Generative artificial intelligence : what is it ?

Artificial intelligence aims to emulate and even surpass human intelligence. The development of this type of intelligence is not new. In recent years, many industries have been using AI to help them perform certain tasks and operations. At the moment, generative AI is a concept that is increasingly present in our daily lives. It allows us to improve research and optimise the use of certain data. This is achieved through specific algorithms.

What is generative AI ?

Generative artificial intelligence is a concept that allows AI algorithms to exploit data and information that already exist in order to produce new ones. It is mainly used in the field of learning and through machine learning solutions and AI tools. The concept allows, among other things, to produce new data such as texts, images, sounds, and many others.

Generative AI will use stored information, either on the net or in a personal server, to generate new information. To produce a new (substantially similar) text, sound or image, it will do its own analysis and compilation of information.

Why is there so much interest in this type of AI solution ?

Today, generative AI is attracting interest in many industries. Examples of tools that use the concept of generative AI and that most of us can’t live without are ChatGPT and Midjourney. The first is a chatbot that allows you to do quick searches and get clear information by conversing with an artificial intelligence solution. ChatGPT is based on the data it collects on the Web in order to give precise information to the Internet user. As for Midjourney, it is a tool that can generate new images from those that already exist on the Net.

There are also AI solutions on the market that have the capacity to create new computer codes from those that already exist. The same applies to AI tools that can generate email content, music and even lyrical content.

The results obtained from these solutions are faster and clearer, and users are more than satisfied with their experiences. It is worth noting that ChatGPT had over one million users after its first week on the market. This result has aroused the interest of large companies such as Google and Microsoft. The latter have also entered the race to exploit the niche. Thus, with solutions such as Bing or Bard, these two Internet giants have also entered the artificial intelligence market.

How generative AI works ?

Generally speaking, generative AI allows data to be recorded. It will then analyze them in order to learn them better. The work of artificial intelligence does not stop there, it will also generate calculations by exploiting the data it has taken in knowledge. It will then use machine learning to develop solutions by responding efficiently to requests, demands or specific problems.

To ensure better performance, generative AI must be able to analyze a very high quantity of information in a minimum amount of time. This allows it to respond quickly to queries. This potential also opens the door to the possibility of surpassing human intelligence, which is limited.

Examples of growing market interest in generative AI

In many fields, more and more companies are interested in generative AI.

The health sector

In the health sector, pharmaceutical companies are using the concept of generative AI to manufacture medical prostheses. To do this, developers and researchers in this sector are combining it with 3D printing technology to manufacture different types of medical devices and even organic molecules.

According to the analysis of industry experts, by 2025, it is likely that more than a quarter of all drugs and medical devices will be discovered using this AI solution.

The visual production sector

Generative AI makes online meetings and conferences more collaborative and productive. It has the ability to improve the quality of images. AI can also generate more than realistic avatars. This solution has the ability to protect an individual’s identity when filmed.

It is also possible to do instantaneous translation with this solution and the concept of deep learning. This is the case with Google Translate. This type of AI can ensure the creation of texts that are difficult to differentiate from those produced by human intelligence.

Generative artificial intelligence and image creation

Researchers have developed AI tools that have learned to record, analyze and process existing images. Thanks to this learning and the concept of generative AI, they were able to create new images. During the learning process, it should be noted that the generative AI still needs human intervention to give it instructions through a precise text. The AI solution will then work on the image styles it has recorded, analyze and process them to generate a new one.

However, in order to perform this task, it is important for the generative AI tool to store and process a large quantity of images. This can be in the billions of images. Thus, the image that the AI will generate will contain a trace of the original work. In other words, the output from the work of the generative AI tool will not be able to be considered 100 % unique and entirely original. The same applies to articles and web content produced by the generative AI.

Generative AI: what are the drawbacks?

The first drawback of generative AI is the veracity of the information it provides. The AI system records and compiles a huge amount of information, which it will analyze to produce new data and information. However, this information is not always 100 % accurate. The generative AI does not yet have the ability to sort through it and eliminate the incorrect data.

You will also have no way of verifying the data it provides as there is usually no source for the information provided by an AI tool. This type of problem has already been seen with many AI tools such as chatbots, even the most famous ones of the moment.