Computers had been designed and used to make tasks easier for humans. However, that required large amounts of algorithms to be written. The functions of the computers were based on these algorithms which made the outputs predictable and limited. If computers were to be used for something, a series of elaborate algorithms were required. Any new addition to the functions had to be accompanied by the algorithms and the algorithms had to be updated frequently. To overcome this shortcoming, such algorithms were created which could identify the instructions, analyze the sample and learn from them. This is known as Machine Learning.
A New Race Of Intelligent Species: The Computers
With the increase in the available data size, Machine Learning has become more and more adept at mimicking the cognitive actions of humans. In layman terms, it allows the computers to think by themselves without much human assistance. This is possibly the major reason why machine learning is being introduced across various public domains to help in several tasks. In the future, the innovations in Machine Learning is slated to be introduced in almost all the industries and allow the computers, devices as well as software to make decisions based on the analysis of historical data and their outcomes.
The Advent of Machine Learning
Let’s look at a few innovations in machine learning and how they have the potential to affect us:
- Creating Autonomous Devices: It is a known fact that devices have better accuracy and consistency than humans. Which is why Machine Learning is being used to create a range of devices which would have an autonomous nature. That is, they would be able to function without human assistance. Currently, Machine Learning is being used to develop self-driving cars, which would result in around 90% decrease in traffic-related problems and accidents, once it is widely adopted. In addition to this, Machine Learning can also be included in other devices, such as medical devices which can be used to perform surgeries in an accurate and efficient manner. In addition to surgeries, Machine Learning can also be used to detect medical anomalies in patients. It would make healthcare more accessible across the world. Machine learning can also be used as a part of the military strategy to conduct surgical strikes or drone strikes.
- Cybersecurity: With the huge involvement of the computer and network systems in the day-to-day functions of various industries and the lives of billions of individuals, cyber attacks are among the top threats. Every day, millions of cyber attacks are carried out in the forms of email phishing attacks or ransomware attacks. These methods keep on evolving. Though there are a number of software to protect the individuals and organizations against these attacks, this can only protect against those attacks which are already identified. Any new form of attack requires a new patch to be developed, released and adopted, which suffers from a significant time lapse. With the help of innovations in Machine Learning, the software can identify the new attacks with as much as 10% variation and protect the systems against these attacks. They are also capable of including the new forms of attacks into their database and modify their parameters accordingly.
- Predicting Consumer Trends: Machine Learning can predict future trends based on historical performances and outcomes by analyzing a series of data samples. This ability can be used in the retail markets to analyze the consumer behavior patterns and would be profitable for companies, as by predicting the future trends of consumer demand, they enable the companies to modify the supplies accordingly. It would also help in the pricing of the products based on the projected demand and supply. Moreover, with the help of the predictions of Machine Learning, the companies can also introduce new products, penetrate new markets, launch new offers and discounts, and take many such steps to gain a strong foothold in the market. The drawback of this ability is that companies can create artificial scarcity to increase their profits or Governments can levy taxes or give subsidies on the products based on differential pricing strategy to manipulate the consumption patterns.
There are several companies trying to expand the uses of the innovations in Machine Learning and introduce it among the various public domains to deal with the problems in an efficient, quick, and accurate manner, free of human errors and inconsistencies. But as with everything, there is also the chance of Machine Learning being used to do more harm than good. We have to remember that at the end of the day, Machine Learning is actually developed by a series of coding and algorithms, and evolves by analyzing historical data and their outcomes. By manipulating these algorithms or data, there is it chance that, in the wrong hands, machine learning would be detrimental to the people.