Unless you're quite out of touch with digital trends, you'd struggle to not have heard of the phrase Machine Learning (ML). Articles are shared online daily, software vendors and service providers have begun to offer Machine Learning as-a-service, thereby making it easier to integrate ML into your existing software products (no PhD required!). But what exactly is Machine Learning? Simply put, machine learning is a type of artificial intelligence, or AI. Software applications are traditionally programmed by a human.

Artificial intelligence now fits in our daily lives and is deployed in more and more business sectors, hustling human expertise. Artificial intelligence should transform one job over two, but does not necessarily represent a threat. In fact, these jobs should be redirected to less repetitive tasks, with more added value. According to a PwC study from March 2017, 70% of the jobs in the energy sector and 65% of the jobs in the consumer sector could be automated through artificial intelligence. This new technology involves a necessary change in the value chain and, if it opens the way to new skills like cybersecurity, it also represents a major challenge and opportunity for these businesses.

Automated story generation is the problem of automatically selecting a sequence of events, actions, or words that can be told as a story. We seek to develop a system that can generate stories by learning everything it needs to know from textual story corpora. To date, recurrent neural networks that learn language models at character, word, or sentence levels have had little success generating coherent stories. We explore the question of event representations that provide a mid-level of abstraction between words and sentences in order to retain the semantic information of the original data while minimizing event sparsity. We present a technique for preprocessing textual story data into event sequences. We then present a technique for automated story generation whereby we decompose the problem into the generation of successive events (event2event) and the generation of natural language sentences from events (event2sentence). We give empirical results comparing different event representations and their effects on event successor generation and the translation of events to natural language.

Rodolfo Bonnin is a systems engineer and PhD student at Universidad Tecnologica Nacional, Argentina. He also pursued parallel programming and image understanding postgraduate courses at Uni Stuttgart, Germany. He has done research on high performance computing since 2005 and began studying and implementing convolutional neural networks in 2008,writing a CPU and GPU - supporting neural network feed forward stage. More recently he's been working in the field of fraud pattern detection with Neural Networks, and is currently working on signal classification using ML techniques.

Did you know that in Rosario, Argentina -- the hometown of Lionel Messi -- a law has been passed preventing parents from naming their children after the Barcelonian superstar?? So, I tried a lot but couldn't find the exact data but still, I believe that there would be almost 25% to 30% of the population sharing similar words in their names. I have a small task for you to do: Check this link out and see whether your name or one of your friend's name is from https://nameberry.com/popular_names Also, you would know the trouble of finding out the correct phone number from a phone book. There are a lot of similar names in this world. If we are having such a problem.

TORONTO, January 25, 2017 - Today NextAI announced major partnerships with several leading Canadian companies to help fund and support the program and its participants. NextAI is a global innovation program for artificial intelligence-related ventures, and talented teams from around the world are invited to Canada to leverage the nation's leadership in AI and are provided with capital, mentorship, education and networking opportunities. The concept for NextAI was born out of an innovation brainstorming session sponsored by RBC and Magna during the summer of 2016, and joining RBC and Magna as founding corporate partners are BDC Capital and Scotiabank. To date, the funding provided by all corporate partners totals $5.15 million. NextAI has also formed technology partnerships with IBM Canada, Google and NVIDIA, who have committed millions in hardware, access to technology, and services.

Apparently capitalism is collapsing, North Korea will nuke us all, and a total environmental breakdown will turn the whole world into a bad Mad Max rerun. Oh yeah and superintelligent machines will rise up and kill us all. It all reminds me of Harold Camping, the doomsday guru who took out ads saying the world would end on May 21, 2011. It must be right around the corner. If we keep predicting Armageddon via sun spots, evil machines and the plague, eventually maybe we'll be right. Hey, even a blind squirrel can find a nut once in awhile. But the more I look at things, the more I think we're firmly in the grip of a mass hysteria of epic proportions, magnified by the megaphone of the Internet. HINT: Capitalism is fine, it's just evolving into something that works better for everyone, as it should (care of the mind blowing power of cryptocurrencies); North Korea is not nuking shit because they know they won't exist the very next day; and I'm betting on brilliant kids like Boyan Slat, renewable energy and plain old "necessity as the mother of invention" to stave off Mad Max. You have firm evidence that if we don't act fast it's all over for us!

A little bit of hype can build excitement about potential, while too much leads to false hopes and misguided planning assumptions. "Right now, the myths surrounding artificial intelligence (AI) are rampant," says Alexander Linden, research vice president at Gartner. "Wisely for now, most organizations' commitments are tentative and more oriented toward experimenting and learning, rather than trying to transform their enterprise or industry as fast as they can." Enterprise architecture and technology innovation leaders must walk a fine line between embracing and overplaying AI technologies' role in delivering business value for digital business. "Leaders shouldn't trust any of the myths and hype around AI. Instead, they must become centers of expertise if they are going to educate senior business executives on the real benefits -- and shortcomings -- of AI," says Linden.

Dubai: Artificial intelligence (AI) will play a stronger role in the cyber security space in the future and the key purpose is to initially help automate mundane tasks, like prioritising security logs, so that companies can reduce the human time and effort. Unfortunately, what mostly happens today is cyber blindness, essentially because there is no way to manually check the huge amount of data that cyber experts process every day. The industry is faced with two options again: to leave the data as it is, leaving the possibility open of looking back to the past to verify data or to develop something, which could help solutions providers to analyse real time logs and take decisions. The second option is called machine learning or AI. More and more organisations are choosing machine learning and artificial intelligence today.

Derek Manky, global security strategist at Fortinet, said that the world is seeing more and more automation being built into black hat attackers' attack technology. What this means is, the time to respond to cyber-attack is shrinking drastically. Ten years ago, weeks or days to respond to a cyber-attack was adequate. Today, "we begin to measure in minutes (less than an hour)". "In the future, we will start measuring this in seconds. Humans cannot operate on this level, and therefore AI is crucial to respond at machine speed to the threat of cyber-attack," he said.