The mystery behind the disappearance of Malaysia Airline Flight MH370 continues with no closure for the families of 239 people who were on board the jet. On Monday, Malaysia Airline's CEO Peter Bellew told The Australian newspaper that advances in science and technology, including artificial intelligence, can help pinpoint the resting place of the missing jet. The Boeing 777-200 went missing March 8, 2014, while on its way from Kuala Lumpur to Beijing. After over three years of search in a remote part of the southern Indian Ocean where the plane was believed to have crashed, no concrete clues as to what happened to the jet have been yielded. The multimillion-dollar hunt for MH370 was suspended this year after search vessels failed to find it.

Along with other tech trends, Natural Language Processing became another buzzword in the past years. But not everyone really understands what NLP is and how it can be used to improve efficiency of the process and impact your business in a positive way. In this article I will be briefly explaining what natural language processing is, how it is used, a few benefits on-site search get from doing it and I will mention a some cool startups that are doing natural language processing today. Let's start with the basics. Natural language processing (NLP) is the ability of a computer program to understand human speech as it is spoken.

In terms of the future of smart machines, the Internet of Things (IoT), and artificial intelligence (AI), it more or less comes down to "Like It or Not, This Is Happening." The quoted statement is a section in the first chapter of the book What to Do When Machines Do Everything from Cognizant Technology Solutions. "What to Do When Machines Do Everything" offers deep insight on how emerging technologies like artificial intelligence and the Internet of Things will change our labor force and production industries. The authors do not sugar-coat the inevitable future. In chapter one, they state how this next stage of technology and business is the same as what we have experienced in the past.

Recent work in learning ontologies (hierarchical and partially-ordered structures) has leveraged the intrinsic geometry of spaces of learned representations to make predictions that automatically obey complex structural constraints. We explore two extensions of one such model, the order-embedding model for hierarchical relation learning, with an aim towards improved performance on text data for commonsense knowledge representation. Our first model jointly learns ordering relations and non-hierarchical knowledge in the form of raw text. Our second extension exploits the partial order structure of the training data to find long-distance triplet constraints among embeddings which are poorly enforced by the pairwise training procedure. We find that both incorporating free text and augmented training constraints improve over the original order-embedding model and other strong baselines.

Cartman – a budget-priced robot from Australia – has triumphed in an annual contest to create a machine that can identify, pick up and stow warehouse goods. The bot was designed from scratch to take part in 2017's Amazon Robotics Challenge and used a radically different design to past winners.

WASHINGTON – The Florida startup Moon Express is setting its sights high: ambitiously shooting to become the first private company to launch a small, unmanned craft to the moon before the year's out. A big success could pave the way for scheduled flights to deliver scientific and exploration equipment, to exploit lunar soil resources and commercial potential. In a recent interview with AFP, CEO and co-founder Robert Richards acknowledged that it is a "very optimistic date given that the rocket has yet to achieve orbit and given we are still building our vehicle." The race to try this first flight on a tight deadline was motivated at least in part by the $20 million offered by the Google Lunar X-prize in 2007. The condition: be a private entity and launch a craft to the moon's surface by Dec. 31, 2017. Another condition will be, once on the moon, to move the ship or a robot on board, over 500 meters and to transmit a video and photographs back to Earth.

Tokyo-based venture ZMP Inc. may begin field testing a self-driving delivery robot in August intended as an alternative to aerial delivery drones as Japan grapples with a growing labor shortage. The box-shaped CarriRo Delivery robot, which is 133 cm long and 109 cm high, is designed to run on sidewalks and carry loads of up to 100 kg, ZMP said. "Our delivery robot is more suitable than drones when it comes to delivering heavy products like food items," said ZMP Chief Executive Officer Hisashi Taniguchi. The company has teamed up with sushi delivery firm Ride On Express Co. to test a prototype of the autonomous vehicle on private property. The robot, which is equipped with cameras and sensors and can steer itself at a maximum speed of 6 kph, selects delivery routes on its own using a pre-loaded map. It can be controlled remotely when needed, according to ZMP, which is also developing self-driving car technologies.

Read the full ABC article and watch the video interview to learn more about Tanmay and his work in the field of AI. The Australian Broadcasting Corporation (ABC) recently profiled 13-year-old Canadian tech prodigy Tanmay Bakshi who started using computers at age five, launched his first app at age nine, and has been working with IBM's AI and cognitive APIs for a couple of years now. Tanmay is in a different league from the average pre-teen. In 2013, at age nine, he built "tTables," an app to help kids learn multiplication which Apple's App Store accepted after rejecting it three times. An incredible achievement for a child who loves to code but is largely self-taught.

After spending the past few years in Virginia Beach, 2017 RoboBoat changed the scenery. Now in Daytona Beach, Florida, we are excited for new challenges and possibilities for our Teams.

Artificial intelligence (AI) promises to revolutionise our lives, drive our cars, diagnose our health problems, and lead us into a new future where thinking machines do things that we're yet to imagine. Even billionaire entrepreneur Elon Musk, who admits he has access to some of the most cutting-edge AI, said recently that without some regulation "AI is a fundamental risk to the existence of human civilization". So what is the future of AI? Michael Milford and Peter Stratton are both heavily involved in AI research and they have different views on how it will impact on our lives in the future. How widespread is artificial intelligence today? Answering this question depends on what you consider to be "artificial intelligence".