Introduction: 

In a nutshell, machine learning is the field of computer science that revolves around equipping systems and software to passively learn existing data without requiring human intervention. Once a system or software has been equipped with ML, it can learn from the data that is available to it without constantly having to be given the commands to do it.

As we said, machine learning is one of the driving forces behind the advancement of online tools. In this post, we’re going to first understand ML itself in detail before looking at some examples of online tools and the role that ML plays in them.

Understanding Machine Learning: An Example

To give you an example of machine learning, the best online tool to talk about would be ChatGPT. ChatGPT is based on the GPT-4 model – which is said to consist of 1.7 trillion parameters.

To understand all the different topics that it knows and to familiarize itself with all the languages, etc., ChatGPT uses machine learning. In other words, it provides information/data in a structured form from the Internet (and other sources).

Then, the model utilizes machine learning to understand patterns from the given data even when it is not monitored or supervised.

Machine Learning and its Role in Online Writing Tools

To help you understand machine learning and its role in online writing tools, we will list a few common ones along with an explanation of how they are improved with ML.

1. Paraphrasing Tool

An AI-based paraphrasing tool is one of the prime examples of how ML plays a role in online writing tools. A paraphrasing tool is essentially made to reword and rephrase text – something that can be done by human writers and editors as well but is significantly quickened when done automatically.

When these tools rephrase text, they make different types of changes to it. They can, for example, change the words it originally contains and swap them with their synonyms.

In all the changes that it makes, there is a chance that the tool can go contextually wrong. In other words, it can make such changes that don’t reflect the way the content was originally written.

In such a situation, the paraphrased version can come out to be different from the original – which defeats the purpose of paraphrasing in the first place.

This is where AI steps in – ML in particular.

When paraphrasing tools are equipped with AI, they are able to understand the text deeply. They are able to determine the tone it carries, the meaning it conveys and the style that it subscribes to.

Then, they are able to specifically make such changes that don’t bother the original nature of the content.

This is something that ML plays a part in. With machine learning, paraphrasing tools are able to analyze their input text and learn from them to understand writing styles and patterns.

Once that happens, the tools are able to make smart and spot-on changes to the text with even extensive structural modifications without changing the meaning one bit.

To give you an example of this, here is an online AI paraphraser in action. You can see the input on the left side and the input on the right:

2. Grammar Checker

Moving on, another example of writing tools that utilize ML is grammar checkers. The main function of grammar checkers is fairly simple and straightforward. They scan and check the content they are given to spot grammar/spelling errors in it. Once they do that, they also provide suggestions to correct the errors.

In some situations, a grammar checker can flag as an error something that isn’t really one. For example, the words “with in” can appear separately and be grammatically correct, but a grammar checker may always point it out as a misspelling of the word “within.”

There are other similar situations in which a word or phrase is pointed out to be an error when, in fact, considering the context and surrounding content, it is completely fine.

To be this much discerning, grammar checkers have to utilize AI, and in particular, ML.

Using ML, grammar checkers can learn from the inputs they are given to see the different contextual applications of various words and terms.

Once they learn and get a better understanding, they can become more accurate in their checking process.

3. Plagiarism Checker

Plagiarismchecker.ai is a glowing example of ML’s impact on online writing. The tool uses ML to identify plagiarism/copying in the input content. It compares the writing against billions of pages available on the web. After the search, it highlights all the copied parts and shows its overall percentage. The software is also capable of identifying the main sources of duplication.

Finding plagiarism is critical for writers because uploading a plagiarized piece of work results in insult, defamation, and penalties. By highlighting it, plagiarism checkers aid writers in producing 100% unique content. 

Plagiarism has different types. It can be direct, accidental, mosaic, paraphrasing, and self-plagiarism. The advanced ML algorithms understand and analyze each input to identify the root of the problem. 

Quality plagiarism checkers are also multilingual. They can check content in all major languages of the world. The AI & ML joins in to produce quick and efficient results with no hiccups. Plagiarism Checkers are useful for students, researchers, bloggers, influencers, copywriters, social media experts, and other content creators.

What is the benefit of integrating ML in online writing tools?

The main benefit of using ML in any place or application is that it allows the tools to learn and improve itself indefinitely. When the algorithms are set in place, they let the tool keep on learning without requiring human effort.

Thanks to this, online tools can keep on improving their working passively while they are being utilized.

Conclusion

Having a good idea of machine learning and how it works in online tools can be beneficial. It can help you understand and appreciate the working of the tools that utilize it.

Oftentimes, tools use the term ML to convey their efficacy and quality – but it can be difficult to realize that if someone lacks the knowledge of what ML actually is.

The purpose of the post above was to help clear things up about how machine learning works and what benefits it provides to online tools.