If you follow the tech news, you have probably heard of tools like ChatGPT and Dall-E. They are examples of a technology called Generative AI, which is capable of autonomously and creatively generating content. These resources are gaining popularity due to their ability to create not only text but also audio, video, images, and even code.
The fact is that this technology is here to stay and will drastically change the way we interact with the internet and create content on it. Therefore, it is essential to delve deeper into its workings and understand the limitations surrounding Generative AI. Keep reading and learn with BIX!
As mentioned before, Generative AI is a subfield of Artificial Intelligence that uses algorithms and machine learning models to generate data independently. In this sense, it has the potential to revolutionize how we create and interact with digital content, opening up new creative possibilities and transforming the way we think about the relationship between humans and machines. The difference between Generative AI and traditional AI applications lies in its ability to create something new – hence the name ‘generative’.
We can see applications of this technology in art, design, music, gaming, image processing, and many other fields. In the legal domain, for example, Generative AI has been widely applied in developing legal opinions and petitions. It can even enhance accessibility for people with disabilities! However, let’s take it slow: later on, we will discuss applications in various areas and the real world in more detail.
With so many potential uses, the power of Generative AI is reflected in numbers: it is estimated that 10% of all data generated by 2025 will come from this technology. Moreover, to give you an idea, the ChatGPT – a chatbot capable of answering questions and assisting in problem-solving – reached its first million users in just five days! For comparison, Netflix took three and a half years to reach the same milestone. In other words, as we mentioned at the beginning of this text, everything indicates that Generative AI has become popular for good.
The foundation of Generative AI lies in neural networks, which are structures composed of interconnected nodes – symbolically similar to our neurons, although involving a lot of mathematics. These networks can identify patterns in large datasets, leading to the generation of original information and content.
Neural networks form the basis of Machine Learning and Deep Learning models. Both use algorithms to process a large amount of data, such as images, code, and texts, among others. The training of these networks occurs through adjustments to the parameters and weights of the connections between the aforementioned nodes. As a result, there is less discrepancy between the desired and predicted outputs, enabling neural networks to learn from mistakes and make more accurate predictions.
To delve a bit further into the subject, let’s talk about one of the most commonly used models within Generative AI: Generative Adversarial Networks (GANs). GANs employ two distinct neural networks – the generator and the discriminator.
Now that you understand the origin and creative potential of Generative AI, let us show you some practical applications of this technology. Here we go:
Applications and Websites
Whether through ChatGPT, the Lensa app, or the powerful Synthesia website, you have probably been introduced to Generative AI by one of these online platforms. They went viral in late 2022 and continue to be popular. Let’s learn a bit more about each of them.
ChatGPT, as mentioned at the beginning of this text, is a chatbot that provides text-based solutions for various queries. Developed by OpenAI, the platform can answer questions, solve mathematical problems, create stories, and even provide advice to users!
Lensa is a photo editing app available for both Android and iOS. It could be just like any other editing app, but it features an algorithm that generates dozens of avatars inspired by real people! The app works as follows: the user provides photos of the same person from different angles, and their features are replicated through GANs in various scenarios.
Lastly, Synthesia enables the creation of videos using Artificial Intelligence. The platform allows users to create videos in 15 minutes and in over 120 different languages. Users need to select a video template (the company claims to have more than 125 distinct avatars) and provide a video script in any of the languages supported by the platform.
Generative AI has also made its way into various business areas, providing new opportunities and innovative solutions. Here are three examples of how this technology is driving productivity within companies:
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