Capgemini's view on the future – Technovision 2017 – states that capturing and leveraging collective knowledge as well as decreasing the dependency on undocumented, individual expertise and experience, is an important aspect of Artificial Intelligence (AI). Cognitive computing, like IBM Watson, can help suggesting solutions and ideas that are unknown to the user, based on collective knowledge. Now Cognitive Computing can find the applicable jurisprudence for any given law case or diagnose the right type of cancer from the patient's syndromes. But beside massive information processing, can Cognitive Computing help people resolve problems by creating new ideas? The goal of "Strong AI" is to develop Artificial Intelligence to the point where the machine's intellectual capability is functionally equal to a human's.

You might have probably heard about the artificial intelligence being developed by some big researchers around the world. The current period of era is also about creating technology that not only process faster, but also works efficiently just like the human brain. The innovation in such technologies has given rise to cognitive computing, which nothing but another miracle innovative development by a human brain to let the machine learn just like human being. Recently, IBM with its new cognitive system called as IBM Watson have entered into the segment of artificial learning to make system that is capable of learning and understanding knowledge to interact with human in a more natural way. The cognitive computing is a self-learning technology platform that uses data mining and pattern recognition to simulate itself in a way that human brain works.

Whereas, in the cognitive approach the recruiters are provided with a prioritised list of job requisitions (based on analysis of drivers such as job complexity, skills, location, and seniority) to streamline their efforts. They are then provided with a pipeline of best-fit talent based on the skills, competencies and other attributes found on resumes compared to the job description – removing any bias and speeding the selection process. Scanning social networks, recruiters receive advanced warning of market sentiment so that recruiters can have better conversations with the candidates. New hire support: Imagine you have been at your job in a new company for one week. There is a lot to learn with new systems and processes, as is the case with any new job.

Virtualization of workplaces and the ever changing technology is fueling an increasing demand for new skillsets while also increasing expectations about employee experience. In such a scenario, cognitive computing is a new tool which could be leveraged to bolster human capabilities and expertise by enabling better decisions. Cognitive computing could impact all the HR functions, especially HR operations, talent acquisition (including onboarding) and talent development. IBM Institute for Business Value (IBV) has revealed the findings of a new report called "Extending expertise: How cognitive computing is transforming HR and the employee experience" published along with the Smarter Workforce Institute (SWI). The report highlights the likely impact of cognitive technologies on HR functions.

With the position of Chief Data Officer being a relatively new concept that corporations are only recently beginning to incorporate into their business models, it comes as no surprise that the role has not yet been universally characterized as a set of defined job functions and responsibilities. In fact, the analytics tools used to do the job are also evolving, even as industry is trying to agree on the definition of the CDO post itself, according to Joe Selle (pictured), global operational analytics solution lead at IBM. Selle spoke with Jeff Frick (@JeffFrick) and Peter Burris (@plburris), co-hosts of theCUBE, SiliconANGLE Media's mobile live streaming studio, at the IBM Chief Data Officer Strategy Summit in San Francisco, California. Selle discussed the lead IBM has taken in guiding and shaping the development of deep learning and cognitive analytics to create the roadmap that will best serve its customers, as well as the marketplace as a whole. There has been a lot of talk at this week's CDO event about IBM's development of deep learning and cognitive computing, which, according to Selle, is set to revolutionize the analytics world. "The participants, the speakers [and] the audience members all know that they're at the cusp of a moment in business history of great change, and that is as we graduate from regular analytics, which are more descriptive, and dashboarding into the world of cognitive, which is taking the capabilities to a whole other level," said Selle.

Should Number 10 be worried about the impending AI revolution? The impending robot revolution has certainly got people talking – from the workplace to the car and home, robots and AI has really grabbed the attention of the public. However, setting aside Terminator-esque visions of the future, what do consumers really think of the impending AI revolution? Enterprise information management firm, OpenText, went and surveyed 2,000 UK consumers to find answers to that very question. Initial findings from the survey mirrored many other reports and surveys, with consumers expecting AI to impact the human workforce and their daily lives in general.

By all accounts, 2017 is set to be the year of A.I and cognitive computing. Forrester predicts that A.I will'drive the insights revolution in 2017' and Gartner claims that A.I and machine learning have reached'a critical tipping point'. Indeed, Gartner goes so far as to predict that by 2020, 30% of web browsing will happen without a screen. While there have been a limited amount of practical applications of this technology to date, there is no doubt that the concept is set to dominate the landscape for some time. However, although these technologies are undeniably exciting and revolutionary, they present as many challenges as they do opportunities.

In order for AI systems to enhance quality of life, both personally and professionally, they must acquire broad and deep knowledge from multiple domains, learn continuously from interactions with people and environments, and support reasoned decisions. Broadly, the AI fields' long-term progress depend upon many advances. As AI systems become ubiquitous in people's lives, serving many purposes in both personal and professional tasks, there are still many things they cannot do or that they should do much better. In order for AI systems to enhance humans' quality of life, both personally and professionally, they must acquire broad and deep knowledge from multiple domains, learn continuously from interactions with people and environments, and support reasoned decisions. Significant research efforts should be devoted to address these deficiencies.

Welcome to the home of information resources for AI and ML. We hope you find this site useful. Feel free to give us feedback.

Thank you for subscribing to the monthly THINK Marketing newsletter. Next-generation cognitive computing is redefining how we live and work as more businesses are using all the data available to them to improve performance and customer service, and drive innovation and revenue. Today's business challenges have never been more complex, and the critical insights that can help address these challenges are often buried in an avalanche of data. Previously, these insights were beyond the capabilities of conventional computing solutions – programmable systems based on mathematical principles that harken back to the 1940s. But IBM Watson has changed the game.