A group of Stanford researchers is using satellite imagery and artificial intelligence to track poverty reduction efforts around the world. By combining those satellite images with machine learning -- the ability for machines to learn things without being programmed to -- scientists hope to collect data that could help the U.N. achieve its 2030 goal to eradicate poverty in a cheap and efficient manner. Collecting that data in the past has been difficult for a number of reasons. "Most countries don't collect much data, and scaling up traditional household survey-based data collection efforts would be expensive," Stanford researchers explain in a short video explaining the project. But the researchers suggest that by using "less conventional data sources," such as algorithms and satellite imagery, they can put together an "accurate, inexpensive and scalable method for estimating consumption expenditure and asset wealth."

Machine learning is nipping at the heels of conventional physical modeling of air quality predictions in more and more places. The latest is Johannesburg, South Africa, where computer engineer Tapiwa M. Chiwewe at the newly opened IBM Research lab is adapting IBM's air quality prediction software to local needs and adding new capabilities. The work is an expansion of the so-called Green Horizons initiative, in which IBM researchers partnered with Chinese government researchers and officials, starting two years ago. Last month, Chiwewe presented some of the Johannesburg lab's first results, involving ground-level ozone level predictions, at the 14th International Conference on Industrial Informatics in Poitiers, France. "You can do a lot of physics to understand how ozone is found in different places," he says, "but what we did is we just collected a lot of data and trained these machines on it and they were able to predict [local ozone levels] without any knowledge of how ozone works in the atmosphere."

NAIROBI – Japanese and African leaders on Sunday pledged to fight terrorism and emphasized the importance of rule-based maritime order as they wrapped up a Japan-led international conference on the continent's development. In the Nairobi Declaration adopted at the Tokyo International Conference on African Development (TICAD), the leaders also agreed to promote investment in infrastructure that leads to job creation in the fast-growing region. The sixth TICAD, convened in the Kenyan capital, Nairobi, was held outside Japan for the first time, as Tokyo seeks to strengthen its economic and political presence in the continent amid China's increasing influence. In the declaration, the leaders said they will seek to maintain maritime order based on rules, and strengthen security and safety at sea by international and regional cooperation in accordance with international law. The reference to maritime security comes as tensions remain high in the South China and East China seas amid China's growing assertiveness.

Weather Underground makes weather forecasts based on 8,000 public and 192,000 privately constructed weather stations across 195 countries. The company is adding 400 new stations across Asia, South America, and Africa, and it'll be integrating all of them with IBM's Watson language-learning AI (the one that played Jeopardy! So what exactly does this mean? It is creating a global weather forecast system tied into a number of worldwide businesses, and with that, a hope to outmaneuver one of the most costly, damaging variables in global industry--weather. When IBM bought The Weather Company/WU last October it immediately announced its intention to merge WU's 200,000 weather stations with Watson through the Internet of Things.

A very, very small quadcopter, one inch in diameter can carry a one- or two-gram shaped charge. You can order them from a drone manufacturer in China. You can program the code to say: "Here are thousands of photographs of the kinds of things I want to target." A one-gram shaped charge can punch a hole in nine millimeters of steel, so presumably you can also punch a hole in someone's head. You can fit about three million of those in a semi-tractor-trailer. You can drive up I-95 with three trucks and have 10 million weapons attacking New York City. They don't have to be very effective, only 5 or 10% of them have to find the target. There will be manufacturers producing millions of these weapons that people will be able to buy just like you can buy guns now, except millions of guns don't matter unless you have a million soldiers. You need only three guys to write the program and launch them. So you can just imagine that in many parts of the world humans will be hunted. They will be cowering underground in shelters and devising techniques so that they don't get detected. This is the ever-present cloud of lethal autonomous weapons. Mary Wareham laughs a lot. It usually sounds the same regardless of the circumstance -- like a mirthful giggle the blonde New Zealander can't suppress -- but it bubbles up at the most varied moments. Wareham laughs when things are funny, she laughs when things are awkward, she laughs when she disagrees with you. And she laughs when things are truly unpleasant, like when you're talking to her about how humanity might soon be annihilated by killer robots and the world is doing nothing to stop it. One afternoon this spring at the United Nations in Geneva, I sat behind Wareham in a large wood-paneled, beige-carpeted assembly room that hosted the Convention on Certain Conventional Weapons (CCW), a group of 121 countries that have signed the agreement to restrict weapons that "are considered to cause unnecessary or unjustifiable suffering to combatants or to affect civilians indiscriminately"-- in other words, weapons humanity deems too cruel to use in war. The UN moves at a glacial pace, but the CCW is even worse.

Night lights, therefore, appear to be an incredible resource. So much so that in countries with poor economic statistics, they can serve as a proxy for a regional wealth survey--except no one has to go house to house, running through a questionnaire. Yet research has also shown this not-a-survey will remain inexact: To a satellite at night, a few well-lit mansions and a dense but poorly lit shantytown can look nearly the same. A new paper from a team at Stanford, published last week in Science, applies a trendy technique to this tricky problem. In order to make night lights more discerning, engineers and computer scientists fed a convolutional neural net--a standard type of artificial intelligence program--a series of data sets.

Are we ready for Ultron type intelligence? This is part of our special series on Artificial Intelligence (AI). If you are catching it for the first time I'd recommend that you start here for some instrumental background and here where I start building the bigger idea behind AI. In my high school years, I remember a brilliant classmate, Matthew (not quite his real name), who got the necessary points at Advanced Level to study law at a local university. I was proud to see him not long ago appearing in newspapers as a commanding Intellectual Property (IP) lawyer.

Can we use big data and artificial intelligence to foster future financial success in today's African youth? Having started with a series of surveys to understand practical behaviours throughout one's childhood that correlate with financial success, Yassi currently leads this initiative across Africa focusing on the creation of personalised data-led mechanisms to nurture those behaviours. Embedding new solutions amongst African youth in underprivileged communities, she will monitor whether via data and AI-enabled technologies such as chatbots, one can influence and maintain their existing drive and ambitions throughout their critical adolescent years. SXSW reserves the right to restrict access to or availability of comments related to PanelPicker proposals that it considers objectionable.

Apple wants you to know it already does great AI -- but it's'subtle' South Africa's CLEVVA is making AI-powered virtual advisors a thing Polly.ai

Apple wants you to know it already does great AI -- but it's'subtle' South Africa's CLEVVA is making AI-powered virtual advisors a thing Polly.ai