7 Machine Learning Trends Emerging Right Now

Machine Learning Trends Emerging Right Now

Seeing machine learning become more prominent should not come as a surprise. AI functions offer a lot of great things, and the ongoing pandemic made even more businesses invest in ML and automate some of the processes.

The future promises to be quite bright for machine learning, but it is also important to indicate that the industry is ever-changing. It is hard to imagine such technology surviving if it becomes too static.

ML trends come and go, but there are a few that seem to have established themselves, particularly in certain industries.

Let’s take a look at some of the trends that have been emerging recently.



Cybersecurity seems like a good way to start. Potential threats loom even if you are a simple individual on a computer or a mobile device. And cyberattacks are a common occurrence for businesses that need to invest in security.

From simple things, such as knowing how to add password to zip file and using different passwords for multiple accounts, to more complicated matters, such as server-wide security systems, it is crucial to create a proper cybersecurity strategy.

AI and machine learning come in handy as they analyze and process external sources using an algorithm to identify suspicious patterns. On the surface, cybersecurity breaches can seem random, but involving AI helps identify certain issues and be more efficient at dealing with them.


The Metaverse

People who are interested in technology must be aware of the metaverse and what it means to the future of the internet. Sure, Facebook is not doing that hot right now, but Mark Zuckerberg is still confident in his vision.

It is expected that artificial intelligence will play a prominent role in creating a virtual world in the metaverse. Virtual AI bots will function as assistants to help users relax and unwind themselves after a long day at work.

The idea of such assistants will likely be similar to what we have with the likes of Siri and Alexa, though it is also likely that the AI in the metaverse will be more advanced.


Lack of Code

One of the biggest obstacles holding AI technology back is the lack of experienced developers and engineers.

Fortunately, this drawback can be circumvented via no-code and low-code solutions. One of the best examples of that would be website builder tools that do not require excessive programming knowledge.

Users can simply drag and drop different graphic elements. Customization can then be carried out with the help of various plugins and extensions. Ready-made modules are a step in the right direction.

Some experts predict that we should have systems that are complex enough to follow written or audio instructions in the future, which should make the lack of code applications even more common.


Workforce Modifications

One of the biggest concerns about AI and machine learning in the workforce was about how it will take our jobs.Well, if you were to take a look at the current trends, the situation is actually the opposite. If anything, these technologies are of great help to workers.

For instance, it becomes much easier to make marketing decisions when you have algorithms processing vast amounts of behavior data from potential customers. Or what about engineers? Predictive maintenance is another area where machine learning offers a lot of value.


Internet of Things

The Internet of Things can be considered its own technology or industry, but it is difficult to separate it from AI and ML completely.If anything, the idea is that these three will connect closer in the future. We can see examples of that happening right now.

IoT is about different devices connected to the same network (the internet), and exchanging information via communications between these devices results in a lot of data. Data that needs to be addressed and processed carefully to get the desired results.

For example, if a city wishes to research vehicle emission rates and determine how to tackle the problem, it will require creating a complicated system and utilizing available technology, including the Internet of Things and machine learning.



Chatbots are perhaps one of the go-to examples when it comes to understanding how far artificial intelligence and machine learning have come.

Most online stores have a customer support section, and one of the departments of the section includes live messaging on a website.

Whenever a customer has a question or runs into a problem, they often send a message to customer support directly on the website and wait for a response.

If it is a real person working the desk, there are no guarantees that a customer will get an immediate response because the rep might be away from the keyboard or have other customers they need to help.

Well, a chatbot solves this problem. More and more shops are implementing chatbots to replace real people in customer support.

Chatbots are available 24/7 (so long as there are no issues with it), and they respond immediately after receiving a query from a customer.

Of course, there is a plethora of different questions and problems that could arise, so being skeptical about a chatbot completely replacing a real person is understandable. However, if there is one thing that AI and ML have shown over the years, it is how fast they can adapt and learn, which includes chatbots.



Integrity should not be underestimated when it comes to AI and ML. The civilized world does not want to see an Orwellian scenario in reality.

There have been many concerns about how some countries are using facial recognition and other tools to track people. It is understandable when such technologies are utilized for the good of humanity (take police work, for instance), but the odds are that they could fall into the wrong hands and be put to bad use.

As such, it is crucial for companies to be mindful of ethics when they are adopting AI. Small problems can snowball and cause risks to the brand’s overall image, not to mention troubles with the law.

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