THE ORIGINAL MACHINERY question, which had seemed so vital and urgent, eventually resolved itself. Despite the fears expressed by David Ricardo, among others, that "substitution of machinery for human labour…may render the population redundant", the overall effect of mechanisation turned out to be job creation on an unprecedented scale. Machines allowed individual workers to produce more, reducing the price of many goods, increasing demand and generating a need for more workers. Entirely new jobs were created to oversee the machines. As companies got bigger, they required managers, accountants and other support staff.

Artificial intelligence is creeping into everyday life in the form of intelligent personal assistants (IPA). Question-answering applications aim for human-like responses, but it's tough to live up to that standard.

Google's DeepMind artificial intelligence (AI) technology has proven to be very smart. DeepMind's AlphaGo system got worldwide attention for beating top-ranked Go player Lee Sedol earlier this year. Previously it has played Breakout and navigated a Doom-like maze. But now the DeepMind software is looking more versatile. Today the Google DeepMind lab unveiled another feat that looks off the wall but is actually evidence of the strength of Google's AI.

"Front-facing robots play an important role in data gathering, and can then make connections. For instance, they can store a query and intelligently offer relevant information to a guest in future," says Pemberton. Crucially, such data can be amassed in a centralized location and delivered on demand locally, so the preferences of a guest staying in a hotel in Miami will be captured and reapplied when she checks into a hotel belonging to the same chain in say, London.

In the construction industry, many projects involve remodeling or refurbishing existing buildings, and such jobs often face delays or cost overruns when hidden problems emerge. "Renovation projects live and die by the quality of information," according to Martin Fischer, a Stanford professor of civil and environmental engineering. New software can analyze this point cloud to automatically extract details to plan a remodel or other purposes. Newer buildings often have computerized blueprints and records, including details such as the number of rooms, doors and windows, and the square footage of floors, ceilings and walls. But such information may not exist for older buildings, necessitating the time-consuming and difficult task of collecting these details manually.

In relation to Bayesian statistics, the sensitivity and specificity are the conditional probabilities, the prevalence is the prior, and the positive/negative predicted values are the posterior probabilities.

The way we are used to do things and draw decisions is about to change with the oncoming digital evolution. Software and hardware are converging in the Internet of Things and devices driven by machine learning will bring in machine-like accuracy and speed to support data driven human decisions and actions. In today's world, we need to designs solutions for customer engagement in the digital age, and regularly rework our industry scenarios to stay ahead of the game. There is a call for design of data driven, machine learning enabled enterprise software to run on state-of-the-art connected devices. As the amount of data continues to grow, it is essential to utilize the power of deep learning to urge better decisions throughout the customer engagement process, and to run on the next generation of connected devices.

MLPB is meant to become an organized collection of machine learning problems and solutions. I need to classify something as A, B or C using a combination of numeric and categorical features. If I could find a similar problem, maybe I could modify the solution to work for my needs. This is where MLPB steps in. Want to see ML problems with sparse data?

At the first Asia ICT Innovation Forum held in Singapore recently, a slew of international thought leaders spoke on their views on "Building a Better Connected World". Not surprisingly, the core issues were around connectivity and how to get internet access to the billions still not connected. But this was balanced by a number of speakers stressing the importance of data analysis and the move to cognitive systems to get the best out of being connected.Getting value from big chunks of data has delivered companies like Facebook, Google, Uber and Airbnb massive valuations – they understand how to turn data into value and traditional companies are starting to figure that out also. Alan Marcus, Head of ICT Agenda at the World Economic Forum (WEF), focused his presentation on the value of Big Data and moving from IT to DT (Data Technology). He prefaced his talk by stating that the WEF believes we are entering the fourth industrial revolution – the convergence of technologies that build upon the digital revolution.

The upgraded site uses'machine learning', a type of artificial intelligence based on pattern recognition, to offer personalised content. The technology is now commonly used in consumer sites, such as Netflix and Amazon, but until now has not been used in the veterinary world. Content is further personalised for those vets and nurses that complete their profile on the site. The upgrade was commissioned after Boehringer carried out a user experience survey of its old website, which revealed that whilst vets appreciated the CPD and educational materials, many were trawling through content that was not of interest to them or struggling to find what they wanted. Jemima Mead, brand manager at Boehringer, said: "We aimed to create an engaging portal – a one-stop shop for vets who want to access high quality CPD and/or relevant information about any of our products. Vets are busy people so need to find relevant information quickly – giving them more time to focus on their clinical responsibilities. Our new slick site, tailored to their individual professional preferences, provides a valuable service that simply has not existed before."