This long article with a lot of source code was posted by Suraj V Vidyadaran. Suraj is pursuing a Master in Computer Science at Temple university primarily focused in Data Science specialization. His areas of interests are in sentiment analysis, data visualization, big data and machine learning. I was surprised to see the overlap with our recent article on top 10 machine learning algorithms. You can read the full article (with voluminous source code in R) here.

It is quite difficult to connect with influencers. PR pitches often don't seem to cut it and influencers will not return your calls if they are not that interested in your product. But how do you connect with the right influencers when you need to run your campaign effectively? Media company Condé Nast has partnered with Los Angeles based influencer marketing platform Influential to implement its IBM Watson-enabled technology platform. This partnership will enable Conde Nast to help its advertisers better connect with audiences and gain insights into their campaigns.

A colleague of mine once quipped that automating a'crap' process just results in'automated crap,' and while the language might be a bit uncouth, the sentiment is absolutely correct. It can be tempting when tasked with automating a process to immediately start considering the systems and software to deploy; however, it's worth determining whether the process is currently valid, effective, and necessary before diving into automating it. Furthermore, some processes simply should not be automated. Sometimes pure technology is not the right answer for process automation, as the whole offshore process outsourcing business can attest to. While there are myriad risks and considerations to process outsourcing, considering non-technology options for process'automation' should be part of your evaluation and due diligence process.

Behavioral biometrics that uses machine learning is behind new features being added to IBM's Trusteer Pinpoint Detect platform, which financial institutions use to head off crooks who may have stolen the username and password of legitimate account holders. The new feature looks for anomalies between legitimate users' normal mouse gestures and those of the current user, and over time refines the accuracy of its analysis, says Brooke Satti Charles, Financial Crime Prevention Strategist for IBM Security. That analysis creates a risk score that banks can use to decide whether an ongoing transaction is fraudulent and trigger an alert. The institutions have to decide what to do about the alerts, but they could cut off the transaction or require further ID before the customer is allowed to continue, she says. The platform already checks the geolocation and IP address of customers as they login in order to detect fraudulent use, and behavior biometrics is an enhancement.

Why was I programmed to feel pain?" The question is played for laughs, but like so many memorable scenes from this most beloved of shows, it also taps into some of the deeper, overarching themes that define our modern civilization. Pain is a fundamental fact of life for many organisms on our planet; a crucial mechanism for identifying what kinds of actions pose serious threats to our physical and mental health. As robots become more sophisticated and interactive, should they also be programmed to experience pain to prevent injuries to themselves or others, and if so, to what extent? "Pain in the Machine," a 12-minute documentary released by the University of Cambridge on Monday, tackles this multifaceted and controversial issue. The film offers insights from artificial intelligence thought leaders, practicing physicians, and other interdisciplinary experts, and contrasts them with iconic popular culture moments that point to the larger philosophical questions inherent to artificially programming pain responses--including a nod to burning robot bit in The Simpsons. Like so many AI research fields, evaluating the utility and benefits of pain in robots inevitably flips the mirror back on our understanding of how those experiences function and protect us in our own lives. "Pain has fascinated philosophers for centuries," Ben Seymour, a Cambridge-based expert on the computational and systems neuroscience of pain, comments in the documentary. "Indeed, some people consider pain to be the pinnacle of consciousness.

Since winning Jeopardy! in 2011, IBM's Watson has apparently found employment as a dress designer, a chef, and a movie director. The latest news is that IBM is doing deals with GM, Slack, and Pearson that will see Watson helping, respectively, with roadside assistance, business messaging, and education. Even if you follow developments in AI closely, though, it can be hard to keep track of all the things Watson can do. It raises a question: what is it, exactly? TV ads that portray Watson as some sort of super-smart Siri don't exactly help.

To most computers, that word printed on an otherwise blank screen is simply a string of characters. You see a word associated with a big cat, a large mammal. Given the context of valet parking, it might also bring to mind a luxury brand that is similar to Mercedes and BMW. Put another way, you have a collection of ideas, or concepts, of what "Jaguar" means and the mental agility to use context to infer which concept the writer of the word intended to convey. On Tuesday, a team of scientists from Microsoft Research Asia, Microsoft's research lab in Beijing, China, announced the public release of technology designed to help computers conceptualize in a humanlike fashion.

Artificial Intelligence (AI) and robotics are no longer distant concepts but are fast becoming a reality. These new technologies will present a range of benefits for a number of industries, including those beyond the manufacturing sector where these are already being used. Forward thinking companies are embracing the new technological revolution – Industry 4.0 – by adopting AI and robotics. Take the example of chatbots. Businesses are increasingly using AI to allow computers to understand and respond to queries from customers.

Batch jobs are the lifeblood for thousands of businesses--many of which run millions of batch jobs every year. Unfortunately, managing these high volumes of batch jobs has become a huge nightmare: numerous errors require a large amount of resources to validate and isolate the problems. Even then, batch jobs still run into unexpected outages, while Service Level Agreement (SLA) violations threaten the proper operation of the business. This webinar demonstrates how ignio, the world's leading cognitive system, has been helping customers tackle this complex problem. We share real world examples on how ignio is implemented and highlight the lessons learned from these implementations.

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