our Summer Series of blog posts, we’ve put together a list of some of our favourite pieces of content we’ve been recommended this year.

1.Behave: The Biology of Humans at Our Best and Worst, Book, Recommended by Deborah Harrison, Microsoft

“Whilst this isn’t entirely AI specific, this book explores why humans act as they do, relative to how we think and act as we do, which I think is incredibly important in artificial intelligence.” — Deborah Harrison

Why do we do the things we do? Over a decade in the making, this game-changing book is Robert Sapolsky’s genre-shattering attempt to answer that question as fully as perhaps only he could, looking at it from every angle. Sapolsky’s storytelling concept is delightful but it also has a powerful intrinsic logic: he starts by looking at the factors that bear on a person’s reaction in the precise moment a behavior occurs, and then hops back in time from there, in stages, ultimately ending up at the deep history of our species and its genetic inheritance.

2. Ethically Aligned Design, White Paper, Recommended by John C Havens, IEEE Global Initiative on Ethics

“The most comprehensive, crowd-sourced, globl treatise regarding the ethics of autonomous and intelligent systems available today.”

It is time to move “From Principles to Practice” in society regarding the governance of emerging autonomous and intelligent systems. The implementation of ethical principles must be validated by dependable applications of A/IS in practice, and here are three ways you can start that process in your life and work. The IEEE Global Initiative on Ethics of Autonomous and Intelligent Systems (The IEEE Global Initiative) has launched Ethically Aligned Design: A Vision for Prioritizing Human Well-being with Autonomous and Intelligent Systems, First Edition (EAD1e), the most comprehensive, crowd-sourced global treatise regarding the Ethics of Autonomous and Intelligent Systems available today.

3. The Local Maximum, Podcast, Recommended by Neal Lathia, Monzo

Join Max Sklar and guests in this podcast about AI, technology, and society to get stuck into the trending topics and current news in the space. Each episode focuses on a different topic with a new guest, covering topics such as transfer learning, machine learning and NLP, and delving into behind the scenes elements of some of the leading AI companies such as Facebook and Google. Recent episodes include ‘Bitcoin and Google Invade Politics’, ‘The Market Loves You: Jeffrey Tucker on the nature of Innovation’, and ‘Talking Python with Michael Kennedy’.

4. Self-Attention: A Better Building Block for Sentiment Analysis Neural Network Classifiers, Journal, Recommended by Emiliano Martinez Sanchez, BBVA

Sentiment Analysis has seen much progress in the past two decades. For the past few years, neural network approaches, primarily RNNs and CNNs, have been the most successful for this task. Recently, a new category of neural networks, self-attention networks (SANs), have been created which utilizes the attention mechanism as the basic building block. Self-attention networks have been shown to be effective for sequence modeling tasks, while having no recurrence or convolutions. In this work we explore the effectiveness of the SANs for sentiment analysis. We demonstrate that SANs are superior in performance to their RNN and CNN counterparts by comparing their classification accuracy on six datasets as well as their model characteristics such as training speed and memory consumption. Finally, we explore the effects of various SAN modifications such as multi-head attention as well as two methods of incorporating sequence position information into SANs.

5. Montreal AI Ethics, Blog, Recommended by Abhishek Gupta, MAIEI & Microsoft

One of our favourite reads on this blog this summer is ‘Social Robotics and EMpathy: the Harmful Effects of Always Getting What We Want’, written by Camylle Lantegine. The post asserts that social robots and empathizing with social robots may negatively affect our ability to empathize with other humans. An important feature of the 21st century so far seems to be the increasing personalization and individualization of numerous facets of life as we know it. One area where this has arisen is with news outlets. On the one hand, the number of sources from which one can get their news, and the relative diversity of the positions one might encounter, are tremendously greater than a few decades ago — and this is good, to the extent that an aggregate of different views is often more accurate than a one-sided story. On the other hand, things are not so simple. While there are more voices, individuals still prefer the ones that fit their own pre-existing beliefs best.

