Even in Top IT companies, recruitment/hiring process is the least technology driven activity. Either companies are still living in stone-age and maintaining applicant records in excel; or they are forced to use custom tools/interfaces which somehow get integrated with their existing IT infrastructure. Although job seeking has evolved in last few years. Job seeker can use online professional networks, job portals, placement agencies, assessment companies and/or training institutes. But every single channel has its own path.

PAU: In the ML space, it's very important to focus on niche apps and solutions. If somebody aims at a very broad application and a very broad set of solutions, it's probably going to fail. If entrepreneurs focus on solving a particular problem with a particular algorithm, they are more likely to succeed. A narrowed variability of results. There are 12-15 algorithms availalbe to use. Very difficult to chose - for solving what?

There is a huge buzz about Artificial Intelligence or Machine learning or rather Deep learning now a days. And you may not know it yet, but these technological developments are playing a key role in what you see and experience on internet these days. From a long time, Deep learning was heavily used to perform computer vision applications, but soon enough, some amazing players in the industry realized that its not just visual data from where one can extract insights using Deep learning, but the same principles can also be applied to textual data and thus these organizations are actually driving a new wave of NLP through deep learning in the industry. Hard to say about you, but we were pleasantly surprised to know that there are about 120 Deep Learning startups only in the bay area. UK, China, India etc are yet to be included in this number. The landscape for Deep Learning and Machine Learning applications is wide and few companies have started exploring this aspect and have come up with some really promising products that would help businesses to drive decisions owing to growth.

Machine learning (ML) is such a hot area in security right now. At the 2016 RSA Conference, you would be hard pressed to find a company that is not claiming to use ML for security. To the layperson, ML seems like the magic solution to all security problems. Take a bunch of unlabeled data, pump it through a system with some ML magic inside, and it can somehow identify patterns even human experts can't find -- all while learning and adapting to new behaviors and threats. Rather than having to code the rules, these systems can discover the rules all by themselves.

It's no secret that business travel can be stressful and travelers are always keen to remove friction during a trip. Artificial intelligence (AI), already familiar to most travelers in the form of digital assistants like Ok Google, Siri and Cortana, may provide an answer. At its core, AI automates computer processes to understand and mimic the human brain. While there are many fields that comprise AI, two that are commonly used for everyday applications are Natural language processing (NLP), and Machine learning. NLP helps computers understand human speech or typing.

Digital transformation is a buzzword that entrenched itself in the tech the business worlds, but who actually knows what it means? Google's Yuval Dvir had a go at pinning down a definition. According to Dvir, who was speaking at the Managed Services World Congress, the key to digital transformation is change. Now this may seem pretty bloody obvious, but in fact it seems that corporate decision makers the world over are vastly under-estimating the scale of change. This could meand change in the context of technology where data is becoming the digital currency, in the context of people who are becoming more immersed in the virtual world, or in the context of business where the cloud has increased the frequency of innovation.

EdTech runs four or five years behind TechCrunch headlines. Accordingly, hot topics in tech this year–AI, robotics, VR, wearables–will become widespread in education in a few years. Makerspaces and online learning are both expected to be widely adopted by schools in one year's time or less to encourage students to take ownership of their education by creating and provide them with ubiquitous access to digital tools, discussion forums, rich media and more. The time to adopt for robotics and virtual reality are estimated within two to three years, while artificial intelligence and wearable technology are expected to be mainstream in schools within four to five years. Horizon Report is published by CoSN, the association of district EdTech professionals, and the New Media Consortium.

Humans have been interested in building intelligent computer systems since the beginning of computing technology. There's something both interesting and strange about mimicking the function of a human brain that we feel the need to explore -- how crazy is it to build a machine that can beat out the human brain in a game of chess? Of course, as applied to today's chatbots, artificial intelligence is still in its infancy. But don't take that the wrong way: Today's bots can still offer a great deal of utility for businesses and consumers. Messaging platforms like Facebook Messenger, WeChat, and Kik are making it easier than ever for brands and businesses to have a presence where millions of users are already spending time.

We'll tell you how to make the most of your money but also why money is not an end in itself and connecting financial goals to your life goals is really what you should be doing. Of course we will also still continue to provide tips for investors, business ideas for businessmen and comments on the economy, markets, companies, financial products, and trends. Have you heard of chatbots? It's an artificial intelligence computer programme that can engage you in a voice or text conversation. Chatbots can answer your questions, book a flight for you and even search for a property you like.

We've all enjoyed the simple benefits of Google's artificial intelligence photo recognition. Google Photos employs a very stripped down version of the algorithm to identify pictures as containing cats, dogs, food, or specific people. However, the search giant has been working on much more advanced photo recognition capabilities, and today they've released their progress to developers. The Google Research Blog reports that the Google Brain team's AI image captioning system has achieved a 93.9 percent accuracy rating. Their results in 2014 used the Inception V1 image classification model and achieved 89.6 percent accuracy.