Incredible drone footage shows a great white shark stalking surfers in Australia. The video shows the shark chasing a surfer off the coastal town of Ballina, New South Wales. Apparently unaware of the predator, the surfer catches a wave and speeds away from the shark. Abandoning its initial pursuit, the shark shifts its attention to another surfer. The second surfer, who is dangling their legs in the water, also appears unaware of the great white's hulking presence.

Yojee (ASX:YOJ) has released its artificial intelligence (AI) backed fleet management software in South East Asia and Australia. The company is positioning itself as a leader in'plug in and play', semi-autonomous logistics management software. Yojee has bolstered its AI capabilities by introducing an intelligent context sensitive interface, enhancing the efficiencies in fleet management. A context sensitive interface reduces the time and difficulty in navigating through complex software and enables users to solve almost any problem with just a couple of clicks. World Economic Forum (WEF) data forecasts a US$810-billion upside for data driven logistics information services.

I went to my neighbor's house for something to eat yesterday. It's pretty simple--English speakers would know precisely what it means. But what does it actually tell you--or, more to the point, what does it not tell you? It doesn't specify facts like the subject's gender or the neighbor's, or what direction the speaker traveled, or the nature of the neighbors' relationship, or whether the food was just a cookie or a complex curry. English doesn't require speakers to give any of that information, but if the sentence were in French, say, the gender of every person involved would be specified.

Artificial intelligence ( AI) is the latest buzz word of the tech industry, with smart algorithms powering your personal assistants and recommending which TV shows to binge on next. And now, AI is getting ready to make music: Brisbane, Australia-based digital music startup Popgun wants to use machine learning to figure out which music is trending on services like Apple Music and Spotify - and then train algorithms to write songs that the users of these services may also like. Popgun is just one of eleven music startups that are part of the inaugural Techstars Music class, a new program run by tech incubator Techstars that gives participating companies $120,000 launch capital as well as a three-month incubation program hosted in Los Angeles. Others include Hurdl, a Nashville-based startup that wants to incorporate wireless LED bracelets into live concerts; Jaak, a London-based startup that is building a rights management system based on the same technology as the crypto-currency Bitcoin; Weav, a new York-based company that is developing generative music for fitness studios that's timed to your heartbeat; and Pippa, a New York-based startup that is working on dynamic ad insertion for podcasts. Techstars Music is being led by Bob "Moz" Moczydlowsky, who previously headed Twitter's music efforts.

Partial Least Squares (PLS) methods have been heavily exploited to analyse the association between two blocs of data. These powerful approaches can be applied to data sets where the number of variables is greater than the number of observations and in presence of high collinearity between variables. Different sparse versions of PLS have been developed to integrate multiple data sets while simultaneously selecting the contributing variables. Sparse modelling is a key factor in obtaining better estimators and identifying associations between multiple data sets. The cornerstone of the sparsity version of PLS methods is the link between the SVD of a matrix (constructed from deflated versions of the original matrices of data) and least squares minimisation in linear regression. We present here an accurate description of the most popular PLS methods, alongside their mathematical proofs. A unified algorithm is proposed to perform all four types of PLS including their regularised versions. Various approaches to decrease the computation time are offered, and we show how the whole procedure can be scalable to big data sets.

The most successful artificial intelligence (AI) systems will be those comprising an emotional intelligence almost indistinguishable from human-to-human interaction, according to Bronwyn van der Merwe, group director at Fjord Australia and New Zealand -- Accenture Interactive's design and innovation arm. While the concept of AI is not new, in 2017 van der Merwe expects emotional intelligence to emerge as the driving force behind what she called the next generation in AI, as humans will be drawn to human-like interaction. As businesses continue to experiment with the Internet of Things, interesting use cases are emerging. Here are some of the most common ways IoT is deployed in the enterprise. Speaking with ZDNet, van der Merwe explained that building on the first phase of AI technology, emotional intelligence enhances AI's ability to understand emotional input, and continually adapt to and learn from information to provide human-like responses in real time.

Building neural networks models and implementing learning consist of lots of math this might be boring. Herein, some tools help researchers to build network easily. Thus, a researcher who knows the basic concept of neural networks can build a model without applying any math formula. So, Weka is one of the most common machine learning tool for machine learning studies. It is a java-based API developed by Waikato University, New Zealand.

The Pacific Ocean might be hiding a whole other continent, Bill Gates wants to tax the robots, and some other robots crash in the midst of a road race. A pretty thrilling Monday morning, we'd say. Funds could help humans find new work when automation takes over. How would you deal with the likelihood that robots and automation will lead to many people losing their jobs? For Microsoft co-founder Bill Gates, the answer is straightforward: tax the robots.

Big Data - The ability to capture and process large amounts of data in real time will enhance companies' ability to gain better insights as well as predict customer behaviours. Censors can help understand and respond to customers' reactions in real time. Data scientists will become an in-demand profession! Robots - Software robots will be providing first line customer service and support, not only reducing costs for companies but delivering a better service by continuously learning and getting better through AI, and allowing real agents to focus on the more complex problems. VR & AR - Virtual and mixed reality [Augmented Reality] provide new exciting opportunities.

This kind of question has been on IQ tests for years and the answer, it turns out, depends a good deal on which era you live in. Back in the down-home, cotton-spinning, 19th century you'd be right in thinking you use dogs to hunt rabbits. Shift forward to the glass-fronted skyscrapers of the 20th century Information Age and there was a new right answer; they are both mammals. But, as humans leapfrog into the 21st century of Artificial Intelligence (AI), robots and machine learning, is there an even newer answer? And if so, what is it?