My situation as an online shopper is somewhat like this, "I know what I need but not sure where to buy em…" Over and above, most of the online shoppers experience a very similar perplexity. And I know how much pain purchasing a set of socks can cause if you are not a brand maniac. Continuing to how web personalisation can heal the aforementioned agony, it is the process where you customize your website to the needs of a specific user (This will curtail the online shopping fatigue). By using the insights you gain from analyzing user navigational behavior on your website. In correlation with other info accumulated in the form of structure, content and user profile data. There are two ways to collecting data on a user's interest and activities on a website.

The year 2016 proved to be an important milestone in the history of Artificial Intelligence (AI). Though the researchers have been working on creating intelligent machines for long, the year 2016 witnessed the concept leaving the realm of science-fiction to become more tangible and realistic. The year began with the Facebook founder Mark Zuckerberg announcing his plans to build an artificial assistant for his home. As the year proceeded, organisations across the globe started increasingly investing their resources towards the research and development of AI. As the word caught on pace, tech titans including Google, Intel and Apple raced to acquire private companies working to advance artificial intelligence.

An artificial intelligence (AI) system developed by Carnegie Mellon University (CMU) has defeated four professional card sharks in a 20-day heads-up poker tournament in Pittsburgh. The AI, Libratus, possesses the ability to perform strategic reasoning and the compute power to process the 10 160 possible information sets a game of heads-up no-limit Texas Hold'em poker has. Libratus was developed by professor of computer science Tuomas Sandholm and computer science PhD student Noam Brown, and hosted on the Pittsburgh Supercomputing Center's Bridges computer. According to both Sandholm and Brown, Libratus' victory was not the result of luck. "The best AI's ability to do strategic reasoning with imperfect information has now surpassed that of the best humans," Sandholm said.

With marketing becoming taking a central role in many companies, CMOs are forced to think more strategic. While they wade through the thousands of martech and adtech software out there, they must also align with the board and line of business heads to ensure that their marketing strategies meet corporate goals. It has ushered a new interest in Artificial Intelligence (AI) to help CMOs succeed. Such needs as created a frenzy among vendors to build the ultimate AI. Amazon, for example, recently announced three new AI tools – Lex, Polly, and Rekognition -- drawing on the character of the company's personal AI assistant Alexa.

Many of us might have heard the terms AI, machine learning and deep learning. Some of us also might have heard that they can have a big impact on cyber security. What are AI, machine learning and deep learning actually? And, how can they improve cyber security? In this article we would discuss about that. Artificial Intelligence or AI is the science and engineering of making a machine intelligent, so that it can perform tasks similar to those that require human intelligence.

Among the numerous articles dedicated to autonomous cars today, one particular thought experiment resurfaces often: the trolley problem. Adapted to self-driving cars, it is usually presented as follows: an autonomous car, with a person onboard, sees five pedestrians suddenly appear in its path. The only way to avoid them is for the car to send itself off the road, crashing and therefore causing its passenger's death. Faced with this Cornelian dilemma, what choice does the Artificial Intelligence control software have to make? This thought experiment is anything but science-fiction.

Syngenta and the AI for Good Foundation have partnered to launch the Syngenta AI Challenge, a new international competition focused on leveraging Artificial Intelligence (AI) tools for use in seed breeding. The competition is accepting submissions from applicants who are ready to put their programming skills to the test for the chance to win $7,500. "This new competition will give entrants the chance to use their talents to take on the extraordinary complexity of seed genetic data," said Joseph Byrum, Ph.D., MBA, PMP and senior R&D strategic marketing executive with Syngenta. "In the face of a rising global population, we need to grow plants that can adapt and thrive in changing conditions – especially as vital resources like water and land are finite. The Syngenta AI Challenge is about creating models that can help solve this puzzle and ensure world food security."

They often have to navigate, with limited resources, a stormy market made of customers, competitors, and regulators, and the interactions between all these actors make finding answers to business questions a complex process. But recently, machines have demonstrated their abilities to help shine some light on this chaos and provide, if not direct answers, context clues that help guide executives in using AI to to handle business problems. In this article, we delve into examples of how natural language processing (NLP) business applications can be applied at scale to address 5 pressing business questions. NLP is used by computers to manipulate human language, whether to extract meaning, generate text, or for any other purpose. The interaction computer-language is categorized according to the task that needs to be accomplished: summarizing a long document, translating between two human languages, or detecting spam email are all examples of tasks that today can be decently accomplished by a machine.

The information security industry's rush to adopt machine learning will help businesses burn US$96 billion on big data, intelligence, and analytics by 2021, says research house ABI . The report by lead number cruncher Dimitrios Pavlakis claims User and Entity Behavior Analytics (UEBA) and "deep learning algorithm designs" will be widely adopted by security companies as they collectively put big data to work detecting threats. The former machine learning technology, UEBA, is correlation on steroids, capable of detecting anomalies that can indicate if staff logins have been compromised and are being tested across the enterprise network. It can learn the activities and services most typical of a user to generate alerts when something anomalous occurs, like login attempts to odd network shares. Vendors are buying up across the space including Splunk's buy of Caspida, and Arksight selling Securonix.