Finding your way

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Millenials have been classified as being those born in the early 1980s to early 2000s. Is this you?

The millennial, or ‘jilted’ generation make up a quarter of the UK’s population, and yet they are frequently derided as narcissistic, tech-dependent and lazy. But are these epithets fair? They are the first generation to do worse than their parents, and many graduated into a climate of joblessness, extortionate housing costs, and instability.  Bestselling leadership expert Simon Sinek explains how we can help millennials become the confident future custodians our society desperately needs.

There is a Japanese expression that goes “Generalisations are seldom accurate” To lump a whole generation as having certain characteristics seems harsh. “Are they useful” would seem to be the criterion by which this can be judged. We use generalisations to help us make sense of the world they are also a cognitive dissonance trap which is not good. If I meet a vibrant witty go getter millennial I have to change my world view of millennials or deny the reality of exceptions. I take great comfort in [Paraconsistent Logic]( which enables me to hold opposing views without dissonance much like our dear friend Schrödinger did.

When we meet a person how much of the real person shines through for us or do we just superimpose stereotypes which in many ways can be very damaging. We have talked about trust here. I tend to trust people automatically until proven wrong. I am of the view that “good” is a natural occurring phenomenon. In training magistrates as part of my work in the probation service I used to quote Goethe :

> “If you treat an individual as he is, he will remain how he is. But if you treat him as if he were what he ought to be and could be, he will become what he ought to be and could be.”

If you are feeling a bit stuck why not start a blog? It is a great form of self expression and some even make money from it. Does your company have a blog and do you want to learn how it works? Start a WordPress blog. Its a great skill to add to your CV. Also in all those application forms where you have left “Website” blank can now be filled.

Blogging can be about anything or everything and can be your public face on the Internet. You can make contact with like minded individuals. Share ideas, share stories, share experiences. You have a voice on the Internet and even if only one person listens you have done a good job.

Have a look around the Internet for blogs that might interest you, there are sure to be some. Below is a contact form that you can fill out, comment about anything.


The Artificial Intelligence Revolution: Part 2 – Wait But Why

  • As mentioned in Part 1, movies have really confused things by presenting unrealistic AI scenarios that make us feel like AI isn’t something to be taken seriously in general. James Barrat compares the situation to our reaction if the Centers for Disease Control issued a serious warning about vampires in our future.5
  • Due to something called cognitive biases, we have a hard time believing something is real until we see proof. I’m sure computer scientists in 1988 were regularly talking about how big a deal the internet was likely to be, but people probably didn’t really think it was going to change their lives until it actually changed their lives. This is partially because computers just couldn’t do stuff like that in 1988, so people would look at their computer and think, “Really? That’s gonna be a life changing thing?” Their imaginations were limited to what their personal experience had taught them about what a computer was, which made it very hard to vividly picture what computers might become. The same thing is happening now with AI. We hear that it’s gonna be a big deal, but because it hasn’t happened yet, and because of our experience with the relatively impotent AI in our current world, we have a hard time really believing this is going to change our lives dramatically. And those biases are what experts are up against as they frantically try to get our attention through the noise of collective daily self-absorption.
  • Even if we did believe it—how many times today have you thought about the fact that you’ll spend most of the rest of eternity not existing? Not many, right? Even though it’s a far more intense fact than anything else you’re doing today? This is because our brains are normally focused on the little things in day-to-day life, no matter how crazy a long-term situation we’re a part of. It’s just how we’re wired.

What an awesome site a must read for all AI peeps.

Deep Learning

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Deep learning is the use of many hidden layers in an artificial neural network to train a model to learn and understand the data without an inherent understanding of the data. Deep learning is used by many different disciplines to allow computers to learn from vast amounts of data. Recent advances in computer vision, object detection and natural language processing can be attributed to the adoption of Deep Learning techniques.

From wiki :

Deep learning (also known as deep structured learning, hierarchical learning or deep machine learning) is a class of machine learning algorithms that:

  • use a cascade of many layers of nonlinear processing units for feature extraction and transformation. Each successive layer uses the output from the previous layer as input. The algorithms may be supervised or unsupervised and applications include pattern analysis (unsupervised) and classification (supervised).
  • are based on the (unsupervised) learning of multiple levels of features or representations of the data. Higher level features are derived from lower level features to form a hierarchical representation.
  • are part of the broader machine learning field of learning representations of data.
  • learn multiple levels of representations that correspond to different levels of abstraction; the levels form a hierarchy of concepts.

In a simple case, there might be two sets of neurons: one set that receives an input signal and one that sends an output signal. When the input layer receives an input it passes on a modified version of the input to the next layer. In a deep network, there are many layers between the input and the output (and the layers are not made of neurons but it can help to think of it that way), allowing the algorithm to use multiple processing layers, composed of multiple linear and non-linear transformations

More to come……

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