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.
Continue reading Deep Learning – What is it and why does it matter?
Artificial Intelligence (AI) – Demystifying the latest buzzword
Everywhere you turn today someone is talking about Artificial Intelligence (AI). It appears to have taken over as the largest buzzword since Big Data.
Progressive organizations are actively seeking ways to apply AI. They want to use it to advance their businesses and build new experiences for those they interact with internally and externally.
Alas there is great confusion as to what AI means. That just gets worse when people mix that up with terms such as Machine Learning and Deep Learning. If you ask several different people their view on what is AI, or Machine Learning, you will get several different answers.
It is the age-old problem of describing an elephant dependent on which side of it you touch while blindfolded.
AI is not a new topic. People have been pursuing AI since the 1940s. Machine Learning, which has developed from the field of Artificial Intelligence, has been around since at least the 1980s and Deep Learning, which is a subset of Machine Learning, has been rapidly gaining in popularity over the past 10 years. This post explores all these topics setting the scene for some upcoming posts.
Continue reading Artificial Intelligence (AI) – Demystifying the latest buzzword
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.
Continue reading Exponential Times – Will Your Organization Adapt or Expire!
Social Media. It can be a daunting world to the newbie. Fear abounds as people consider if they should engage or not. This fear is significantly intensified if the engagement is in a corporate context where people worry a mistyped line can result in the elimination of their job.
The fact is that today most people should be engaged in Social Media with guidelines helping them understand the rules of engagements to avoid getting themselves into a tough situation. Most organizations have now established social media guidelines/policies but that is where the help often stops. It feels like the aim is to control rather than encourage.
This is why, back in August, I wrote this post focused on “How to get your most valuable resources engaged in social media
“. That post shared a framework through which a person can move as they go on their social media journey. It can be adopted by an organization and used by individuals to determine where they are comfortable on the platform.
The framework covers being a content sharer via Twitter and LinkedIn. As a result I shared a post containing “15 points for the twitter beginner
” which reflects the advice I gave to people stepping out into the world of Twitter for the first time as a content sharer.
In this post I move beyond being a content sharer to the broader content creator space. I focus on the 10 tips for first time bloggers which I shared with people as they went on their journey towards being socially engaged. Nowadays this applies to the LinkedIn publishing platform, corporate blogs and personal blogs.
All of these posts have been part of a series that shared my experience as I tried to get people to be socially engaged in this modern world of social media and social selling. Getting people socially engaged in your organization will drive great benefits and great knowledge sharing.
I am very interested to know if you have other hints and tips so please feel free to share them in the comments.
Continue reading 10 tips for first time corporate bloggers
I come from a world of Analytics and Business Intelligence. A world where we mostly take transactional information generated by various operational systems, and more recently sensors, such that we can try to understand the past, predict the future and then take actions where necessary to affect the future outcome.
In that world we try to understand and predict, through analytics, things such as which employees are likely to leave next, understand which customers are likely to churn as they undertake their journey with the company and understand which customers are likely to abandon their shopping cart. In all these cases we are trying to spot things early such that we can take proactive action to prevent the predicted outcome occurring, where it makes sense to intervene, through the use of analytics.
There is no doubt that Analytics can help you understand what is likely to happen next, and who it might affect, such that you can take proactive action. One question often still remains and that is WHY? The Why is important as it lets you attack issues at the source not just be focused on dealing with the symptom.
- Why is it that a customer is thinking to churn or has churned?
- Why is it that an employee is thinking to leave or has left?
- Why is it that a customer decides to abandon their shopping cart or abandoned it?
- Why is it that one part of a process seems to run slowly no matter how you optimize it?
Continue reading Enterprise Feedback Management – Your Next Competitive Edge?