What Does Generative AI Mean and What Are Some of Its Applications

What Does Generative AI Mean and What Are Some of Its Applications
27 Jan 2022

We have all witnessed the power of artificial intelligence, as it has made its way through major industries, transformed business processes, improved organizations’ workflow efficiency, and overall, positively affected our lives. However, recently, a new term has come into play, and that term is “generative AI”. Quickly becoming a true buzzword, generative artificial intelligence has made the headlines and attracted the attention of specialists, who recognized its potential and included it in lists of top upcoming trends and emerging technologies. So, let’s see what exactly has made experts display such a growing interest in this type of artificial intelligence, and to start things off, allow us to briefly define the concept of generative AI.

What is generative artificial intelligence?

What Does Generative AI Mean and What Are Some of Its Applications

Generative artificial intelligence can be viewed as an enhanced and upgraded form of AI, which no longer limits itself to interpreting or analysing data, but goes beyond these capabilities, enabling systems to generate new content. What is this new content that we are speaking about? Well, generative AI is able to create everything from digital images, text or code, to video and audio files, with the help of unsupervised learning algorithms. By means of the latter, computers are capable of determining and understanding the fundamental pattern associated with the input, and then harness that, in order to generate artificial content.

In other simpler words, productive artificial intelligence, as some specialists have also named generative AI, offers systems the ability to use pre-existing information, in the form of images, audio files, or texts, with the purpose of producing new similar data. But let’s explore some of the use cases for generative artificial intelligence, to have an even better understanding of the emerging technology.

These models use deep learning techniques such as neural networks and reinforcement learning to learn and generate new data. Generative AI has a wide range of applications, including art, gaming, music, and storytelling. It has the potential to revolutionize the way we create and interact with content, as well as drive innovation in various industries.

Applications of generative AI

Generative artificial intelligence has numerous applications, some of the most widespread uses for the technology consisting of those related to images. In this sense, with a bit of help from generative AI, systems are capable of converting a black and white image to a coloured one, a photo to an artistic painting, or even a descriptive text to an image. This technology is also used in images and movies’ restoration, assisting those who resort to it, in generating clearer, more vivid images and higher quality videos.

And it doesn’t stop here, important industries have also become interested in the capabilities of generative AI, and healthcare makes no exception. The medical world has found that generative artificial intelligence can help specialists in coming up with better treatment plans, by using the innovative technology in the process of diagnosis. And a more accurate diagnosis is not all that generative AI can assist specialists with; when combined with other tools and technologies, such as 3D printing and tools for editing genomes, generative AI can be used to render prosthetic limbs or organic molecules.  

Pros of generative artificial intelligence

As we have seen earlier, generative AI benefits various industries, that have already begun to adopt this technology, so that they can enjoy its perks. Patients can take advantage of a more accurate diagnosis, and thus a more efficient treatment plan, financial institutions and banks’ clients benefit from increased security, as generative AI-powered systems are able to identify fraudulent or suspicious activities promptly, and the perks just keep on coming.

Generative AI comes bundled with fewer risks, an improved quality in terms of outputs, and a better understanding of abstract concepts, when it comes to machine learning models, that can help predict future trends. However, as we will be revealing in the following, generative AI has its limitations, that those who are considering integrating the technology, must be aware of.

Cons of generative artificial intelligence

Despite offering numerous advantages, generative AI can also bring along quite a few challenges; systems may generate unsatisfactory results, that are difficult to interpret, while those with malicious intentions might use the technology to engage in fraudulent activities.

At the same time, productive artificial intelligence could fail to live up to users’ expectations, given that generative AI algorithms are unable to create completely new content, and require vast amounts of information and training data, in order to complete the tasks that they’ve been assigned with.


The new and improved version of artificial intelligence that is generative AI, has taken industries and businesses by storm, as it has been successfully applied across various fields. Healthcare, finance, and media and entertainment are just some of the areas that have embraced the emerging technology, and more and more spheres are starting to enjoy the wonderful perks that generative AI has to offer.

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