Lately, we have heard more and more buzz about the new term Machine Learning, and many companies are gaining interest in this new technology.
Thanks to the development of new technologies, systems have been improving and are now able to function autonomously without the need for human intervention, the main goal being, to have machines be able to learn on their own.
Machine Learning has created the possibility of the development of online applications such as chatbots that are responsible for generating answers based on language processing, or intelligent books that are capable of determining in which subjects a student needs more help, to vehicles that can practically drive themselves.
There is no doubt that this science is gaining a lot of momentum, but do we really know what Machine Learning is?
What is it and what can it do for us?
Machine Learning is a branch of artificial intelligence that gives computers the ability to learn without having to be programmed explicitly and in turn can essentially make decisions for themselves.
Arthur Samuel (1954) Machine Learning: A field of study that gives computers the ability to learn without being explicitly programmed.
This term has been used since the 1950s, however, only in recent years has it gained revelance thanks to the increase in computer capacity and the volume of data that companies have begun to manage.
What applications does it have?
Currently, automatic learning has a wide variety of applications, which continue to increase day by day. Here are some of them:
- Facial or voice recognition (We can see this on our mobile devices).
- Fraud Detection (Detecting fraud patterns in a business, based on its customer base).
- Search engines like Google and Bing, among others (Improving suggestions and search results).
- Anti-spam and virus detection (Used in the detection of malicious software).
- Autonomous vehicles (Uber, Tesla, Volvo, among others).
- Prediction and forecasts (Climate, vehicular traffic, etc).
- Genetics (Used in the classification of DNA sequences).
- Digital marketing agencies (Predictive Marketing or Neuromarketing).
- Analysis of high quality images.
- Pre-medical diagnostics.
All of these applications are used by thousands of companies, including the most relevant in e-commerce and technology such as Amazon, Microsoft, Netflix, Google, Spotify, and eBay, among others.
What impact has it had?
The advances of this great science have given us surprising results.
In the business sector, applications have been developed that can establish dates that specify when to raise or lower prices according to demand and that have come to estimate whether the pace of sales is at an optimal rate.
In the social network sector, Facebook has developed a system that allows us to detect whether content is too violent or contains images not suitable for all audience during live broadcasts and can automatically block this kind of content.
In Singapore they have developed a wonderful autonomous driving technology system adapted to wheelchairs, giving the patients the ability to move from one place to another without having to depend on another human being.
In the field of online marketing, software has been developed that allows us to create personalized online campaigns based on user data, following their navigation patterns and purchases.
The techniques and applications in which Machine Learning is being used are growing considerably. From the technology that Google uses in its search engines, voice recognition, facial recognition, movie recommendations from Netflix, to Uber's automatic driving technology.
All of us interact with automatic learning while it complements our daily activities. We are in an era where opportunities are increasing at the same rate that algorithms are learning.
While technology giants continue to offer companies services and solutions that will help them solve a myriad of challenges in their business, Machine Learning has become a step further towards Artificial Intelligence.