In the past decade, we have seen remarkable breakthroughs in the areas of machine and deep learning, and their applications in a wide range of tasks, from image classification & video processing to speech recognition & natural language understanding. The data in these tasks are typically represented in the Euclidean space (i.e. they follow the rules of Euclidean geometry, e.g. the shortest distance between two points is a straight line). However, there are a number of applications where data are generated from non-Euclidean domains and are best represented as graphs with complex relationships (e.g. client accounts in a bank, interactions between these accounts, and the inflow and outflow of assets from these accounts). Consequently, many studies on extending deep learning techniques for graph data have emerged. There are indications that these emerging techniques perform significantly better than traditional methods on non-Euclidean data (e.g. rules based or statistical approach). Given their relevance to areas such as prevention of money laundering and financial crime, in this post, I have provided links to a couple of introductory talks on this topic. Enjoy!
Millennials are a unique generation caught in a faltering global economic system that has already peaked productivity and taken us to the precipice of climate change. They are in despair as their values are not represented in the economy or governance. A seismic shift in the world economy is also underway. According to author and futurist, Jeremy Rifkin, we are in the final phases of the fossil fuel era. Much as coal and steam powered the First Industrial Revolution, and oil and telephony powered the Second Industrial Revolution, clean energy and digital technologies are now converging toward what he describes as the Third Industrial Revolution. This next phase of infrastructure modernisation is rooted in the convergence of 5G, a renewable energy Internet (clean technologies and smart grids), and a digitised mobility and logistics platform (autonomous electric vehicles, artificial intelligence, and the Internet-of-Things).
I no longer read the Economist. I just listen to it – thanks to the Economist audio edition! It almost feels like I am listening to a radio station with some of the finest handpicked playlists, but without any of the usual baloney. It is also convenient, and saves me time. And that’s exactly why Voice is going to be the next big thing. In not so distant future, Google searching or texting by typing will be an obsolete concept. Instead, we will be talking and listening to intelligent devices and apps. What will then become of the businesses built on making us “read and see” stuff displayed on every possible corners of our screen? Who will be the winners and losers? And will we sacrifice some of our privacy for convenience and time? If you would like to explore these thoughts, listen to this fascinating and inspirational talk by Gary Vaynerchuk.
“Success in creating effective A.I.,” said the late Stephen Hawking, “could be the biggest event in the history of our civilization. Or the worst. We just don’t know.” Are we creating the instruments of our own destruction or exciting tools for our future survival? Once we teach a machine to learn on its own – as the programmers behind AlphaGo have done, to wondrous results – where do we draw moral and computational lines? In this video, leading specialists in A.I., neuroscience, and philosophy tackle the very questions that may define the future of humanity.
AI is the future – but what will that future look like? Will superhuman intelligence be our slave, or become our god? Taking us to the heart of the latest thinking about AI, Max Tegmark, author of the book “Life 3.0 – Being Human in the Age of Artificial Intelligence” and the MIT professor whose work has helped mainstream research on how to keep AI beneficial, separates myths from reality, utopias from dystopias, to explore the next phase of our existence. How can we grow our prosperity through automation, without leaving people lacking income or purpose? How can we ensure that future AI systems do what we want without crashing, malfunctioning or getting hacked? Should we fear an arms race in lethal autonomous weapons? Will AI help life flourish as never before, or will machines eventually outsmart us at all tasks, and even, perhaps, replace us altogether?
Whether you get a job or a mortgage, who you date or where you eat – algorithms increasingly determine the big and small decisions in our lives. We may not be aware, but behind the scenes, many companies, and increasingly governments too, are using or plan to use algorithms to automate bureaucratic processes and business decisions. Because algorithms are faster and more efficient than people. But do they always make better decisions? Can algorithms be misused for monetary gains at the cost of others? With these questions in mind, this article explores the darker side of black box algorithms that we as a society must address as our lives become increasingly intertwined with modern digital technologies.
What are Chatbots? Where did they come from? What are they good for? And of course the million dollar question – how do you monetise Chatbots and conversational products? Let’s explore!
2019 is the year 5G is stated to become a reality. 5G or the fifth generation mobile internet is not your traditional network. Rather it is a network that is optimised for connected and intelligent machines, with the capacity to support devices ranging from gigabits per second data needs to the ones with multi-year battery life. Software, connectivity and digitalisation are reshaping both industries and society at an ever increasing pace, and 5G is a going to be a strong catalyst. With that in mind, this article explores what a 5G powered world of automation might look like.
We live in an age of rapid technological advances where artificial intelligence is a reality, not a science fiction. Every day we rely on algorithms to communicate, do our banking online, book a holiday – even introduce us to potential partners. Driverless cars and robots may be the headline makers, but artificial intelligence is being used for everything from diagnosing illnesses to helping police predict crime hot spots. As machines become more advanced, how does society keep pace when deciding the ethics and regulations governing technology? To address this question, this article explores the ethical dilemma surrounding the use of artificial intelligence and autonomous technology.
Some of the world’s largest carmakers see autonomous driving and the shared economy as potential game changers for the automotive industry. And as a result, the automotive industry is at an arms race to create fully driverless vehicles. But are we ready for the ride? To address this question, this article explores the current state of play of fully autonomous vehicles and what a driverless world could look like.