Did you know that Artificial Intelligence (AI) will bring us self-driving cars within 5 years and that these cars will simply drop us off at our destination and then go to find a parking spot, without us? Or that an AI start-up in Montreal has developed AI technology that can mimic any voice, after listening to it for just 60 seconds? AI is moving out of laboratories and sci-fi novels and into the realm of ordinary people, and we will live differently because of it – the story of the Internet tells us this. But will we market our products and services differently because of AI? According to research by Demandbase, 80% of marketing executives believe that AI will revolutionize their field by the year 2020.

Robot Academy is an online platform that provides free-to-use undergraduate-level learning resources for robotics and robotic vision. The content was developed for two 6-week Massively Open Online Courses (MOOCs) that Corke taught in 2015 and 2016. This content is now available as individual lessons (over 200 videos, each less than 10 minutes long) or in masterclasses (collections of videos, around 1 hour in duration, previously a MOOC lecture). Unlike a MOOC, all lessons are available all the time. While the content is typically designed for undergraduate-level students, around 20% of the lessons require no more than general knowledge.

The Australian wine industry is turning to artificial intelligence to streamline its manufacturing. South Australian tech firm Ailytic has developed an artificial intelligence (AI) program to significantly increase production efficiency by optimising machine use. It uses an AI technique called'prescriptive analytics' to account for all the variables that go into mass-producing wines such temperature, wine changeover and inventory. The program then creates the best possible operation schedule, allowing companies to save considerable time and money. Ailytic's list of clients includes world-renown wine companies such as Pernod Ricard, Accolade Wines and Treasury Wine Estates.

Identifying and pinpointing potential network failures and performance issues has long been a matter of educated guesswork, but an emerging generation of predictive analytics tools promises to bring greater accuracy to network reliably forecasts, allowing staff to address and remedy specific issues even before they can even begin affecting network operations. Predictive analytics is a game-changer, giving CIOs the ability to literally look into the future. "There is a growing need for networks to adapt to dynamic application demands as well as address dynamically to special events, seasonality and so on," says Diomedes Kastanis, head of technology and innovation for Ericsson. "Although we have a lot of automation systems and rules to manage and operate networks, it still it not enough to cope with the intense changing environment and proactively adapt to changing demands." Predictive analytics incorporating processes such as machine learning (ML) and artificial intelligence (AI) are relatively new concepts to many CIOs.

Immigration from Mexico--both legal and illegal--has been declining for over a decade. 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. "We don't see -- no matter what happens -- that the labor problem will be solved," said Soren Bjorn, president of Driscoll's of the Americas.

Elite sport is now awash with data. As athletes and management look to gain every competitive advantage they possibly can, they are gathering information about all aspects of individual and team performances in booth training and matchplay, as well as a raft of other metrics. The confidence with machine learning often needed to get coaches to the pinnacle of their field means that some are still reluctant to cede ground to algorithms and machines, but inherent prejudices and the fallibility of human memory mean that the brain is an inefficient tool for processing complex information, especially in the time required during sports games. This is especially true for team sports, where they must monitor a number of players at once. Machine Learning can be applied to sports in a range of ways, with data now accessible about almost anything.

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.

A silent communications system in which nonaural carriers, in the very low or very high audio-frequency range or in the adjacent ultrasonic frequency spectrum are amplitude- or frequency-modulated with the desired intelligence and propagated acoustically or vibrationally, for inducement into the brain, typically through the use of loudspeakers, earphones, or piezoelectric transducers. The modulated carriers may be transmitted directly in real time or may be conveniently recorded and stored on mechanical, magnetic, or optical media for delayed or repeated transmission to the listener.

Australian law explicitly allows computers to make important decisions previously made by the ministers or staff of at least 11 federal government departments. This has been going on since at least 2001, well before the age of algorithms, and yet there remains little clarity about exactly what decisions are being entrusted to the computers. As best we can tell, the first legislation allowing computers to automatically make important decisions with real impact on people's lives was the Social Security (Administration) Act -- which also happens to be the critical piece of legislation that allowed the most high-profile and controversial automated government program so far, Centrelink's'robodebt' endeavour. The legislation giving computers decision-making power over social security is very short and, as these things go, easy to understand. It was introduced in 2001 along with a slew of other provisions around debt recovery.

So far, the company has completed two acquisitions, relocated its headquarters to Melbourne, and is now in the process of expanding its cognitive computing and machine learning footprint. Mark Armstrong, vice president and managing director of international operations for APJ and EMEA, for Progress, discusses the company's mission to democratise data science and make technologies such as machine learning, predictive maintenance and Artificial Intelligence more accessible so businesses in Australia and New Zealand can succeed. One of the reasons for our success in the region is the strong collaboration with our local channel partners. We have a strong partner program, and our A/NZ partners have delivered incredible value to the Progress' ecosystem in the past year. Actually just last May, three of our Australian partners were awarded by Progress' Global Partner Awards, amongst the 18 winners across 10 countries.