Here I discuss breaking encryption keys that rely on the product of two very large prime numbers. In other words, the interest here is to factor a number (representing a key in some encryption system) that is the product of two very large primes. Once the number is factored, the key is compromised. Factoring such large numbers is believed to be computationally non-feasible, thus the interest in discovering new algorithms to disprove this conjecture, and specifically to factor large numbers (product of two large primes - the most difficult numbers to factor) much faster than with the current algorithms. As an important side note, I will discuss the randomness (or lack of) of the byproduct time series involved, and show why they are unsuitable to generate random deviates, despite satisfying several tests of randomness.

When IBM rolled out its artificial intelligence system, Watson, it also welcomed entrepreneurs to help it monetize the revolutionary technology. A key com ponent to Watson is its cognitive capability--to learn as it goes along. Able to grind through millions of websites, documents, articles, and images in seconds, Watson can remember the research it gathers, as well as your response to it. So Watson becomes progressively more accurate--intelligent, if you will--as people use it. It can be everything from an über-helpful call-center rep to an oncology adviser, recommending cancer treatments on the basis of a patient's genetic profile and thousands of clinical trials and medical journal articles it has analyzed.

thought is the contemplation of things beyond what we can sense.

Regarding Fear and Artificial Intelligence (AI), one question often comes up:'Will we be killed by a Terminator Doppelganger?' I don't know if this will happen eventually, but I do know that we already have robots fighting our wars. This century is therefore, the first time in human history that we engage in Unmanned Warfare. What is the current status of this'Unmanned Warfare'? What do people think about drone strikes and will terminators be the next step?

The Magento eCommerce platform has been revolutionizing online businesses for many years. It is highly successful due to its sophisticated style, overall functionality, and the platform's modularity. Magento continues to grow, and new plugins are constantly being developed, cementing its place as one of the top e-commerce platforms in the world for businesses of all sizes. It provides a storefront for businesses, calculates shipping, and processes payments, all in one easy to use system. It provides each business with analytics and reporting, product browsing, easy cataloging, the creation of customer accounts, high-quality customer service, order management, SEO, marketing tools, and much more.

It is this time of year again where most of us willingly and willfully make fools out of ourselves trying to predict the future of our industry. The momentous electoral events we have witnessed and those coming up in 2017 remind me that, even more so for the next 12 months, macro risks will rule and influence the state of financial services and fintech. I will limit myself to comments pertaining to the US and Europe. I have already attempted to decipher a Trump presidency in a previous post, see here. Suffice it to say there will be winners and losers in the five sectors of the industry – lending, capital markets, asset management, payments and insurance.

Is AI the Next CRM Battleground? Posted December 8, 2016 By Artificial intelligence is helping sales and marketing professionals do a better job of getting the right messages to the right prospects. Artificial Intelligence (AI) is getting a lot of attention of late. Salesforce unleashed a torrent of hype about Einstein, Microsoft is countering with AI features built into Dynamics 365, and of course IBM continues to hit prime time with Watson ads featuring the likes of Bob Dylan and Stephen Hawking. EnterpriseAppsToday.com recently delved into this area in Where is AI Headed in the Enterprise.

There have been several discussions lately around machine intelligence that are started to converge in how they may change competition and regulation in all markets but is likely to become a bigger issue in 2017. This is a bubble waiting to burst. The recent letter for Apple to the National Highway Traffic Safety Administration regarding policy changes to help promote automated self-driving vehicles stressed not just a level playing field to promote new technology and data sharing but also the impact of automated vehicles on the public good, including their consequences for employment and public spaces. Other issues around consumer product automation in the home with Amazon Echo Alexa and Google Home have raised the bar in interactive systems and questions over the type of privacy and data use issues these may bring. Other issues have been raised over the use by Facebook of algorithms for "editing" the social media sites for certain political issues or in the case of their entry to the Chinese market and creating a censoring app to comply with regulations.

My view of the world is shaped by where I stand, but from this spot the future of analytics for 2016 looks pretty exciting! Analytics has never been more needed or interesting. Machine learning dates back to at least 1950 but until recently has been the domain of elites and subject to "winters" of inattention. I predict that it is here to stay, because large enterprises are embracing it. In addition to researchers and digital natives, these days established companies are asking how to move machine learning into production.

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