A COMPLETE GUIDE ON CHATGPT FROM OPENAI 

Introduction

If you’ve been following recent developments in AI technology (and even if you haven’t), you’ve likely heard of ChatGPT. This chatbot, developed by OpenAI, is built on top of GPT-3, a family of large language models that have been fine-tuned using supervised learning techniques. But what exactly is ChatGPT, and how can it be put in practice? A complete guide on ChatGPT from OpenAI is here to answer this question.

ChatGPT was first introduced as a prototype on November 30, 2022. And on February 13, 2023, it had its first stable release. Time to unwind some common questions about this OpenAI app without diving deep into technical details and sophisticated terminology. Although, we will use some terminology to start with: 

ChatGPT is a chatbot developed by OpenAI, that is built on top of GPT-3 family of large language models, that were fine-tuned using supervised learning techniques.

Chat GPT's Path to 1 Million Users

This technology has the potential to revolutionize a wide range of industries, from customer service to content creation to personal assistants and beyond. In our article we’ve uncovered the very essence of ChatGPT and its possible scope of application.

How does ChatGPT work?

ChatGPT is almost like an ordinary chat with only one exception – you a computer responds instead of a human. But no one is really amazed by scripted answers anymore, and therefore it must be something new that ChatGPT possesses. This chatbot is built on top of the comprehensive language model called GPT-3. But first thing first, let’s define what a language model is. In simple words:

Language Model is a tool that can predict the next word (or words) in a sequence. 

These models already operate in:

One particular language model (strictly speaking – family of models) is a Generative Pre-trained Transformer (GPT). It was first published on June 11, 2018 by OpenAI (AI research laboratory). Since then, 2 versions had already been released, tailing with the version GPT-3 (it is even rumoured that the GPT-4 will be released later in 2023). Summing up:

GPT is a family of language models.

Frankly speaking this definition is truly oversimplified. GPTs are trained on a large corpora (corpus – language resource of a large and structured set of texts) to generate human-like texts. 

Now let’s sum up:  ChatGPT is a chatbot that uses language models specially trained on a large amount of structured text data to communicate in a human-like manner.

How to use ChatGPT and OpenAI models

The next big question we are about to answer is where OpenAI’s  technology can be used. So, while ChatGPT keeps making headlines after months of dominating the internet, let’s figure out how this latest viral AI chat can be applied. 

Here’s what the AI says about itself

ChatGPT defines itself

Chatbots

By leveraging the natural language processing capabilities of OpenAI models, chatbots can understand and interpret the meaning behind the text written by customers and generate appropriate responses. This can help businesses provide better customer service and support, as well as reduce the workload on human customer service representatives. Overall, chatbots powered by OpenAI models have the potential to revolutionize the way that businesses interact with their customers and provide support.

Content creation

OpenAI models are sophisticated machine learning models and that can train on large datasets of text. One of the key applications of these models is generating high-quality content, such as articles, blog posts, and product descriptions. By analyzing patterns and structures in the text data they are trained on, OpenAI models can learn to generate text that is similar in style and tone to human-written content. 

Well, nice try

Well, nice try

This can be useful by businesses that need to produce a large amount of content quickly and efficiently, or for individuals who want to generate high-quality content without spending a lot of time writing it themselves.

Personal assistants

OpenAI models have the potential to serve as virtual personal assistants, helping individuals manage their daily tasks and responsibilities. These models can train on large datasets of text, which allows them to understand and interpret natural language input from users. This makes it possible for OpenAI models to perform tasks like scheduling appointments, sending emails, and setting reminders based on spoken or written commands from the user. 

For example, a user might say “schedule a meeting with John for next Thursday at 2 PM,” and the OpenAI model would be able to understand the request and schedule the meeting accordingly. 

Language translation

OpenAI models can be trained on large datasets of text in multiple languages, allowing them to understand and interpret natural language input in one language and generate corresponding output in another language. For example, a business that operates in multiple countries might use an OpenAI translation model to translate marketing materials, product descriptions, and other text-based content into multiple languages, enabling them to reach a broader audience. 

