Hillary Clinton told federal agents and prosecutors that she did not recall receiving any emails that were too secretive to be handled by her private computer server and did not believe any of her devices had been hacked or compromised, according to FBI records released Friday. The former secretary of State reiterated earlier comments that she decided to use a single private email address to send personal and work correspondence as "a matter of convenience" and was not seeking to avoid having to comply with open records laws, according to an FBI summary of a three-hour interview with agents and prosecutors on July 2. The Democratic presidential nominee added that she relied on her staff -- three of her closest aides were responsible for the vast majority of her work-related correspondence -- and career diplomats to filter out secret information before it reached her unclassified email account. She pushed back when pressed by agents about specific emails containing classified material, saying she was not concerned that the information was sensitive or should have been deemed classified. During its investigation, the FBI determined that 110 emails contained material that should have been sent only on a classified system, even though they was not marked as such at the time. Another three emails included markings to indicate they contained classified information.

Sequential planning portfolios are very powerful in exploiting the complementary strength of different automated planners. The main challenge of a portfolio planner is to define which base planners to run, to assign the running time for each planner and to decide in what order they should be carried out to optimize a planning metric. Portfolio configurations are usually derived empirically from training benchmarks and remain fixed for an evaluation phase. In this work, we create a per-instance configurable portfolio, which is able to adapt itself to every planning task. The proposed system pre-selects a group of candidate planners using a Pareto-dominance filtering approach and then it decides which planners to include and the time assigned according to predictive models. These models estimate whether a base planner will be able to solve the given problem and, if so, how long it will take. We define different portfolio strategies to combine the knowledge generated by the models. The experimental evaluation shows that the resulting portfolios provide an improvement when compared with non-informed strategies. One of the proposed portfolios was the winner of the Sequential Satisficing Track of the International Planning Competition held in 2014.

Startupbootcamp InsurTech has announced that the FastTrack tour will be coming to Cape Town on 11 October and Johannesburg on 13 October 2016. Exponential Ventures, the innovation unit of JSE listed financial services group, MMI Holdings, partners with Europe's leading accelerator programme to showcase South Africa's entrepreneurial talent in the global market FastTracks are open to innovative early stage startups specialising in insurance related areas: virtual and augmented reality; Blockchain; artificial intelligence and machine learning; Internet of Things and wearables; drones and robots; cyber security; data analysis and big data; life science and genome; MedTech and digital health; and customer experience. Exponential Ventures, the disruptive innovation unit of JSE listed company, MMI Holdings, has continued with its relentless pursuit of innovation by becoming an investor partner in the insurance incubator programme, Startupbootcamp InsurTech managed by Startupbootcamp a leading international startup accelerator. Startupbootcamp InsurTech has announced that the FastTrack tour will be coming to Cape Town on 11 October and Johannesburg on 13 October 2016. FastTrack days (or pitch days) are sessions where startups are given an opportunity to present their insurance related business idea to the Startupbootcamp InsurTech team and industry experts.

A new technique using artificial intelligence to read satellite images could aid efforts to eradicate global poverty by indicating where help is needed most, a team of U.S. researchers say. The method would assist governments and charities trying to fight poverty but lacking precise and reliable information on where poor people are living and what they need, the researchers based at Stanford University in California said. Eradicating extreme poverty, measured as people living on less than 1.25 a day, by 2030 is among the sustainable development goals adopted by United Nations member states last year. A team of computer scientists and satellite experts created a self-updating world map to locate poverty, said Marshall Burke, assistant professor in Stanford's Department of Earth System Science. It uses a computer algorithm that recognizes signs of poverty through a process called machine learning, a type of artificial intelligence, he said.

NAIROBI – Japanese and African leaders on Sunday pledged to fight terrorism and emphasized the importance of rules-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. "Japan's public and private sectors will offer cooperation for the development that is led by Africa itself," Prime Minister Shinzo Abe told a news conference after wrap-up of the sixth TICAD, convened in the Kenyan capital of Nairobi. Kenyan President Uhuru Kenyatta told the same news conference that Japan does not press its own views on the continent and continues to be a force for African development. The triennial conference 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.

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.