A compact computer called Euclid from Intel should make the development of robots much easier. Euclid looks much like the Kinect camera for Xbox consoles, but it's a self-contained PC that can be the guts of a robot. It's possible to install the Euclid computer where the "eyes" of a human-like robot would be typically placed. Intel demonstrated the Euclid computer in a robot moving on stage during CEO Brian Krzanich's keynote at the Intel Developer Forum on Tuesday. Euclid has a 3D RealSense camera that can serve as the eyes in a robot, capturing images in real-time.

It's no secret that there is a wide gender gap in the tech industry. According to the Center for the Study of the Workplace, women represent around 20 percent of engineering graduates, but just 11 percent of practicing software engineers. Unconscious bias is one of the primary drivers of this disparity, which has led many of Silicon Valley's leading tech companies to introduce unconscious bias training to their employees. However, it's fair to say that its machine learning algorithms need it more. In humans, unconscious biases are ingrained assumptions about particular personal attributes (including race or gender) that can influence decision making without the decision maker being explicitly aware.

It's been called the'sexiest job of the 21st century', the'hottest job of the decade', and is the fastest-growing field in tech at the moment – the impact of Data Science in today's world cannot be overstated. As a discipline, data science involves the collection and study of data – both structured and unstructured – to gain insights and information that can be used by organizations to devise effective strategies. By collating data over a period of time, patterns can be identified that enable companies to find new market opportunities, enhance efficiency, reduce costs, and place themselves at a competitive advantage in their industry. Due to rapid technological advances, especially in areas like mobile advertising, social media, and website personalization, a massive amount of data is being generated on a daily basis. These data volumes have resulted in industries having to become data-savvy & adapt to the new landscape – or risk falling behind the competition.

The amount of data in pathology images has previously been too vast for researchers to process easily, but that's changing thanks to advanced machine learning. A group of researchers from Stanford University were able to more accurately predict lung cancer prognoses by grabbing images from the Cancer Genome Atlas from patients with the disease, and then through those train a computer software program to pinpoint characteristics in the images previously unable to be seen by the human eye, according to an announcement. Their research was published in Nature Communications. Once the researchers could home in on those specific characteristics, they were able to figure out the cancer subtype, as well as how long a patient would live with that diagnosis. "Ultimately this technique will give us insight into the molecular mechanisms of cancer by connecting important pathological features with outcome data," Michael Snyder, Ph.D., a professor and chair of genetics at Stanford, said in the announcement.

The journal has a broad scope and publishes high quality papers on all aspects of computational intelligence and artificial intelligence related to games. TCIAIG has been accepted into the Thomson Reuters Web of Science and will, by mid-2012, have an Impact Factor listed in the Journal Citation Report (JCR). The journal is co-sponsored by the IEEE Computational Intelligence Society, the IEEE Computer Society, the IEEE Consumer Electronics Society and the IEEE Sensors Council. It is technically co-sponsored by the IEEE Systems, Man, and Cybernetics Society, the IEEE Instrumentation and Measurement Society, the IEEE Robotics and Automation Society, and the IEEE Communications Society.

Not to mention, technological disruption that (a) erodes, (b) replaces, or (c) reverses most of the current best practices every 6-12 months. "RankBrain has become the third-most important signal contributing to the result of a search query", according to senior research scientist at Google, Greg Corrado. It's an artificial intelligence engine that uses pattern matching at scale to process millions of search queries daily. And with an 80% accuracy rating, it outperforms engineers by a wide margin. There's no wonder that it's taking over the search giant then. Part of that success comes from the ability to literally guess – based on millions of datapoints in fractions of a second – the searcher's intent behind a few random keystrokes.

Like many in Silicon Valley, technology entrepreneur Bryan Johnson sees a future in which intelligent machines can do things like drive cars on their own and anticipate our needs before we ask. What's uncommon is how Johnson wants to respond: Find a way to supercharge the human brain so that we can keep up with the machines. From an unassuming office in Venice Beach, his science-fiction-meets-science start-up, KerNEL, is building a tiny chip that can be implanted in the brain to help people suffering from neurological damage caused by strokes, Alzheimer's, or concussions. The team of top neuroscientists building the chip -- they call it a neuroprosthetic -- hope that in the longer term, it will be able to boost intelligence, memory, and other cognitive tasks. The medical device is years in the making, Johnson acknowledges, but he can afford the time.

Stellaris 1.2.5 hotfix patch released, with AI fixes

There is no such thing as artificial intelligence. I am beyond thrilled at the interest the field is receiving. As someone who has had to explain what machine learning is, how big data could better a solution, and just generally push a new method of thinking I am excited and optimistic that this is becoming top of mind for technology businesses. Like anyone else with a dear interest in a topic, it is hard for me to get past gimmicky nuances winning over true understanding. Big data is nothing more that large set of stationary data. Faster computing makes it easier for us to statistically sift through data.

The next industrial revolution Australian businesses will face won't be based on mechanisation, engineering or globalisation. Instead, it will be the rise of automation and artificial intelligence (AI) systems that will power the next great business push. AI is fast becoming a necessity in the business world and organisations are increasingly adopting AI to solve long-standing issues within their industry. Just last month, KPMG revealed they would be using AI to complete audits in Australia, which they anticipate will enable them to analyse bigger batches of data rather than relying on traditional sampling techniques. Taking tasks which usually require human intelligence and delegating them to machines has significant impact on business activities, including productivity, efficiency and even the way job roles are defined. But what really is AI?