A perfectly correct answer

A perfectly correct answer

Sentiment analysis

By using natural language processing techniques, OpenAI models can determine the sentiment of the writer and identify trends and patterns in the data. This can be useful for businesses that want to understand how customers feel about their products or services. As well as for researchers who want to study social trends and public opinion. For example, a company might use an OpenAI sentiment analysis model to analyze customer reviews. It can identify areas for improvement in their products or customer service. Similarly, a researcher might use an OpenAI model to analyze social media posts and identify patterns in public sentiment about a particular topic.

Text summarization

OpenAI models have the potential to help individuals and businesses process large amounts of text-based information more efficiently. One of the key applications of OpenAI models is to automatically summarize long articles, reports, and other types of text into shorter, more concise summaries. By analyzing the key themes and concepts in the text, OpenAI models can generate summaries that capture the essence of the original content. This can be useful for individuals who want to quickly understand the main points of a document without reading the entire thing, as well as for businesses that need to process large volumes of text-based data quickly and efficiently. For example, a news organization might use an OpenAI summarization model to generate brief summaries of news articles that can be easily shared on social media. Similarly, a business might use an OpenAI model to automatically summarize reports and other documents for internal use.

Creative writing

OpenAI models can generate original and high-quality content in various formats. Such as poetry, short stories, and even scripts for movies and television shows. By learning from large datasets of human-written text, these models can replicate the style, tone, and structure of human writing, allowing for the creation of new works that resemble human writing. This technology can be especially helpful for writers who are struggling with writer’s block or looking for inspiration for their own creative projects. Moreover, the ability of OpenAI models to produce new creative content has the potential to inspire new forms of art and entertainment, and to change the way we think about creativity itself.

ChatGPT tells a programmers joke

Old but gold (yet not original)

Personalization

By analyzing large amounts of data on a user’s behavior, such as their search history, purchase history, and social media activity, OpenAI models can develop a profile of the user’s preferences and interests. This information is convenient for tailored content creation. For example, an e-commerce website might use an OpenAI model to recommend products to a user. The recommendations will be based on their past purchases and browsing behavior. Similarly, a streaming service might use an OpenAI model to personalize recommendations for TV shows and movies based on the user’s viewing history. By providing more personalized content and recommendations, OpenAI models have the potential to enhance the user experience and increase engagement with digital services.

How to use ChatGPT and OpenAI models?

After a short explanation of what ChatGPT is, a brief description of how and when it was developed and a concise enumeration of possible technology applications – lets talk about how we can use it currently.

At the moment, there is no official statement regarding an API for ChatGPT. So, it is currently not clear whether ChatGPT will be accessible for commercial use at all.

However, OpenAI offers other solutions for businesses and individuals in the form of language models available via API. These models are available in different variations for several purposes at versatile pricing points.

There are 3 types of models available:

We have already discussed GPT-3, so let’s move to the next one – Codex. Codex is a set of models that can translate natural language to code. Besides,  GitHub Copilot uses this model to generate code in assistive mode.

It is important to keep in mind that because of the relatively young age of modern AI models and an exponentially growing price on training them, there are still open questions about their ability to analyze rational and moral aspects of human beings. With that knowledge in mind, let’s consider the last available model – content filter. Content filter is a model that helps identify whether a specific text might be sensitive or unsafe.

OpenAI models to choose from

Let’s assume that we are aiming to integrate the AI to the existing application, that is not related to the safe content and source code. Then, we are left with the only suitable option that is the GPT-3 model. OpenAI offers the following models (sorted by their capabilities):

Davinci – is the most capable, the slowest and the most expensive model that is good at:

Ada, on the other hand, is the fastest model. But the price for the execution time is in its simple capabilities:

So, strictly speaking, currently you cannot use the ChatGPT itself in your application. But you can use GPT-3 models that OpenAI currently offers, looking back on your specific requirements on the model’s capabilities.

Summary

To summarize all the above:

Oh, and by the way. ChatGPT wrote this article. Or did not.

For a deeper insight on building chatbots based on AI read this article: Artificial Intelligence Application in Chats Beyond ChatGPT: Simple Chatbot by ProArea (With Code)

 

Created by Mykhailo Temnokhud

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