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Whether you are a seasoned machine learning engineer or just curious, you may be wondering: How is Chat GPT trained?
The AI language model, developed by OpenAI, has become wildly popular in a short period since its launch. So much so that the website often experiences server capacity problems, blocking users from accessing the site.
The online model has the ability to do numerous tasks, generating responses to almost any prompt you give it. But, how was it created?
How is Chat GPT trained?
First things first, Chat GPT was built on the foundation of OpenAI’s GPT-3.5. Another more advanced language model that was built on a massive dataset, typically containing information from the internet. The GPT (Generative Pre-trained Transformer) model uses this knowledge base to make predictions about the next word in a sequence of words. This produces human-like text and relevant responses to user prompts.
As a result of the deep learning LLM (Large Language Model) taking input prompts in natural human language, many users ask if those same queries are used to train the neural network. The answer is yes, but you can choose to opt out.
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Does ChatGPT learn on its own?
The answer lies in transformer architecture. The GPT model, in all its iterations is based on an AI architecture called transformer tech. GPT-3.5 was fine-tuned so it could interact with its users in a conversational format. Let’s explore what this fine-tuning looked like!
According to OpenAI, Chat GPT was trained using “Reinforcement Learning from Human Feedback” (RLHF). Initially, the model went through a process called supervised fine-tuning, where OpenAI trainers played the role of both a human user and an AI bot.
Through this, the trainers created a dialogue sequence in order to emulate how humans communicate, which was then added to the model’s dataset to fine-tune it for conversational uses.
Chat GPT was later improved by creating a reward model to be used for the next step – reinforcing learning. This involved AI trainers interacting with the tool to generate responses. Then grading them from best to worst, based on quality.
With this information, OpenAI could further fine-tune the model using its own technique called Proximal Policy Optimization. If you are looking for detail on this process, OpenAI covers it on its blog.
What type of machine learning is Chat GPT?
OpenAI’s Chat GPT is a Large Language Model. As the name suggests, these models are huge and are built using billions of parameters. They are a type of deep-learning algorithm that can understand and generate text, according to the data on which it was trained.
These sorts of models have a wide range of uses from creating chatbots, acting as search engines, and generating creative content such as lyrics and stories.
Where does ChatGPT get its data?
ChatGPT’s data comes from a massive dataset that includes a diverse range of sources such as websites, books, news articles, and journals.
Is ChatGPT based on NLP?
Yes, ChatGPT is based on natural language processing, which is a section within artificial intelligence. As the name suggests, NLP focuses on the interaction between computers and humans using natural language. This is why ChatGPT can understand, interpret and generate responses just like a human.
Grasping the training process of AI language models, like ChatGPT, can be very perplexing. We hope this article has given you an insight into how OpenAI created this infamous language model. If you’re interested in the full capabilities of the worlds most popular AI chatbot, why not read about ChatGPT Plus or ChatGPT Enterprise, and how it can even make PowerPoints!