In 2012, Harvard Business Review named the data scientist the sexiest job of the 21st century. A few years ahead, in 2016 Glassdoor named it the best job of the year. Why I bring this up? Data Scientists are professionals skilled at utilizing Machine Learning. The who is who of technology companies in Silicon Valley and abroad such as Google, Amazon, Apple and Microsoft have relentlessly focused on utilizing machine learning and related technology to improve their products and services or even come up with new digital products built on top of machine learning algorithms. You see a trend here? Machine learning is big, its growing and it’s here to stay.
Can you remember your days when computers did not exist? I remember my first computer many years ago, it was a Macintosh and all I could do was play some games. As computers became mainstream they changed the world. The internet vastly improved the tasks that computers could do by connecting all of us. Now, Machine Learning will exponentially improve the tasks that computers can do.
Computers perform tasks was through a series of instructions that a programmer would implement. This would follow explicitly defined logic. If this then do that that type of logic. This, of course, has limits to what can be accomplished. As an example imagine you want a computer to purchase apples for you. And you want the apples purchased to be just like you like them, maybe you like the red apples, crispy and just ripe for eating. For a computer to do this you have to write all the logic for the computer program to determine what is red, what is crispy, what is ripe. It would be too many lines of code and probably logic that you wouldn’t even know how to define for the computer. Now, through machine learning, you could show the computer many images of apples each one classified as Yes or No I don’t like and the computer would LEARN to identify the apples that you like and those that you don’t. Instead of programming all the logic, you would program the algorithm that would learn a task by itself, this in essence is machine learning.
"Machine Learning is a field of computer science that gives computers the ability to learn without being explicitly programmed to do so." Wikipedia.
This, my friends, will be a game changer. Some of the algorithms being used in machine learning are not new. The perceptron, an algorithm which served as the inspiration for state of the art algorithms used today, was invented in the 1950’s. Today, the world is much different. The internet connected us all. Data is being captured at incredible rates. Processing power and storage are much cheaper and scalable. We have come a long way since my first apple computer. The interconnection of data and processing power will give rise to the promise of AI through machine learning algorithms.
The impact will be vast and the change will be great. Some have come to fear what this could bring to the world while others are embracing it and preparing the regulatory environment to protect us citizens. Governments see it as a tool for world domination.
“The nation that leads in AI ‘will be the ruler of the world.” Vladimir Putin
“China, Russia, soon all countries with strong computer science. Competition for AI superiority at national level most likely cause of WW3 imo.” Elon Musk.
Machine learning is one of the most popular approaches to achieving AI. It has the power to change the world and it is at our fingertips through hard work, vision and dedication.
InsightsBot was created to help disseminate machine learning knowledge. Our name comes from what we believe to be the way of the future, insights using bots, i.e. computer programs. These insights drive actions that create value.
Here at InsightsBot we believe the way of the future is insights through bots, i.e. computer programs. These insights drive actions that create value.
In order to successfully implement Machine Learning one needs a combination of skills such as computer science, programming, data management, business knowledge, curiosity and inquisitiveness. At InsightsBot we plan to touch on all of these to help you on your quest for machine learning knowledge.