By using this "Contrivance," "the most ignorant Person at a reasonable Charge, and with a little bodily Labour, may write Books in Philosophy, Poetry, Politicks, Law, Mathematicks, and Theology, with the least Assistance from Genius or study." Bayesian inference will become a leading approach in machine learning. The boat was equipped with, as Tesla described, "a borrowed mind." The word "robot" comes from the word "robota" (work). It features a robot double of a peasant girl, Maria, which unleashes chaos in Berlin of 2026--it was the first robot depicted on film, inspiring the Art Deco look of C-3PO in Star Wars.

On Facebook, headlines are often more important than the articles themselves. Most headlines are browsed, not clicked -- think about your own Facebook behavior; How often do you click on links? Because of this, the headlines frame our positions on topics without even having to read the content. It's quick, simple, and we feel informed. But with respect to politics, this news feed browsing behavior creates an electorate that can become dangerously uninformed.

There is no doubt that the next promising evolution will be brought by bots, but it could be sooner than expected. Today, leading companies have dived into the chatbot space, and brands are ensuring they aren't late to the party. You can read what companies are up to here. Startups like Jugnoo and also newer like Yellow Messenger have started implementing bots. Satya Nadella has already declared bots are new apps, and has been adding timely updates to make this possible in the future.

I started to delve into the field of Machine Learning few months back and after making a few projects, I thought to myself, "this isn't really tough". That was until I encountered Deep Learning. A whole new field of study, Deep Learning requires a vast amount of mathematical as well as analytical knowledge. As I was preparing to get hands on with Neural Nets, I realized that it is so overwhelming. There are so many complex concepts that cannot be just "learnt and implemented".

Fukoku Mutual Life Insurance Co. is planning to slash nearly 30 percent of its payment assessment department's human staff after it introduces an artificial intelligence (AI) system in January 2017 to improve operating efficiency. While concrete examples of AI systems making human workers redundant are currently rare, observers have pointed out that such cases are likely to increase. The insurance firm will introduce an AI system based on IBM Japan Ltd.'s Watson, which according to IBM is a "cognitive technology that can think like a human," and "can analyze and interpret all of your data, including unstructured text, images, audio and video." The Watson-based system will be tasked with reading medical certificates written by doctors and other documents to collect information necessary for making payouts, such as medical histories, length of hospital stays, and surgical procedure names. In addition to determining payment amounts, the system will also be able to check customers' cases against their insurance contracts to find any special coverage clauses -- a measure expected to prevent payment oversights.

If you indulge in the occasional television crime drama like most of us do, you've no doubt seen some high-tech investigative tools in action. Incredibly sophisticated video facial recognition is one that's commonly featured: Investigators watch live, grainy security footage, zoom in on a suspect's face, instantly snap it into high-resolution and immediately match the face to a criminal's photo in a massive database. But is that super-advanced level of technology realistic? While real-time video facial recognition remains in its infancy, the development of deep learning techniques -- part of the machine learning family -- is advancing the technology at a rapid pace. Deep learning has also fueled advances in a host of other artificial intelligence and cognitive computing applications for intelligence agencies.

The various manifestations of machine learning, deep learning, neural networks, cognitive computing, image recognition, speech recognition and natural language processing are consistently aiding the enterprise in analytic endeavors associated with big data. In many instances, AI is an immediate solution for the volumes and velocities for which big data is known. Touted as one of the primary expressions of big data in the subsequent decade, its emergence should become much more apparent in the coming 12 months largely due to the maturing influence of AI and the cloud itself. Its most eminent application could very well be provisioning a prototype for security measures to truly fortify the IoT. The year 2017 will see additional organizations experimenting with ways those capabilities render big data less daunting and perhaps even more enjoyable.

Apple has stayed true to its promise and published its first academic paper on artificial intelligence. The world's most valuable company has traditionally kept its AI research private but earlier this month Ruslan Salakhutdinov, director of AI research at Apple, made a pledge to start being more open. The new Apple paper -- published December 22 and titled "Learning from simulated and unsupervised images through adversarial training" -- gives an insight into some of the techniques that Apple is using to develop AI. In the study, which was published through the Cornell University Library, Apple researchers explain a technique that can be used to improve how an algorithm learns to "see" what is in an image. The paper's six authors state that using synthetic images (such as those seen in a video game), as opposed to real-world images, can be more efficient when it comes to training AI models known as neural networks, which are designed to think in the same way as the human brain. Because synthetic image data is already labelled and annotated while real-world images aren't.

Downtown Havana resident Margarita Marquez says she received a special Christmas gift this year: web access at home, a rarity in Cuba, a country with one of the lowest internet penetration rates in the world. Ms Marquez, a 67-year-old retired university professor, was among those selected by the government two weeks ago to participate in a pilot project bringing the web into the homes of 2,000 inhabitants of the historic centre of the island's capital. Most of Communist-ruled Cuba's 11.2 million inhabitants only have access to internet at wi-fi hotspots, and only then if they can afford the 80p hourly tariff that represents around five per cent of the average monthly state salary. Only five per cent of Cubans are estimated to enjoy internet at home, which requires government permission. This is usually granted mainly to academics, doctors and intellectuals.

What are lift, KPI, robustness, model fitting, design of experiments, and the 80/20 rule? Answer: KPI stands for Key Performance Indicator, or metric, sometimes called feature. A robust model is one that is not sensitive to changes in the data. Design of experiments or experimental design is the initial process used (before data is collected) to split your data, sample and set up a data set for statistical analysis, for instance in A/B testing frameworks or clinical trials. The 80/20 rules means that 80 percent of your income (or results) comes from 20 percent of your clients (or efforts). What are collaborative filtering, n-grams, Map Reduce, and cosine distance?