GPT technology can help people write code quickly and accurately by using natural language as a prompt. GPT can take a text prompt such as "I need a function to calculate the average of two numbers" and generate code that is tailored to the given task. This technology has the potential to cut down development time, as it can generate code quickly and accurately. It can also help reduce the risk of errors, as GPT is capable of generating code that can be tested and used immediately. Try AI Code Generator to create code in any language, from small functions to entire static websites.

AI Generated Books

AI can even generate books by using natural language processing to generate text. This technology can be used to generate book-length pieces of text based on a given set of topics. For example, an AI system could be given a list of topics and then it would generate text that incorporates those topics into a cohesive narrative. Currently, AI Book Generator allows people to create ebooks that can be sold on book stores like Amazon and Kobo to make some extra-money.

Able to generate anything you want

GPT technology is revolutionizing the way we write. With the help of GPT, it is now possible to generate content within a fraction of the time it would take a human to do the same. GPT is able to generate any kind of content from articles to poems, songs, essays, and more. It can even be used to generate entire stories or novels in a matter of minutes. GPT is a powerful tool that can help writers save time, increase productivity, and produce higher quality content.


OpenAI has opened up a Discord server, allowing users to come together and discuss the latest developments in AI and GPT technology. The server provides an invaluable opportunity to connect with other like-minded people, ask questions, and learn more about the technology. With the OpenAI Discord server, users can join a vibrant community and stay up-to-date with the latest news and developments in AI.


GPT technology is a powerful tool, but it also comes with certain limitations. GPT is not yet able to understand context, which means it can produce text that may not make sense in certain situations. Additionally, GPT is also not able to generate creative content, so it is unable to produce original ideas or stories. Finally, GPT is not able to produce content that is tailored to a specific user or situation, so it is not able to provide personalized content. Despite these limitations, GPT is still a powerful tool that has many applications.

Is ChatGPT busy?

Is ChatGPT currently busy due to high traffic? Check out and start talking with AI now. Vate is powered by GPT technology, responses are quite fast and there are no service interruptions . Whether you need to write articles, ask questions or manage your content creation business, Vate is an effective solution that allows you to experience the same technology used by OpenAI.


Here some example of how ChatGPT works and what you can create with it. It is an interactive chat where you can talk like facing a real person.

How did we get to ChatGPT

For many years, humanity based its calculations on simple machines. The abacus is an example of how addition and multiplication could be more easily tackled without resorting to mental or graphical calculations. More recently, with mechanics and subsequently electronics, calculators have allowed us to perform roots, exponentials, integrals etc.

Similarly, even the operations we have always performed were simple operations. Most of the calculations that we carry out during our daily lives are purely additions or multiplications. Only during the last years of high school, and eventually during university, students do have the opportunity to confront something more advanced, such as function analysis, derivatives, and differential calculus. But these are not, in any case, topics that are often taken up in non-school discussions.

In the last decade, however, the rapid progress of technology, that is, the computing power of hardware units, as well as the expansion of the speed of information transmission, has brought about a new art in our daily lives, the neural one, typical of the complexity of our mind. Object recognition, voice assistants, neural networks capable of writing reports and essays automatically: millions of small agents, algorithms, take part every day in the activities we carry out, to significantly facilitate or enhance the quality of work and information.

Generative networks

At the heart of all this lies a new type of computation, the neural one, which is essentially based on derivatives and multiplications. However, its significance is much broader: inserting all the values of a data set into a mathematical function and then calculating the derivative of that function tending towards 0 (with 0 being the reference value that one wants to represent or obtain) allows the neural algorithm to generalize on those values as a whole, controlling them all at once, and resulting in a process that is very similar to how our minds work.

This "controlling" of all elements of a data set (images, texts or other data) allows this new type of computation to exercise intelligent functions and thus perform discriminating operations (e.g., reporting whether an image contains a license plate or not) and, conversely, generative ones (generating an image containing a specific object).

Mathematically, neural computation is not overly sophisticated, but the result it generates is as complex as the functions typical of intelligence. And that is why it is called artificial intelligence. Following the Aristotelian saying "The whole is greater than the sum of its parts," the results of neural algorithms also have properties that increase the value of individual starting units. A particular example of this is the fact that the most recent generative neural networks (e.g., those that generate images) can draw almost anything and are materially composed of a file of a handful of gigabytes. Almost all images can be drawn with such tools, and yet they do not "weigh" more than ten thousand of them, resulting in efficiency. Similarly, the same neural networks that generate images have proven to be powerful image compression algorithms.