Our Digital & Social Media Coordinator Lucy Woods speaks with Neil MacDonald who recently joined Speechmatics as Chief Revenue Officer. Having recently announced Speechmatics to feature as a finalist in the Fast and Furious Pitch Off (press release here) at Venturefest East, we wanted to find out more about this rising start-up. Speechmatics is the culmination of 3 decades of advanced Machine Learning and Artificial Intelligence research conducted by our founder Dr Tony Robinson. We apply the latest research in Neural Networks to the task of understanding speech. We provide an automatic speech recognition technology that unlocks the data contained within what we say to each other verbally.

This year's I/O was a big one. Among other things, the Mountain View, California company announced its Daydream VR platform for Android, an evolution of the Google Now assistant in the form of an AI-powered "Google Assistant," a couple of new messaging apps and some hardware to play the part of debuting the Assistant, a new version of Android Wear, and more. The keynote had this overarching theme that Google is no longer just a company that does search and ads. Now, Google is diving head first into artificial intelligence and machine learning, and most of the things that were announced in the keynote fell into that narrative for the most part. This is the stuff that's not coming out for at least half a year.

This year's I/O was a big one. Among other things, the Mountain View, California company announced its Daydream VR platform for Android, an evolution of the Google Now assistant in the form of an AI-powered "Google Assistant," a couple of new messaging apps and some hardware to play the part of debuting the Assistant, a new version of Android Wear, and more. The keynote had this overarching theme that Google is no longer just a company that does search and ads. Now, Google is diving head first into artificial intelligence and machine learning, and most of the things that were announced in the keynote fell into that narrative for the most part. This is the stuff that's not coming out for at least half a year.

Back in 2015, SAP announced Digital Boardroom a solution for simplifying the performance for real-time reports across business areas. The solution, which is built on SAP Analytic Cloud, relies on data from both external sources and the featured S/4HANA platform. In this context, business application journey has not finished yet. SAP CEO Bill McDermontt considers more is coming and released a prediction on the next 5 to 10 years, which will generate a hype around especially on machine learning, artificial intelligence, and augmented reality. Considering the fact S/4HANA platform has already added more than 3200 clients around the world, I believe there is an important market evolution ahead.

Baidu is planning to shift its focus to Artificial Intelligence (AI).(Photo Baidu Inc. is planning to overhaul its business model, shifting from its current search oriented model to one that focuses on'artificial intelligence.' Baidu CEO Li Yanhong said in a company's internal letter on Tuesday that this change will help the company to develop new products in areas such as search, automatic translation, and driverless vehicles. Industry observers say that the shift in business model will likely affect the company's short-term profitability. Li also promised to put more emphasis on user experience and set up a department to weed out any action or behavior that damages its user' experience.

Brian Christian is the author of The Most Human Human, which was named a Wall Street Journal bestseller and a New Yorker favourite book of 2011, and has been translated into ten languages. He is the coauthor, with Tom Griffiths, of Algorithms to Live By, available Spring 2016. The Most Human Human is a provocative, exuberant, and profound exploration of the ways in which computers are reshaping our ideas of what it means to be human. He has just released his latest book, Algorithms to Live By. Co-written with cognitive scientist Tom Griffiths, the book offers a fascinating exploration of how computer algorithms can be applied to our everyday lives, helping to solve common decision-making problems and illuminate the workings of the human mind.

Everywhere you turn these days there are more and more automated processes appearing all the time. From automatic vacuum cleaners to self-order counters at restaurants, to cars that automatically park themselves, robots are all around us in one way or another and physics is no different. In using the latest artificial intelligence to do the same tasks as people, we are not only saving time and money but saving on resources too. A recent physics experiment developed by physicists from The Australian National University (ANU) and the University of New South Wales at the Australian Defence Force Academy (UNSW ADFA) was shown to be completed by artificial intelligence (AI) just as a human would. The test was to create a replica of "Laser Beam" experiment that won the 2001 Nobel Prize and produced an extremely cold gas trapped in a laser beam (known as Bose-Einstein condensate) and the incredible AI literally taught itself how to do the experiment, from start to finish, in under one hour!

Talking about quantum machine learning algorithm is a tricky subject considering the divergent views experts hold on it. Critics consider machine learning to be predominantly a linear algebra subject with little resonance with quantum computing. Proponents comment that the methods of quantum computing can help train datasets that are too large for classical methods. Seth Lloyd of MIT recently gave a talk citing an example. He suggested that analyzing all the topological features for a dataset with 300 300 points will require two to the 300th power processing units, an insolvable computing problem.

At its 10th annual I/O developer conference, Google CEO Sundar Pichai and his lieutenants doubled down on artificial intelligence as the next big phase of computing. Machine learning was a common thread in Google's latest products and launches - Google Home, Google's Assistant, Duo and Allo, and Instant Apps. As the event unfolded, it outlined Pichai's vision of what kind of company Google wants to be. Every decade, a new era of computing arrives that pretty much shapes everything we do. During the event, Pichai noted that saying that Google aims to be more assistive and provide a more ambient experience.

In this example, we will demo how to use MXNet to build an end-to-end deep learning system to help Diagnose Heart Disease. The demo network is able to achieve 0.039222 CRPS on validation set, which is good enough to get Top-10 (on Dec 22nd, 2015). Notice this is a very simple model with no attempt to optimize the structure or hyper parameters, you can build fantastic network based on it. While this tutorial is written in python, mxnet comes with support for other popular languages such as R and Julia which can also be used. You are more than welcomed to try and contribute back to this example.