Mainland Chinese start-up Horizon Robotics, founded by the former head of online search giant Baidu's Institute of Deep Learning, claims it is on pace to bring chips with built-in artificial intelligence (AI) technology to market. "General processors are too slow for AI functions. A dedicated chip will dramatically increase the speed of these functions," Yu Kai, the founder and chief executive of Horizon Robotics told the South China Morning Post. Founded in Beijing in July, Horizon Robotics is developing chips and software that attempt to mimic how the human brain solves abstract tasks, such as voice and image recognition, that are difficult for regular computer programmes. It also makes sensors for smart devices.

It's a notion marketers will drool over: Imagine if their overloaded job responsibilities could be wiped clean by the use of robots to do tedious marketing tasks for them. Just as we already use programmatic buying and other data-driven marketing tools to simplify difficult and time-consuming processes, artificial intelligence (AI) is viewed by both robotics experts and marketing professionals as a tool to expedite menial content creation in the future. Efforts to bring AI to the mainstream are underway. IBM's Watson AI is already making appearances in ads holding conversations with celebrities. Robotic writing solutions have been used for simple writing tasks, such as recapping sporting events.

Human patrols serve as the most direct form of protection of endangered animals, especially in large national parks. However, protection agencies have limited resources for patrols. With support from the National Science Foundation (NSF) and the Army Research Office, researchers are using artificial intelligence (AI) and game theory to solve poaching, illegal logging and other problems worldwide, in collaboration with researchers and conservationists in the U.S., Singapore, Netherlands and Malaysia. "In most parks, ranger patrols are poorly planned, reactive rather than pro-active, and habitual," according to Fei Fang, a Ph.D. candidate in the computer science department at the University of Southern California (USC). Fang is part of an NSF-funded team at USC led by Milind Tambe, professor of computer science and industrial and systems engineering and director of the Teamcore Research Group on Agents and Multiagent Systems.

How we explain reality to ourselves is a construction with many parts. We gather knowledge and generate meaning through our experiences and traditions; from what we learn in school, at work and at home; from how we witness others explaining reality for themselves (on TV, via social media, etc). This narrative that we tell ourselves everyday throughout our entire lives largely defines who we are and how we approach the world. The first time I ran (in Mexico) an adaptation of Stanford's workshop "Makers in Residence" (an intensive 80 hour program for high schoolers on digital fabrication and design thinking which was designed by the Transformative Learning Technology Lab) I was shocked by the comments of participants regarding their place in relation to technology. Most participants were impressed that they were "smarter" than the computers they programmed; when I asked them more about it I started understanding the new narrative that a generation of kids growing up surrounded by digital technology are developing in their heads.

One key buzzword these days is "algorithm," which technically means any computational formula but which has come to mean a formula that predicts our behavior. Amazon and Netflix have algorithms that predict what books a user is likely to want to read or what movies and TV shows he or she is likely to want to watch. Facebook has an algorithm that predicts the news a user is likely to want. Dating sites like Match.com and OkCupid use algorithms to predict with whom we would fall in love. Google, with the most famous algorithm of all, predicts what we want when we type a search term.

As the average age of farmers globally creeps higher and retirement looms, Japan has a solution: robots and driver-less tractors. The Group-of-Seven agriculture ministers meet in Japan's northern prefecture of Niigata this weekend for the first time in seven years to discuss how to meet increasing food demand as aging farmers retire without successors. With the average age of Japanese farmers now 67, Agriculture Minister Hiroshi Moriyama will outline his idea of replacing retiring growers with Japanese-developed autonomous tractors and backpack-carried robots. U.S. Agriculture Secretary Tom Vilsack has warned that left unchecked, aging farmers could threaten the ability to produce the food the world needs. The average age of growers in developed countries is now about 60, according to the United Nations.

Big data can't deliver on its potential unless enterprises have the right tools to extract insights. Woodside, an Australia-based oil and gas giant, realizes this and is using advanced machine learning technology to leverage its data via predictive analysis. Front and center in the company's toolkit is IBM Watson, a cutting-edge machine learning and natural language processing platform that analyzes vast amounts of unstructured data. According to CIO, Woodside is using a variety of big data tools -- including Amazon Web Services (AWS), Apache Spark and Watson -- to improve operational efficiency and predict potential catastrophes at its production facilities. Elsa Jordan, principal data scientist at Woodside, told attendees of the Chief Analytics Officer Forum in Sydney how the company has implemented these data science technologies in recent years and how the Watson engine has become a key component of the organization's big data platform.

One week ago, I asked Facebook's Messenger to send me the weather forecast every morning. It has yet to do so. Messenger is supposed to deliver me the weather through a free service called Poncho, one of the first "chat bots" to live inside Facebook's messaging app behemoth. Instead of checking the weather through an app like Dark Sky or even Poncho's own iPhone app, Poncho's playful Messenger bot is designed to chat with me about the weather like a human being. Poncho's bot has not only failed to send me the weather like I asked, but its bot has so far proven to be the most complicated method of getting the weather imaginable.

Research funded by the National Science Foundation may have found an ingenious solution to poaching: applying game theory and computer science to real-life situations. One of the biggest factors in why there are so many endangered animals today is poaching – a centuries-old problem. The dwindling tiger population is one of the most glaring examples of this. Whether for sport, medicine, pelts or other body parts, poaching remains a huge threat to wildlife. Patrols have long been the most direct form of human intervention in wildlife protection.

See Sea Hunter hunt submarines. Was it really only December that DARPA told us it was building a submarine-hunting drone-ship for the Navy? Well, get ready to be surprised. Just four months after we learned of the existence of the Anti-Submarine Warfare Continuous Trail Unmanned Vessel program, or ACTUV, it's already complete -- and afloat. Last week, the Pentagon's mad scientists at the Defense Advanced Research Projects Agency unveiled the ACTUV prototype in Portland, Ore., christening the vessel Sea Hunter.