Using Cognitive Computing to Humanize Computer Interaction
Every so often there is a fundamental shift in how we interact with “machines”. The era of cognitive computing is about to trigger a new shift.
It is easy to forget how far input devices have evolved since the first automated computing devices were introduced just over a century ago. Today we are all used to touching, swiping and pinching using our fingers, on the screens in order to interact with machines.
This move to touch was a radical shift from typing on a computer keyboard or using a mouse (more recent), which was the norm, since the first automated computing devices were introduced just over a century ago.
It is pretty amazing to think that today we use touch to interact with machines daily. We rarely give that a second thought. Touch has undoubtedly augmented existing interaction models and opened new possibilities. There are now many things where touch is simply the best method of interacting with a machine.
Despite the innovation it is a fact that we have still not been able to really humanize the experience of working with computers or machines.
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Deep Learning – what on earth does that mean?
Have you ever wondered just what this phrase Deep Learning is referring to and why it matters? If so then this post is for you!
In my last post, I demystified a variety of buzzwords, and explained that Deep Learning is a subset of Machine Learning. This post explores the world of deep learning for non-mathematicians (just like myself). In doing so it:
- Touches on convolutional neural networks;
- Explains the impact Deep Learning is having on Cognitive Computing;
- Outlines a few examples of Cognitive Computing (Deep Learning) in action.
Starting with Artificial Neural Networks
To understand Deep Learning, you must first understand a little about Artificial Neural Networks. Don’t worry – as I am not a data scientists I will not try to describe the mathematics behind it all. That means no talk beyond this sentence of weighting, activation functions and more.
Deep Learning normally revolves around the use of Artificial Neural Networks with more than 1 hidden layers. More on what a hidden layer is shortly. The theory is that the more hidden layers you have the more you can isolate specific regions of data to classify things.
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Exponential Times – Will Your Organization Adapt or Expire!
Digital transformation is either the worlds largest hoax or it is the most important single business modifier of our times. My opinion is that is no hoax. We live in exponential times and business model innovation tied to an ever increasing digital world is vital for organizations to adapt, survive and thrive.
Exponential Times refers to the fact that burying your head in the sand, while digital transformation occurs around you, and doing nothing is harmless until it is too late to react to sudden shifts in which case you face a fight to survive let alone thrive.
When I first show this image to people they think I am referring to the pace of technology change. No doubt technology is changing dramatically around us. What I am referring to though is the rate of business model change being enabled by rapidly shifting technology. For me digital transformation does not happen without business model innovation.
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