6. AI for Social Good, White Paper, a RE•WORK Publication

With the rapid advancements and applications of AI, conversations have increased around the intentions of this technology. There are concerns that AI could be used with malicious intent rather than for the benefit of human-kind. This paper explores areas where artificial intelligence can benefit society and tackle global challenges such as the environment, education, healthcare and sustainability. Topics including Global AI Inititiaves, the Challenges of AI, Benefits of AI for Social Good, the Future of AI for Good are covered, as well as case studies from Google, Intuitive AI and GoodAI. Additional expert contributors include Shell, WeWork, XPRIZE, University of Waterloo, MIT-IBM Watson AI Lab and more.

7. An AI Glossary, Blog, Recommended by Andrew Barber, Chief Technical Officer at CoachConnector and CEO at G2L

The term “artificial intelligence” may sound new and futuristic, but it was actually coined back in 1956 for a tech conference at Dartmouth College. Since then, the A.I. field has progressed in fits and starts as new hardware, software and ideas slowly propelled it forward. The current boom started in 2012, when a team of researchers used an artificial neural network in an image recognition competition that showed what A.I. could do with faster computer chips and bigger data sets. The last six years have witnessed breakthroughs in everything from self-driving cars to algorithms that can detect diseases, and social networks like Twitter that rely on A.I. to determine what content appears on our feeds. Take a look at some of the most common terms and their definitions.

8. Technology and the Virtues, Book, Recommended by Marc Steen, Senior Research Scientist at TNO: Human-Centered Design

The 21st century offers a dizzying array of new technological developments: robots smart enough to take white collar jobs, social media tools that manage our most important relationships, ordinary objects that track, record, analyze and share every detail of our daily lives, and biomedical techniques with the potential to transform and enhance human minds and bodies to an unprecedented degree.

9. How to Develop Your Own AI Playbook with Andrew Ng, Video, Recommended by Christopher Lund, CVP of Ag Products, Climate AI

Andrew Ng, in discussion with MIT Technology Review’s Will Knight, closes EmTech Digital with advice on how to chart your own path forward in the AI Era. Dr. Andrew Ng is the founder and CEO of Landing AI and and a general partner at AI Fund. As the former chief scientist at Baidu and the founding lead of Google Brain, he led the AI transformation of two of the world’s leading technology companies. A longtime advocate of accessible education, Dr. Ng is the cofounder of Coursera and founder of, an AI education platform. He is also an adjunct professor in Stanford University’s computer science department.

10. How to Enjoy the Driving Experience, Risk-Free, Blog, Recommended by Nikita Johnson, CEO of RE•WORK

Is there a way to get the best of both worlds? Meaning, you get the experience of driving while dealing, risk-free, with the distractions. Imagine you have a sentient being in the car that detects when you’re distracted and alerts you, or better yet, takes over the auto-drive feature as soon as you become distracted. In contrast to Einstein’s thought experiments on special and general relativity, our thought experiment is easily realized using computer vision and deep learning technologies.

What have you come across this summer that you’ve particularly enjoyed reading, watching, or listening to? Let us know!

Here are a few more pieces we’ve particularly enjoyed:

Making Sense with Sam Harris #138 — The Edge of Humanity, Podcast

“They touch on automation and other issues related to the future of humanity and computing. I know Sam Harris can be a controversial figure — I certainly disagree with him often — but I think the talk is tremendously fascinating.” — Deborah Harrison, Microsoft

Graph Neural Networks: A Review of Methods and Applications, Aricle

“A great review of graphical neural networks — one which I think many people interested in the topic would find very useful.” — Emiliano Martinez Sanchez

“I hope that POET will inspire a new push towards open-ended discovery across many domains, where algorithms like POET can blaze a trail through their interesting possible manifestations and solutions.” — Jeff Clune



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