Machine learning has been in development for some time now, with more than a few major players in the digital industry investing substantial amounts of time and money into its progress. For the most part it is open source and therefor available to anyone with the understanding to leverage upon it, and in this regard can be used for a wide range of applications which are limited only by a user’s imagination. Machine learning promises to usher in a new era of technology which will likely permeate through all areas of our global society and become a commonplace part of our daily lives. Though for any business owner, marketing manager or researcher who is currently active in their industries, there may come a time when an intimate understanding of what machine learning is, how it works and how it can benefit a range of processes becomes necessary for survival in a competitive market; so you may as well start familiarising yourself with the concept now.
What is Machine Learning?
In a nutshell, machine learning describes the earliest stages of artificial intelligence. It is a form of software that can adapt and make decisions independently, working from initial information fed to it by human users.
The term was first coined in 1959 by Arthur Samuel to describe a process by which a machine (in this case software) can be fed information, and then using it, can learn and adapt to meet a particular objective without the need for prior programming.
Now, brought back to life by innovators like Elon Musk, the concept which has been made open source through the power of the internet, has become a global community project that can be used for a wide range of applications. This has been made possible by projects like Deep Learning, which provides an open source platform for anyone interested in the technology to conduct research on it independently, thereby adding to its development.
So far, it has been applied and added to by combining its principles with a range of other practices; including gaming, marketing, data gathering and software development.
Where is Machine Learning Already in Use?
The big benefit to machine learning is its ability to process incredibly large pieces of information in very little time, and it can do so by independently pulling from a range of external sources once initial data has been used to determine its approach and directives. Because it can perform this task thoroughly and efficiently, it is being used to streamline a number of campaigns and strategies right now.
In terms of its continual development, constant research is being done in terms of its capability, often using popular games to test and push the capabilities of artificial intelligence and its decision making prowess.
Machine Learning and Gaming
As I mentioned above, machine learning owes much of its success to research conducted using game clients and partnerships with leading developers and publishers. The most notable example of this concerns a PC Game developed by Blizzard called Starcraft 2. It is an intensive resource management and space-centred strategy game; and as a strategy game provides the perfect groundwork for AI development.
But we have been playing games against computer programmes for decades now, so what makes machine learning so special? Well, where classic gaming AI or BOTS had to be given specific instructions on how they should behave under certain situations, machine learning allows programmes to adapt according to their own wishes. That means that once the programme has learnt to play the game, it will be able to enact any number of strategies that stay true to the game’s rules, independently of instructions initially given to it. This makes it less predictable, far more challenging, and a lot more like playing against a human (if humans could process an immense number of possibilities in a matter of split-seconds).
Machine Learning and Mobile App Development
Though not all of us are gamers, and so this news is only so exciting on the whole. On a more practical note, mobile app developers are using the principles of machine learning to develop smarter apps. Let’s start big. Consider Siri or Cortana and their ability to learn about their user’s search preferences over time. This is the result of machine learning. Navigation apps can learn to recognise areas, roads or traffic lights from images, and can even calculate traffic speeds depending on the information it fetches. Scores of productivity apps that learn the schedules and work habits of their users are also excellent examples of deep learning in apps; while more and more chat-bots (almost all of which would pass the Touring test) seem to come out each day.
Machine Learning and Marketing
Machine learning isn’t just being used for apps and games, but have been used to excellent effect in many a marketing strategy in the past year or so. Since the tech is still developing, however, it will likely take some time before it becomes a common part of the marketplace.
Still, marketing managers all over the world have been leveraging machine learning’s ability to process immense pockets of data and its adaptive data collection strategies to develop campaigns that are up to 20% more efficient.
Deep learning can be used to great effect when identifying target audiences in ways that are far more practical, cost effective and far reaching than traditional means. This type of software is able to glean demographics from a wide pool while still targeting those individuals who add value to your brand, or are more likely to make profit generating decisions based on their interests, likes and demographics. The point is that it can do this in an adaptive manner, and also in colossal quantities to sift through more data than even a team of human’s could to delimit the ideal target audience, where they will be found, and what type of content is most likely going to appeal to them.
What Does this Mean for the Future of Human Resources?
Now, I know what you are thinking, what does this mean my role will be in the near future. If an algorithm can do what I do better and at a fraction of the cost, then what chance do I really stand as the technology develops. Well, you will still be needed, so don’t worry. As impressive as machine learning is, it has no real way of using initiative. That is to say that it needs to be instructed towards a certain objective and fed the right information to get it started on its process, and this information still needs to be fed to the AI by a human participant who has set out and planned clearly determined goals. Artificial intelligence gets a lot of bad press over the fear that it will someday be our overlord, steal our jobs and eventually turn us into batteries. Since the tech has been developed as a tool which is still reliant on human input, it is about as likely as turning our world upside down as the calculator is, though stands to be just as revolutionary as a tool for our productivity.
Contact Applord Today
There are many ways in which this tech can be implemented, and at the moment it hinges on the imagination of innovative app development companies and software designers to give it more functionality. If you would like to know more about having an app developed that takes advantage of new and innovative technologies and techniques, contact a representative from Applord today, or visit our website for further details.
