Stockspot founder and CEO Chris Bryci says since the launch of the robo-advice service he founded in 2014, response from the public has been positive. "Professional financial advice is expensive and many Australians are locked out of the market for personalised investment advice due to the high costs involved," Bryci says. While younger people aged between 18-35 are typically the first to embrace online businesses and technology, Bryci has seen an increase in the number of older Australians giving the service a go. Robo-advisers such as Stockspot are opening the doors to a wider range of investors by using algorithms to plan and manage investment portfolios. This results in an automated process, which reduces the cost of seeking financial advice.

Intel's RealSense platform was the star of its Intel Developer's Forum conference in San Francisco last month and it seems the company is only looking to grow the scale and capabilities of its computer vision tech. Today, the company announced that it is acquiring the computer vision startup behind Google's Project Tango 3D-sensor tech, Movidius. In a blog post, Movidius CEO Remi El-Ouazzane announced that his startup will continue in its goal of giving "the power of sight to machines" as it works with Intel's RealSense technology. Movidius has seen a great deal of interest in its radically low-powered computer vision chipset, signing deals with major device makers, including Google, Lenovo and DJI. The eight-year old company has about 180 employees with offices in Silicon Valley, Ireland and Romania.

Did you ever think you'd live in a world where the foxiest job title was "Data Scientist," people who build "models" all day? Well, Weird Science has come to pass. This is our new and very exciting reality. Knowledge and experiences are wrapped together for a new set of challenges, from data scientist to developer to marketers. Last year's news that Google was using a new machine learning tool called RankBrain -- used to contribute to its search engine results -- caused a kerfuffle in the SEO world, leaving us wondering just what kind of impact it would have.

It might surprise some of you to know that artificial intelligence (AI) is already in use and a routine part of our daily lives, but we leverage this technology when we use our smartphones or other devices to ask Apple's Siri, Microsoft's Cortana, Google Now, or Amazon's Alexa a question to get the facts or data we are looking for. Using your voice, you can say, "Where's the nearest gas station?" or "What's on my calendar today?", and the intelligent personal assistant (IPA) will respond by finding information and relaying it from your phone or sending commands to other apps. However, AI is not only being used in the context of a personal assistant. Self-driving cars are moving closer to reality, retailers are using anticipatory shipping in the hopes to send you items before you need them, and banks are using AI to detect fraud to monitor accounts and alert the owners when questionable transactions occur. So it is here, but what is AI? AI is an intelligent system's ability to improve predictions, accelerate problem solving, and automate administrative tasks, ushering in an era of automation.

Mizuho Bank and Softbank Group Corp. on Thursday agreed to set up a 50-50 joint company to provide loans to consumers using artificial intelligence technology. Using customers' business histories with both firms for credit screening, the new firm will provide an innovative, attractive loan service through low-cost operations without outlets, Mizuho Bank and Softbank said. Capitalized at 5 billion, the new company will be established in November. Its operations are seen starting in the first half of 2017. Inc., the parent of Mizuho Bank, and Softbank President Masayoshi Son announced the launch of the new company at a press conference in Tokyo.

Drago? Gavrilu? is an antimalware research manager at Bitdefender, managing a team of 80 people that develops heuristic detections, cloud-based services, system testing services, disinfection routines, Android and iOS analysis, event correlation algorithms, data mining, IoT and cybersecurity analysis. He is also a lecturer at the Alexandru Ioan Cuza University of Ia?i, where he received his Ph.D. in 2012. He received his B.Sc. and M.Sc. in computer science from the same university.

I'm experimenting with Layer Normalization on recurrent neural networks (GRUs) and I've noticed that the gradient tends to behave erratically. I've applied gradient norm clipping, but even with that every few updates I get some NaN in the gradient, which I "fix" by throwing the gradient away for that update and shrinking the parameters (that is, instead of updating with the true loss gradient I update with a L2 regularization gradient). Ultimately, the optimization process still makes progress, but I'm wondering if I'm losing some performance because of this issue. Is there any way to mitigate it?

Machine learning has had fruitful applications in finance well before the advent of mobile banking apps, proficient chat bots, or search engines. Given high volume, accurate historical records, and quantitative nature of the finance world, few industries are better suited for artificial intelligence. There are more uses cases of machine learning in finance than ever before, a trend perpetuated by more accessible computing power and more accessible machine learning tools (such as Google's Tensorflow). Today, machine learning has come to play an integral role in many phases of the financial ecosystem, from approving loans, to managing assets, to assessing risks. Yet, few technically-savvy professionals have an accurate view of just how many ways machine learning finds its way into their daily financial lives.

One of the first questions I have asked no one in particular is: what will change when artificial intelligence is part of the fabric of day to day life? It sounds like a simple question, but it had a logical fallacy in that for the last 30 years, artificial intelligence (AI) projects were science experiments with high expectations and low delivery rates. The AI systems of the past were nowhere near as commonplace as the possibilities that were presented to us. We weren't even nearing the feats of the "The Engine," described in Jonathan Swift's Gulliver's Travels almost 300 years ago. "at a reasonable charge, and with a little bodily labour, might write books in philosophy, poetry, politics, laws, mathematics, and theology, without the least assistance from genius or study." Although Swift may have been skewering purposeless-science, The Engine actually sounds pretty useful right now.

Mondly, the second-largest free language app available, teaches 33 languages and has been downloaded over ten million times. The developers have made this app even better by creating a new voice Chatbot that makes learning easier through the use of proprietary technology. The Chatbot is interactive, letting people talk in the language they are attempting to learn and respond accordingly with a human voice. CEO and Co-Founder Alexandru Iliescu explains, "The best way to learn a new language is to build your confidence with practice… This new feature is truly a revolutionary new way to learn a new language and we're proud that Mondly is the first to do it." Speech recognition technology lets the Chatbot understand millions of phrases in all of these 33 languages, making it possible to have a conversation.