How does Chat GPT work?
There has been a lot of talk about Chat GPT since its launch in November 2022. This ‘smart chat’ has surprised even the most skeptical. In this post we will discuss how it works and how you can use Chat GPT in your projects.
What is Chat GPT?
Chat GPT is defined as a generative language model. However in practice it is understood as an artificial intelligence chat that has been trained and designed to hold natural conversations. Chat GPT belongs to the research company OpenAI, founded in San Francisco in 2015 by Sam Altman, Elon Musk, Greg Brockman, Ilya Sutskever and Wojciech Zaremba.
What is Chat GPT used for?
But what are the applications of Chat GPT? Some of the applications for which you can use Chat GPT (besides having a good time asking questions) are discussed below:
With GPT you can generate coherent and well-written texts in a wide range of styles, topics and languages. In addition, news summaries, product descriptions or stories can be generated.
Thanks to this chat, problems can be analyzed and solutions or answers to questions can be generated.
GPT can be used to generate appropriate and consistent responses for a chatbot in a wide range of contexts.
It can be used to generate attractive posts and messages for social networks.
With GPT you can generate reports, e-mails and other content for productivity applications.
Thanks to chat GPT, large data sets can be analyzed and valuable information can be extracted from them.
How does Chat GPT work?
As its acronym indicates, Generative Pre-training Transformer, Chat GPT is a generative language model based on the ‘transformer’ architecture. These models are capable of processing large amounts of text and learning to perform natural language processing tasks very effectively. The GPT-3 model, in particular, is 175 billion parameters in size, making it the largest language model ever trained. To work, GPT needs to be “trained” on a large amount of text. For example, the GPT-3 model was trained on a text set that included over 8 million documents and over 10 billion words. From this text, the model learns to perform natural language processing tasks and generate coherent, well-written text. Once the model is well trained, GPT can be used to perform a wide range of tasks, as we have seen in the previous section. Reinforcement learning, based on human feedback, was used for training. Ultimately, by supervised fine tuning. The human AI trainers provided conversations in which they represented both the user and the AI assistant. In addition, the coaches were provided with written suggestions to help them write their proposals. So, they mixed this new dataset with the InstructGPT dataset that was transformed into a dialog format.
But how did they create the reward model for reinforcement learning?
The first thing that was needed was to collect comparison data. This consisted of two or more model responses, ranked by quality. So, in order to collect the data, they took some conversations that the trainers had had with Chat GPT and randomly selected them. In this way they tested various endings for the coaches to rank.
For this reason, these reward models could be adjusted using Proximal Policy Optimization. Also, the trainings were carried out on a Microsoft Azure platform on a supercomputer. In conclusion, to use GPT in a chat, the model is provided with an input in the form of text. This input can be in the form of a question or a context sentence. And, from this input, GPT generates an appropriate and coherent response. In fact, this response can be used in a chatbot or any other application where it is necessary to generate a text from a given input.
What does it mean that Chat GPT is transformer-based?
A “transformation” is a type of data processing that is performed on a sequence of elements, such as words in a sentence or characters in a word. And “transformers” are machine learning models that are specifically designed to process sequences of elements using transformations.
The architecture of the transformers is based on the use of attention, which is a technique that allows the model to pay attention to different parts of the input sequence at different times while processing the sequence. This allows the transformers to process information more effectively and perform natural language processing tasks more accurately. GPT (Generative Pre-training Transformer) is a generative language model based on the transformer architecture. This means that the model has been designed to process sequences of elements, such as words in a sentence, using transformations and attention. This architecture is very effective for performing natural language processing tasks and has revolutionized the way many NLP tasks are approached.
We chat with Chat GPT How could its creators benefit from Chat GPT?
In 2019 in an interview with OpenAI CEO Sam Altman, he said they would keep their promise to investors and task the AI itself with finding ways to generate revenue. At the time the audience took it as a joke, but looking at how the system works, it’s closer than we think. To check it out, we have done the test. Below, you can read Chat GPT’s response: “ATRIA: Can you name 5 ways in which OpenAI can make money through Chat GPT? GPT Chat: Sure, with pleasure. Here are five ways OpenAI could make money through GPT (Generative Pre-training Transformer):
Offering paid APIs for access to GPT: OpenAI has developed APIs for some of its more advanced language models, such as GPT-3, that allow companies to use these models in their own applications and services. Enterprises can use these paid APIs to access these models and use them to perform natural language processing tasks in their own applications.
Offering GPT-based application development services: OpenAI can collaborate with companies and organizations to develop applications and services that use GPT and, in return, get paid for these services.
Selling GPT-generated content: OpenAI could sell GPT-generated content to companies or individuals interested in using this type of content for their purposes.
Offering training and consulting in the use of GPT: OpenAI could offer training and consulting to companies and organizations that wish to use GPT in their own projects and applications.
Licensing the use of GPT to other companies: OpenAI could license the use of GPT to other companies for a fee. This could include selling exclusive usage rights or selling non-exclusive usage rights.”
The result is not inconsistent and logical. In our opinion, we are facing a new technology revolution in terms of language models.
Other OpenAI language developments
Thanks to OpenAI, some of the world’s most advanced and highest performing language models have been developed. Some of OpenAI’s most prominent language models include:
Ø It is a generative language model that has been trained on a large number of texts and can generate high quality content on a wide range of tasks.
Ø It is an even more advanced generative language model than GPT, with significantly more processing power and performance.
Ø It is a natural language processing model that has revolutionized the way many NLP tasks are approached and has set new standards in performance, across a wide range of tasks.
Ø It is a text-based image generation model that can generate realistic images from natural language descriptions.
Ø It is the largest and most advanced language model that has been developed to date by OpenAI, with even greater processing power and performance than its predecessors.
These are just a few examples of the language models developed by OpenAI
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