If we look at the structure of technology, then machine learning definitely falls as a subset of artificial intelligence. Machine learning generates algorithms that help machines to get a better understanding of the data and take data-driven decisions. For instance, software testing is a classic example of implementation of machine learning in many organizations, including the likes of giants such as Google, Apple, Facebook and soon.
According to some analysts, they are anticipating that machine learning will gain immense popularity by 2024, with the maximum thrust in 2022 and 2023.
Why was machine learning technology developed is something that is quite technical in nature, but the fundamental reason for the development of this technology was to create a method that will help developers and IT professionals in quickly generating applications and solutions. Hence, this technology was developed to ease the job of testers who were working on large volumes of variables., which probably is out of range of a human capacity. As a result of these machine learning tools, the possibility of getting accurate answers was higher and professionals were able to analyze the answers correctly and derive the right conclusions.
Subject to this tool, artificial intelligence has an opportunity to create its own set of neural networks. This essentially means that it gives the AI model to create a replica of a human brain. This kind of a model helps in gaining experience and removes any sort of ambiguity and mistakes in the future.
Machine learning’s primary objective is to eliminate totally or partially any sort of human checking. This further enables the testers to completely automate any sort of complex analytical process. Thus, we can say that machine learning is used for making accurate predictions.
Usage of machine learning covers multiple areas, domains and activities. Machine learning used cases can be seen in sectors such as banks, restaurants, manufacturing units, and even gas stations.
Let us look at some of the upcoming machine learning trends in the year 2022 and beyond, when it comes to machine learning technology.
1. Internet of Things and Machine Learning
The first and foremost machine learning trends where most of the tech professionals are eagerly waiting for this particular trend. A development in this space will have a significant impact on 5G adoption, becoming the fundamental for IoT. As 5G has tremendous network speed, devices will be able to receive and transfer information at a faster rate. Through IoT devices, other devices on the network can be connected using the internet. Every year we see a huge surge in the usage of IoT devices that are being connected to the network, causing a proportionate rise in the amount of information that is exchanged.
2. Automated machine learning
By implementing automated machine learning, professionals can develop efficient tech models that help in improving productivity and efficiency. As a result of this, we will see most of the developments happening the area of efficient task solving. AutoML is essentially used to create highly sustainable models that can help in deriving work efficiency, in development space, where professionals can develop applications without much of programming knowledge.
3. Improved Cybersecurity
With the advent of technology, most of the applications and appliances have become smart, with a considerable progress in the technology. However, since these smart appliances are constantly connected to the internet, there is a pertinent need for having increased security for these appliances. With the use of machine learning, tech professionals can develop anti-virus models that can stop any potential cyber-attacks and minimize the threats.
4. Ethics in Artificial Intelligence
With the development of new technologies, such as artificial intelligence and machine learning, there comes a serious concern of defining some ethics around these technologies. More modern the technology, ethics should be modern as well. Absence of these ethics will result in machines not able to work efficiently and ultimately leading to wrong decisions. This is quite evident in the self-driven cars that we see in the market today. The failure of the self-driven car is due to the failure of the inbuilt artificial intelligence, which is the core of the car. If you do a root cause analysis, there are two primary reasons for this failure
- Developers are very much biased when it comes to selection of data. For instance, they use the data where most of the factors are in favor.
- Most of the machine learning models fail because there is a dearth of data moderation techniques
5. Automation of natural speech understanding process
We are seeing lot of information been shared on smart home technology, which technically works on smart speakers. Because of usage of intelligent voice assistants such as Google, Siri and Alexa, the process is relatively simplified, and it establishes a connect with the smart appliances through a non-contact control. These programs already have high accuracy in terms of recognizing human voices.
Gone are the days where the above process was executed through a series of commands and strict syntax framework. Today, machine learning is the answer this requirement and it executes the process relatively faster.
6. General Adversarial Networks
General Adversarial Networks, also known as GAN, considered as the upcoming machine learning trends which generates samples that must be checked by networks that are discriminative in nature, and that can eliminate any sort of unwanted content. Just like government has multiple branches, GAN helps in accuracy and reliability by providing checks and balances.
Innovation is the key for businesses to achieve their goals and they should find new and unique ways to leverage technology for the same. Machine learning is the future, and every organization is adapting this new breed of technology.
Final Thoughts
The objective of designing machine learning was to help in things like making accurate predictions. The technology helps various personas such as marketers, IT employees, and business owners. With the help of machine learning technology, these personas can make informed decisions and create new solutions or products. Ever since Artificial Intelligence has been involved, the machine has the ability to learn, memorize, and generate accurate outcomes. With the mention of these machine learning trends, which are of course anticipated ones, machine learning will always be moving in an upward trajectory.
