Two telepresence robots roll into a human-computer interaction conference. Sounds like the beginning of a very nerdy joke, but it really happened (#2017). A few weeks ago in Denver, Colorado, a robot I was piloting over the internet from my computer in Idaho stood wheel-to-wheel with a similar'bot in a pink skirt controlled by a researcher in Germany. We introduced ourselves by yelling at each other's screens. Given the topic of the conference, this particular human-computer interaction was a little too on the HD touch-screen nose.

The interdisciplinary field of computational sustainability is using machine learning algorithms to analyse and extract valuable insights from sets of Big Data gathered from environmental fields. It's not just about having large data sets or advanced pattern finding algorithms – it's how we use them. The following projects highlight how Machine Learning and Big Data are helping conservation efforts of all kinds. The ambitious Earthcube project has been in development the past five years and aims to produce a living 3D replica of Earth to serve scientists of different disciplines. It has been built upon interconnected projects that use computer science, big data, and geoscience among various other branches of learning.

This week we find out what's really going on behind the selfie with Gary Willmott and Anton Moulder, co-founders and managing partners of Cape-based digital product studio, Urbian... Inspired by the imagination of children, Net#work BBDO and visual effects and animation agency Sinister Studio applied technology to advertising to create a virtual reality (VR) campaign for Mercedes-Benz South Africa...

Another big part of the food supply comes from ranches and farms that raise and slaughter various livestock. While ranching is sometimes bundled with agriculture, I discussed farming in Big Data in Agriculture, so we'll focus on ranching this time around. Somewhat surprising is that big data usage in ranching appears more limited than in farming. That said, there are a number of novel uses of technology and data in animal husbandry. At a high level, the goals of ranching and farming are the same as any business: increase yields and lower costs. Production maximization has long played a role in large operations.

The global text analytics market size is estimated to grow from $3.97 billion in 2017 to $8.79 billion by 2022, at a Compound Annual Growth Rate (CAGR) of 17.2%. The customer experience management (CEM) is expected to hold the largest market share during the forecast period. Among the various applications in the text analytics market, the CEM application is expected to hold the largest market share during the forecast period. Text mining is the most traditional application in customer service and is frequently utilized to improve customer experience through various information sources. Today, text analytics is implemented to offer quick, computerized feedback to the clients, which significantly reduces dependency on executives for resolving issues.

Together, the last two responses add up to 71 percent of respondents, and Accenture reports that insurers are investing in AI in several areas of the business, including distribution, claims and underwriting. They are looking to empower agents, brokers and employees to enhance the customer experience with automated personalized services, faster claims handling and individual risk-based underwriting processes, Accenture said in a statement. Separately, Carrier Management interviewed representatives of four global insurance groups--XL Catlin, Allianz, QBE and Zurich--who described some of the AI initiatives already underway at their firms. They range from condensing lengthy engineering reports for swifter underwriting, reassigning some of the claims administrative services handled by offshore humans to robots, interpreting crop risk information delivered by drones, and deciphering communications from customers with heavy accents using natural language processing. Also detailed is Zurich's use of a multilingual natural language processing product called Cogito from Expert Systems that mines complicated, voluminous claims data to rapidly provide more refined information to claims adjusters for faster decision-making.

It all started at Baledogle, the old Soviet airport 70 miles northwest of Mogadishu, Somalia's capital, where the U.S. runs a deeply clandestine drone operation with around 30 to 40 American personnel. While shrouded in secrecy, Baledogle has reportedly grown over the years into a key point for training Somali commandos and, early last month, for launching a joint strike against al-Shabab. The radical Islamist group grew out of the splintered factions of Sharia-based courts that filled the vacuum of authority after a U.S.-led coalition withdrew from the country in the early 90s. Today, al-Shabab sees itself as the preeminent terror force in Somalia with global ambitions. "These folks are honing their skills in a local conflict that is part of a global war they are waging against the United States," said Katherine Zimmerman, an expert on Al Qaeda at the American Enterprise Institute. Al-Shabab regularly attacks foreigners, including aid workers and Somalis, as it wages an insurgent fight against the U.S.-leaning government.

The convergence of artificial intelligence (AI) -- machine learning -- increased global mobile connectivity, the Internet of Things, heightened computing power, virtual and augmented reality, and nanotechnology will produce a data tsunami that will require most organizations to transform how they do business. The magnitude of the coming disruption is mindboggling. One major aspect of this disruption will be the impact on employment and the resulting loss of global consumer purchasing power. According to research from the Martin School at Oxford University and Citi published in January 2016, technology has a high probability of automating 57 percent of the jobs in the Organization for Economic Cooperation and Development countries, as compared to 47 percent of the jobs in the United States alone. The corresponding high risk of job automation numbers for China is 77 percent, India is 69 percent, South Africa is 67 percent and Ethiopia is 85 percent.

Advancements in Artificial Intelligence -- the capability of machines to make informed decisions and perform tasks usually reserved for humans -- are moving at a rapid rate, and it's threatening workers from truck drivers to surgeons, according to a new study from the University of Oxford. Spearheaded by Katja Grace of the Future of Humanity Institute at Oxford, the report surveyed more than 350 AI experts on how long it'll take machines to master certain jobs, from remedial to advanced. Within the next decade, experts predict machines will outperform humans when it comes to translating languages, writing a quality high school essay, and driving trucks. AI proficiency in sales and retail is expected by the early 2030s. The essay data is especially intriguing.

In an article published on the CAF website, Rhodri Davies, programme leader at Giving Thought, an in-house think tank at CAF, says that artificial intelligence could help make philanthropy advice a "mass-market commodity" widely available to the public, rather than the preserve of the rich. The article also says artificial intelligence could reduce the cost to charities of giving advice to potential donors, help people choose how to donate and decide what they want to achieve with their donation, and help maximise social outcomes and donor satisfaction. Artificial intelligence could even become a new charitable cause as it becomes more commonplace, a second article by Davies suggests. There are a number of examples of the use of artificial intelligence by charities, including the use of chatbots and personal assistants, it says. For example, it mentions a project in which Arthritis Research UK partnered with Microsoft to pilot a chatbot that can give users tailored advice on arthritis, which Davies says shows how artificial intelligence can help the charity sector.