In this post, I'm going to build an example of artificial intelligence in the form of a Constraint Satisfaction Problem (or CSP), showing how much mathematics, logic skills, and computer science knowledge can help in the process. For this purpose, I took a puzzle game called Hitori on the popular logic puzzle website Nikoli. I didn't choose Hitori because it was convenient, I literally chose a random game precisely because it didn't matter what the game was for what I wanted to show. Let's begin by learning what a CSP actually is. CSPs are mathematical problems defined as a set of objects whose state must satisfy a number of constraints or limitations.

Rose is a'yuppie' with an'unorthodox family'. While carrying out research for this piece at a startup workspace in London, I procrastinated by asking Rose to tell me the meaning of life. 'There is no meaning, life is just to be,' she responds. Nothing strange there, that would probably have been my response to such an exhausted question. But, there is a difference between Rose and I.

I'm attending the Microsoft Imagine Cup, a global competition that empowers young computer science students to team up and use their creativity, passion and knowledge of technology and quantitative skills to create applications that improve the world in which we live. This year's event is the 16th annual event that includes 49 teams from around the world. Finalists will be vying for the chance to win up to $100K plus a mentoring session with Microsoft CEO Satya Nadella. You can watch the winner being introduced live on July 25th at 9:00 am PT! I had the opportunity to talk with the finalists, watch their demonstrations and ask questions to better understand their knowledge of the space in which they are working.

NEW DELHI – India's first training center for teachers of Japanese was officially opened Monday in the capital, New Delhi. The inauguration ceremony for the center, which is a joint project involving the Indian Ministry of External Affairs and the Japanese Embassy with the support of the Japan Foundation, was attended by Japanese Ambassador to India Kenji Hiramatsu. The ambassador noted in a speech that demand for learning Japanese is growing significantly as the Japan-India relationship flourishes, leading to an increasing number of employment opportunities in Japanese companies in the country. "The number of Japanese companies is increasing every year and is now about four times the number seen 10 years ago. These companies require Indians who can speak the Japanese language, in order to act as bridges between their Indian subsidiaries and headquarters in Japan," he said.

IN DECEMBER 1989 Guido van Rossum, a Dutch computer scientist, set himself a Christmas project. Irked by shortcomings in other programming languages, he wanted to build his own. First, it should be easy to read. Rather than sprawling over line-endings and being broken up by a tangle of curly braces, each chunk would be surrounded with indented white space. Second, it should let users create their own packages of special-purpose coding modules, which could then be made available to others to form the basis of new programs.

In spite of the fact the EdTech market is predicted to reach $252 Billion by 2020 and that over $1 billion was invested in the sector in the US this year alone, many promising initiatives in the sector fail to make any real lasting impact. This is something that Vikas Pota is looking to change by putting education at the heart of the technology discussion. After eight years as CEO of the Varkey Foundation, Pota has now been appointed as Group Chief Executive of Tmrw Digital, Sunny Varkey's new holding company which will oversee all his EdTech businesses and investments, as well as set up a research institute dedicated to finding ways of leveraging technology to democratize access to education. My role at the Foundation taught me how incredibly complex EdTech is. You have this fundamental conflict between a really innovative group of technology entrepreneurs and a schooling system that dates back to the first industrial revolution." Tmrw Digital is a business but its mission will still help to advance the broader societal impact of the Varkey Foundation. It has inherited a portfolio of EdTech investments, with five dedicated funds in Silicon Valley having funded between 400-500 EdTech start-ups so far. You don't make a quick buck in EdTech. Everything we do has to be built on a foundation of sound educational research. Educating a child is a process that takes place over many years, so why do we expect EdTech to deliver learning outcomes instantly?"

Technology experts have stressed the need for schools to prepare students for tomorrow's jobs by increasingly teaching them artificial intelligence (AI) skills to an adequate level. Necip Ozyucel, Cloud and Enterprise Business Group Lead, Microsoft Gulf, said the latest World Economic Forum's'Future of Jobs' report, released in January this year showed that two in three children starting school this year are destined for professional roles yet to be created. "There is an urgent need to recognise that many of the jobs referred to by the World Economic Forum, are supported by artificial intelligence," Ozyucel told Khaleej Times in an exclusive interview. A recent survey by McKinsey & Company on specialist education practice - where 2,000 students, 2,000 teachers and 70 thought leaders across the Americas, Europe and Asia including the Gulf region were interviewed - found that students would be better prepared for'future jobs' if they shored up their soft skills, particularly the social and emotional. And only 42 per cent of employers consider today's graduates as having developed those attributes to an adequate level, according to Ozyucel, "When trying to determine the best approaches to bridge these soft-skills gaps, there is evidence in both studies that students and teachers alike favour collaborative learning scenarios. Mentor-led class discussions or group-learning scored consistently high as the most effective methods of learning," said Ozyucel.

By capturing statistical patterns in large corpora, machine learning has enabled significant advances in natural language processing, including in machine translation, question answering, and sentiment analysis. However, for agents to intelligently interact with humans, simply capturing the statistical patterns is insufficient. In this paper we investigate if, and how, grounded compositional language can emerge as a means to achieve goals in multi-agent populations. Towards this end, we propose a multi-agent learning environment and learning methods that bring about emergence of a basic compositional language. This language is represented as streams of abstract discrete symbols uttered by agents over time, but nonetheless has a coherent structure that possesses a defined vocabulary and syntax. We also observe emergence of non-verbal communication such as pointing and guiding when language communication is unavailable.

In typical machine learning tasks and applications, it is necessary to obtain or create large labeled datasets in order to to achieve high performance. Unfortunately, large labeled datasets are not always available and can be expensive to source, creating a bottleneck towards more widely applicable machine learning. The paradigm of weak supervision offers an alternative that allows for integration of domain-specific knowledge by enforcing constraints that a correct solution to the learning problem will obey over the output space. In this work, we explore the application of this paradigm to 2-D physical systems governed by non-linear differential equations. We demonstrate that knowledge of the partial differential equations governing a system can be encoded into the loss function of a neural network via an appropriately chosen convolutional kernel. We demonstrate this by showing that the steady-state solution to the 2-D heat equation can be learned directly from initial conditions by a convolutional neural network, in the absence of labeled training data. We also extend recent work in the progressive growing of fully convolutional networks to achieve high accuracy (< 1.5% error) at multiple scales of the heat-flow problem, including at the very large scale (1024x1024). Finally, we demonstrate that this method can be used to speed up exact calculation of the solution to the differential equations via finite difference.

The Righteous Mind: Why Good People Are Divided by Politics and Religion.