Data mining isn't a new invention that came with the digital age. The concept has been around for over a century, but came into greater public focus in the 1930s. According to Hacker Bits, one of the first modern moments of data mining occurred in 1936, when Alan Turing introduced the idea of a universal machine that could perform computations similar to those of modern-day computers. Forbes also reported on Turing's development of the "Turing Test" in 1950 to determine if a computer has real intelligence or not. To pass his test, a computer needed to fool a human into believing it was also human.

Data mining isn't a new invention that came with the digital age. The concept has been around for over a century, but came into greater public focus in the 1930s. According to Hacker Bits, one of the first modern moments of data mining occurred in 1936, when Alan Turing introduced the idea of a universal machine that could perform computations similar to those of modern-day computers. Forbes also reported on Turing's development of the "Turing Test" in 1950 to determine if a computer has real intelligence or not. To pass his test, a computer needed to fool a human into believing it was also human.

This type of approach is extremely versatile, and allows manufacturing teams to visualize large design projects through miniature scale models, design and create small runs of custom parts and equipment for customers and prototype new products. As 3D printing speeds increase, Gartner predicts the 3D printing industry will be a $4.6 billion market by 2019. Until now, the primary application for 3D printing in discrete industries has been prototyping new parts and equipment, but there's significant room for expansion, especially in the efficient fabrication of spare parts. Most discrete manufacturers are already producing spare parts, but few have adopted tactical 3D printing as an update to their process. The lead time currently required to create many spare parts can be both long and expensive, so the only way to ensure these parts are available to the customer in a timely fashion is to create and store them in advance.

Data mining isn't a new invention that came with the digital age. The concept has been around for over a century, but came into greater public focus in the 1930s. According to Hacker Bits, one of the first modern moments of data mining occurred in 1936, when Alan Turing introduced the idea of a universal machine that could perform computations similar to those of modern-day computers. Forbes also reported on Turing's development of the "Turing Test" in 1950 to determine if a computer has real intelligence or not. To pass his test, a computer needed to fool a human into believing it was also human.

I love it when I get feedback from a blog that I've written. I appreciate the different perspectives and insights that others bring to a topic of interest. And no blog that I've written has drawn more comments than my blog, "Isaac Asimov: The 4th Law of Robotics." The section of the blog that fueled the most comments stem from a scene in the movie I, Robot where Detective Spooner (played by Will Smith) is explaining to Doctor Calvin (who is responsible for giving robots human-like behaviors) why he distrusts and hates robots. He is describing an incident where his police car crashed into another car and both cars were thrown into a cold and deep river – certain death for all occupants.

What will the future of manufacturing be like? Imagine needing a new part for a household appliance. You could order it, get it made locally and get it delivered to your door within a couple of hours. Advances in 3D Printing and additive manufacturing will reduce waste even more, making it possible to create products and components that we can't make now. Everything will be connected by the Internet of Things to ensure that supply can keep track of changes in demand. Robots will take care of the repetitive, dangerous processes so that people can focus on matters where human interaction is so valuable.

These two Cat 793Fs are part of the autonomous mine truck fleet now at work globally. Cat says there will 100 such trucks working by the end of 2017. Imagine a time in the very near future when your hand-held concrete drill contains the entire layout of a job in its CPU and guides you to exactly where the holes need to be drilled. You never have to measure or use a chalk line or set the depth of the drill. It knows where to drill, how deep and everything it needs to know about the job.

The UN has warned that robots could destabilise the world ahead of the opening of a headquarters in The Hague. The centre's role is to monitor activity and developments in the field of artificial intelligence. So, the UN will monitor the risk of mass unemployment to the deployment of autonomous robotics by criminal organisations and/or rogue states. Consequentially, the new Centre for Artificial Intelligence and Robotics has been set the goal of second-guessing the possible threats. This, the rise of the robots, has the potential for disaster to societies and nation states across the globe.

Remember how just five years ago it seemed like 3D printing was going to take over the world? How it seemed like we'd have 3D-printed cars that we'd be parking in our 3D-printed houses? Things didn't seem to work out so much. But even while the hype died, companies have been steadily working on the technology. Two years after MX3D announced a plan to 3D print an entire steel bridge designed by Joris Laarman, the project really is going forward, with anticipated completion sometime next year.

IT personnel must pay very close attention to 3D printing for two main reasons: It will change how the organization for which they work operates and how they will do their own jobs. The technology has been here for quite some time, but it is increasingly stunning. It continues to change and grow in capabilities. For instance, nanowerk reports on research published two weeks ago in Advanced Materials that describes 3D printing of electronics. This hybrid method – which combines direct ink writing (DIW) with automated pick-and-place of surface mount electronic components within a single manufacturing platform – enables surface mount electrical components of arbitrary shapes and sizes to be readily integrated onto printed soft wearable circuits.