One of the first computers required punch cards. Yes, you would take a piece of paper with tiny holes and use it to interact with the device. Now we have computers the size of soda cans that sit in your house and control your lights, provide weather updates, solve math equations and tell jokes, all by simply speaking to them… and some of them have better jokes than my actual friends. In many ways, we all should have seen this coming -- we can thank our Hollywood friends for that. We had C-3PO and R2-D2 running around the galaxy with Luke trying to help him save the universe from his dad.

The consequences of recent criticisms of statistical tests have breathed brand new life into some very old howlers, many of which have been discussed on this blog. What is not funny, though, is how standard notions such as frequentist error probabilities are being redefined in the process, and how we now have arguments built on equivocations. In fact, there are official guidebooks for the statistically perplexed giving inconsistent definitions to the same term (See for just 1 of many examples this post). How much more perplexed will that leave us! Since it's near the 5-year anniversary of this blog, tonight let's listen in to a new comedy hour mixing one from 3 years ago with some add-ons*.

Our intelligent analysis tool, alfazen, is specifically designed to identify successful trading opportunities. These samples are fed into hundreds of analytical as well as self-learning algorithms, incorporating most available technical analysis models, using the latest state of the art AI (Artificial Intelligence), which employs complex calculations using large computer clusters.

Internet search giants making self-driving cars appears to be a trend, and Russia's Yandex wants in. It's partnering with Daimler, truck maker Kamaz and government-backed researchers at NAMI on an autonomous shuttle bus that could carry up to 12 people and travel about 124 miles on a charge. Yandex is contributing its experiences with artificial intelligence, computer vision and voice recognition, and it'll even be central to the interface -- you'll use a Yandex-linked mobile app to pinpoint your destination. NAMI will start testing the self-driving bus on closed circuits in 2017, and it's bound to be a while after that before you can see one (or something like it) cruising the streets. There's no guarantee that you'll ever get to ride this bus beyond Russian borders, but it wouldn't be surprising if Yandex's technology finds its way into more vehicles. If nothing else, this is further evidence that driverless transportation is quickly becoming a worldwide phenomenon.

Which methods/approaches you used in the past 12 months for an actual Data Science-related application? Please vote and we will analyze and publish the results.

Reinforcement learning framework integrated with deeplearning4j. This is a tech preview and distributed as is.

I'll be speaking next month at the MarTech conference on How Machine Intelligence Will Really Change Marketing. This required assembling a list of marketing systems using machine intelligence, which pretty much inevitably led to the logoscape below. In particular, it illustrates several points that would otherwise have been hidden or much harder to convey. These include: Lots of systems. You may think that machine intelligence is still a pretty rare thing.

"Ethical concerns will only be taken into consideration if it makes financial sense. As the data market builds, are tech companies optimising for their own benefit or those of their clients? Companies should take responsibility for their role in the data ecosystem, making sure data flow vs responsibility are in equilibrium. "My hope lies in the European General Data Protection Regulation, effective by 2018, which sets a baseline for compliance. If tech companies can help their clients make ethical decisions about their data uses, we are on the right track." With the ability to sequence our DNA, we have become data - but what if we start creating a super race of humans or new species of plants and animals? Robots are beginning to take away jobs that require physical labour. "But what about when knowledge-based jobs start disappearing?

How Many Arlington Asset Investment Corp (NYSE:AI)'s Analysts Are Bearish?

Mount Sinai medical school's new Center for Computational and Systems Pathology will combine advanced technology, computer science and mathematical techniques with artificial intelligence to more precisely classify and treat disease. The center is designed to be a hub for developing new diagnostic, predictive and prognostic tests and determining which patients will be best served by them, according to an announcement. It will partner with Mount Sinai's "Precise Medical Diagnostics" (Precise MD) initiative, which is developing new approaches to characterize an individual's cancer by combining data from multiple sources and analyzing it using mathematical algorithms. "Our goal is to provide a precise mathematical approach to classifying and treating disease, which will assist our clinicians with information for effective patient care and health management," says Carlos Cordon-Cardo, M.D., Ph.D., chair of the pathology department, who will oversee the new center. "By refining diagnoses, we can save patients from unnecessary treatments."