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".

If you're a content creator, you're not just striving to do your best work. You want to make your best work better. At the SIGGRAPH conference, which runs July 31-Aug. From Siri to Smart Cars to Netflix recommendations, AI is infused in our daily lives. Now, thanks to the computational power of NVIDIA GPUs, new AI accelerated workflows are optimizing content creation, saving artists and studios time and money, and driving greater creativity.

Tesla announced it will livestream the deliveries of the first Model 3 cars this Friday. You'll be able to watch Elon Musk's company hand over its Model 3 sedan to new owners. Earlier this month, Musk tweeted Tesla would hold a "party for first 30 customers" on July 28. The event should put Tesla fans at ease, since the company's second car, the Model X, was delayed by more than a year. It should especially be a relief for the others who have already reserved a car and are expecting to have it delivered next year.

In biological research machine learning algorithms are part of nearly every analytical process. They are used to identify new insights into biological phenomena, interpret data, provide molecular diagnosis for diseases and develop personalized medicine that will enable future treatments of diseases. In this paper we (1) illustrate the importance of machine learning in the analysis of large scale sequencing data, (2) present an illustrative standardized workflow of the analysis process, (3) perform a Differential Expression (DE) analysis of a publicly available RNA sequencing (RNA-Seq) data set to demonstrate the capabilities of various algorithms at each step of the workflow, and (4) show a machine learning solution in improving the computing time, storage requirements, and minimize utilization of computer memory in analyses of RNA-Seq datasets. The source code of the analysis pipeline and associated scripts are presented in the paper appendix to allow replication of experiments.

We present an interactive version of an evidence-driven state-merging (EDSM) algorithm for learning variants of finite state automata. Learning these automata often amounts to recovering or reverse engineering the model generating the data despite noisy, incomplete, or imperfectly sampled data sources rather than optimizing a purely numeric target function. Domain expertise and human knowledge about the target domain can guide this process, and typically is captured in parameter settings. Often, domain expertise is subconscious and not expressed explicitly. Directly interacting with the learning algorithm makes it easier to utilize this knowledge effectively.

Driscoll's is so secretive about its robotic strawberry picker it won't let photographers within telephoto range of it. But if you do get a peek, you won't see anything humanoid or space-aged. AgroBot is still more John Deere than C-3PO -- a boxy contraption moving in fits and starts, with its computer-driven sensors, graspers and cutters missing 1 in 3 berries. Such has been the progress of ag-tech in California, where despite the adoption of drones, iPhone apps and satellite-driven sensors, the hand and knife still harvest the bulk of more than 200 crops. Now, the $47-billion agriculture industry is trying to bring technological innovation up to warp speed before it runs out of low-wage immigrant workers.