Machine learning, artificial intelligent assistants, algorithms… the new frontier of automated tools and tech is making it easier than ever to streamline our work. Moderating your comments section is no different, with many platforms offering tools to help automate the task so you can focus your attention on other matters. In this increasingly automated world, is there even a role for the human comment moderator? First, let's delve into the pros and cons of comment moderation software. Thanks to automatic moderating, you can ensure a safe space for your community to discuss your brand free from profanity, abuse and spam, without having to keep a constant eye on the community.

Whether selling via a website or app, you need to respond immediately to each step of the journey. You need to "see" your customer, understand who they are, collect the right data, evaluate their needs, detect anomalous behavior, assess risk / pricing / product / affordability, dynamically adapt the customer journey and make many other decisions... and all this in real-time. To do all this and more, Zoral has developed one of the world's most advanced, intelligent decision engines Zoral Decision Engine (ZDE). In many ways selling digitally is no different to selling face to face. You need to understand as much as possible about your customer and ask the right questions.

RSA USA Every year, the RSA Conference in San Francisco brings out the best and the brightest for its crypto panel, and the view from the floor was simple. Ignore the fads and hyped technology, and concentrate on the basics: good, clean, secure programming. The panelists were unimpressed with recent moves to build artificially intelligent security systems – despite the success of programs like the DARPA Cyber challenge – saying it was too early to consider such systems reliable and warning that some may never be. "I'm skeptical of AI on security," said Ronald Rivest, MIT Institute professor and the'R' in RSA. "Where we are seeing it becoming a wedge issue with the recent election is with AI bots in chat rooms. In 10 or 15 years you'll be competing to find a real human in a sea of chat bots."

Predicting earthquakes is the holy grail of seismology. After all, quakes are deadly precisely because they're erratic--striking without warning, triggering fires and tsunamis, and sometimes killing hundreds of thousands of people. If scientists could warn the public weeks or months in advance that a large temblor is coming, evacuation and other preparations could save countless lives. So far, no one has found a reliable way to forecast earthquakes, even though many scientists have tried. Some experts consider it a hopeless endeavor.

Although we don't know how brain functions yet, we have the feeling that it must have a logic unit and a memory unit. We make decisions by reasoning and by experience. So do computers, we have the logic units, CPUs and GPUs and we also have memories. But when you look at a neural network, it functions like a black box. You feed in some inputs from one side, you receive some outputs from the other side.

Sounds like a self-help group for frustrated call center employees. Rather, it's a catch-all term for how companies manage customer interactions and data. It covers strategies involving everything from customer service to sales. Each incoming phone call or email may contain an overwhelming amount of data that a mere human in today's hyper-competitive, tech-intensive environment can't handle alone. Time to bring in some help with artificial intelligence.

Data is growing at an astounding rate. Even the smartest humans could never consume all of the constantly generated data. New tools and solutions are helping companies connect and analyze internal, external and publicly available data to power decision-making across teams. This infographic series takes a deeper look at today's data landscape and how it is impacting industries including banking, telecom and manufacturing. What opportunities are you missing out on by not being more data-driven?

IBM will soon bring some of the core machine learning technology from IBM Watson to mainframes and the private cloud, the company announced on Wednesday. The new cognitive platform, simply called IBM Machine Learning, will make its debut on the z System mainframe. In a press release, IBM described IBM Machine Learning as a platform for "continuously creating, training and deploying a high volume of analytic models in the private cloud at the source of vast corporate data stores." The service could help enterprise data scientists more quickly get to valuable insights. "IBM Machine Learning was designed leveraging our core Watson technologies to accelerate the adoption of machine learning where the majority of corporate data resides," Rob Thomas, general manager for IBM Analytics, said in a press release.

It learns the parameter vector by formulating the problem as a structural SVM problem. The exact details of the method are described in the paper Max-Margin Object Detection by Davis E. King.

Research on machine learning and artificial intelligence needs to be done in the open and not by military research labs, Eric Schmidt, executive chairman of Google's parent Alphabet has said. Mr Schmidt was speaking at the RSA Conference in San Francisco on Wednesday. Some 40,000 security professionals have been attending the event this week. Security threats discussed at hundreds of sessions include the Russian hacking of the Democratic National Committee in advance of the US presidential election last year, as well as threats to business, to government and to internet-connected devices. In conversation with journalist Gideon Lewis-Kraus, Mr Schmidt said machine learning capabilities, which allow computers to learn without being programmed, needed to be done in the open and not by military research labs.