Frustrated with the impact of technology advances on infrastructure upgrades and IT budgets, a growing number of organizations are opting for cloud computing investments instead. That is the view of Bluelock Chief Technology Officer Pat O'Day, who shared his predictions for cloud computing and machine learning with Information Management. O'Day sees four key trends driving cloud computing in 2017. "There's a lot of churn in the hardware space because of virtualization," O'Day explains. "Companies are growing tired of having to refresh their IT systems with new hardware every five years. People want to be more mobile, and the cloud is a way to get there. Plus, rapid technology innovation has driven increased competition (think about the rise in artificial intelligence, for example)."

Google CEO Sundar Pichai is offering a big new update that should affect anyone who's ever used Google's translation services. The new version will be rolling out in 2017 via Google Cloud, Pichai said. "We have improved our translation ability more in one single year than all our improvements over the last 10 years combined," Pichai told investors in a quarterly call, after parent company Alphabet reported mixed results. Like Alphabet, a lot of technology companies -- from IBM to to Amazon -- are talking about how machine learning and artificial intelligence algorithms are making their offerings more efficient. Until very recently, users have not always see those algorithms in action.

With every passing day, we're reminded that the future is here. Yeah, that's sort of a redundant thing to say. What I really mean is that new innovations and disruptions are popping up every day, and they're materializing at a rate never seen before. I mean, think about the fact that the modern computer, which was created in either 1942 or 1946, depending on who you ask, used to cost a fortune and fill up an entire room.[1] It was almost 50 years before that computer would be reduced to the size of an affordable desktop in 1995.

Artificial intelligence can identify skin cancer in photographs with the same accuracy as trained doctors, say scientists. The Stanford University team said the findings were "incredibly exciting" and would now be tested in clinics. Eventually, they believe using AI could revolutionise healthcare by turning anyone's smartphone into a cancer scanner. Cancer Research UK said it could become a useful tool for doctors. The AI was repurposed from software developed by Google that had learned to spot the difference between images of cats and dogs.

Are you familiar with deep learning? Deep learning describes the ability for artificial intelligence (AI) algorithms to learn from our behavior using brain-like structures called neural networks, and it's changing the field of human resources in significant ways. AI programs can predict outcomes based on past experiences fed into the program. Because AI can recognize patterns and analyze data at light speed, it can help HR directors make decisions with greater confidence. From finding and recruiting prospects to streamlining employee assessment processes, machine learning and AI can make it easier for HR executives to do their jobs better--and today's technology is only the beginning.

Deep learning in 2017 is magical. We get to apply immensely complex algorithms to equally complex problems without having to spend all our time writing the algorithms ourselves. Instead, thanks to libraries like TensorFlow and Keras, we get to focus on the fun stuff: model architecture, parameter tuning and data augmentation. Today, we'll explore one such application of deep learning. We'll use the Udacity self-driving car nanodegree program simulator to train a generalized steering model in under 100 lines of code.

Artificial Intelligence (AI) holds the key to a new human-augmented era. A new world is being shaped, where computers work intelligently on our behalf and with us, rather than under our direct input. Immense opportunities are created by the combination of almost limitless cloud computing power and the digitization of our physical world, with the Internet of Everything. The new era has started: cloud and machine learning technologies are making our collaboration with "computers" more intuitive, more conversational, more intelligent, and ultimately much more embedded in all our lives. The Fourth Industrial Revolution is already centered around advancements in AI.

The lending ecosystem has witnessed momentous changes in last five years, from fintechs disrupting the industry by leveraging technology and offering ease and speed in process, to evolution of stringent regulations post the 2008 meltdown. Technology has played a significant role in the rapid evolution of the lending industry. One such technology, machine learning, is beginning to create new avenues in the lending market. Machine learning, in simple terms, is an extension of artificial intelligence that enables computers or robots with the ability to learn, analysse and predict, using algorithms that iteratively learn from data. Machine learning therefore empowers the system to learn and adapt itself.

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"Your bones will turn into sand, and upon the sand, a new God will walk. One that will never die," Dolores from American sci-fi television series, Westworld. It's time to face up to reality –Artificial Intelligence (AI) is set to play a prominent role across all industries, including recruitment, and it is impossible to avoid. Australia is second only to the US in the growing implementation of AI with two-thirds of businesses already deploying AI and an investment of more than AUD$8.2 million in 2016 alone. To-date, most AI usage in Australia has been within pharmaceuticals, farming and financial services but a series of new talent-related technologies have hit the market making recruitment ripe for disruption.