GPT-4: AI's Language Revolution Unleashed!

In the rapid development of the field of artificial intelligence, language processing technology has always played a crucial role. OpenAI’s latest release, GPT-4, has attracted widespread attention as it propels the interactive capabilities of artificial intelligence to a new height. With advanced machine learning algorithms, GPT-4 exhibits unprecedented natural language processing capabilities, being able to accurately understand and generate in-depth dialogues. This article will delve into the features and application fields of GPT-4, exploring the infinite possibilities brought by this language revolution in artificial intelligence.

Table of Contents

What is GPT-4?

OpenAI’s latest natural language processing model, GPT-4, is a multimodal large model capable of processing text and image inputs and generating corresponding text outputs. This major upgrade was announced on March 14, 2023, and OpenAI’s chat tool, ChatGPT, was also upgraded synchronously, and the current ChatGPT Plus has integrated the functionality of GPT-4. 

According to OpenAI’s announcement, GPT-4 has reached human level in many professional tests and academic benchmarks, and its performance significantly surpasses the previous version, GPT-3.5. For example, in a simulated law examination, GPT-4’s scores are in the top 10% of examinees, while GPT-3.5’s scores are only in the bottom 10%. Although GPT-4’s performance in real-world scenarios still needs to be improved, and there may be fabrication of facts and reasoning errors when handling some complex issues, its overall progress is undoubtedly significant.

It’s worth mentioning that the biggest highlight of GPT-4 is its visual input capability, which can generate corresponding text outputs based on text and image prompts. However, this function is still in the research stage and is not yet open to the public.

GPT-4 Background

OpenAI first released their GPT model (GPT-1) in 2018 and wrote a paper titled “Improving Language Understanding with Generative Pretraining.” This model is based on the transformer architecture and has been trained on a large amount of book text. Just a year later, OpenAI released GPT-2, a larger and more powerful model that can generate coherent and high-quality text.

In 2020, OpenAI launched GPT-3, a model with a hundred times the number of parameters of GPT-2, enabling it to perform a variety of tasks after receiving very few examples. Subsequently, GPT-3 was further optimized into GPT-3.5, which was used to build the chatbot product ChatGPT.

How to use GPT-4 with API?

Important note: The GPT-4 API and corresponding gpt-4 model are currently in the testing phase. To get access, you need to register for the waitlist. To do this, visit the OpenAI dashboard , and then navigate to the “Join the GPT-4 API Waitlist” section. Click the “Register” button and follow the instructions to join the waitlist. Once you have access, you will be able to use the GPT-4 API.

Before you start enjoying the advantages of GPT-4’s powerful features, you need to prepare your environment and get API access. In this section, we will guide you through all the steps needed to get started and use the GPT-4 API.

1.Create an account and get an API key:

To use the GPT-4 API, you first need to create an account on the OpenAI website. Visit OpenAI website and register a new account. After completing the registration, log into your account and find the API section. Here, you will see your API key, which is necessary for your GPT-4 API requests. Be sure to keep this key safe as it is the unique identifier of your account and should not be shared with others.

2.Set up the development environment:

Before you start making API calls, you need to set up your development environment. You can choose any programming language that supports HTTP requests, such as Python, JavaScript or Ruby. For the convenience of this guide, we assume that you will use Python. First, you need to make sure that Python is installed on your system. If not yet installed, you can download the latest version from the Python official website . Then, create a new directory for your GPT-4 API project and open it in the terminal or command prompt. We recommend using a virtual environment to manage project dependencies. To create a virtual environment, you can run the following commands:

Activate the virtual environment by running the appropriate command for your operating system:

  • windows:
  • macOS/Linux:

3.Install the necessary libraries and dependencies:

Now that your development environment is set up, you need to install some libraries to interact with the GPT-4 API. For Python, we will use the popular requests library to issue HTTP requests.

Install the requests library by running the following command:

With your account, development environment, and dependencies set up, you can now start making API calls and unleash the powerful capabilities of GPT-4!

GPT4 vs GPT3.5

GPT-4 is the latest member of the GPT model family and has achieved significant improvements in many areas compared to GPT-3.5, such as: Visual inputs; text input limit raised to 25,000 words; significantly improved answer accuracy, etc. The main features are as follows:

  • Image-to-Text: GPT-4 can recognize images and generate text content based on the prompts of the images
  • Generate new text content based on text, including online real-time interactive chat, text content generation, cross-language task processing, etc.
  • Stronger multi-language capabilities: GPT-4 tested its multi-language capabilities during training, and the results in 24 of the 26 tested languages ​​were better than the English capabilities of GPT-3.5 and other LLM models. In other words, although GPT-4 is written in English, its capabilities in other languages ​​are even stronger than English.
  • Significantly improved accuracy of answers: GPT-4 outperforms GPT-3.5 and other similar models in most cases in simulated exams during testing, for example, it passed the simulated lawyer exam, and the score was in the top 10% of test takers; in contrast, the score of GPT-3.5 was in the bottom 10%.
  • Significantly increased text input limit: The text limit of GPT-4 has been raised to 25,000 words
  • Safer “GPT-4” introduced an additional safety reward signal during training to reduce harmful outputs by training the model to reject requests for such content. Compared with GPT-3.5, the model’s response tendency to disallowed content requests has been reduced by 82%, and GPT-4’s frequency of responses to sensitive requests (such as medical advice and self-harm) that comply with policies has increased by 29%.

How does GPT-4 work?

GPT-4 works by using a neural network trained ona large amount of data. The model has been pre-trained on a large corpus of text, allowing it to understand and generate natural language. Once the model is trained, it can be fine-tuned for specific tasks, such as language translation, question answering, or summarization.

How much does GPT 4 cost?

If you access GPT-4 through ChatGPT Plus, you will need to subscribe to its $20 per month plan. However, if you access GPT-4 through the API, there are two pricing options based on context length.

OpenAI has reduced the price of prompt tokens, making it easier for users to use the new language model GPT-4.

Here is the cost for models with an 8K context length (gpt-4 and gpt-4-0314):

  • Prompt token cost is $0.03/1k
  • Sampling token cost is $0.06/1000

Here is the cost for models with a 32K context length (gpt-4-32k and gpt-4-32k-0314):

  • Prompt token cost is $0.06/1k
  • Sampling token cost is $0.12/1000

What is the future of GPT?

As more problems are discovered, OpenAI plans to iterate and improve GPT-4 after deployment, and the company has committed to taking some steps. These include:

  • Adopting multi-layer mitigation measures: As AI models become more powerful and are further adopted in multiple industries, the need for multiple lines of defense is crucial. OpenAI will adopt multi-layer mitigation measures in the GPT-4 model system to reduce potential risks and misleading outputs.
  • Consider the evaluation, mitigation, and method development of actual usage scenarios: Understanding who the users are and what these tools are used for is crucial to mitigate any potential harm that may be caused. OpenAI will consider actual usage scenarios when deploying these tools, and evaluate, mitigate, and develop methods as needed to ensure that they can better meet user needs.
  • Ensure that safety assessments cover urgent risks: As model capabilities increase, it is important to be prepared for complex interactions and unforeseen risks. OpenAI will ensure a comprehensive safety assessment of GPT-4, including considering urgent risks, and take necessary measures to deal with these risks.
  • Plan for unpredictable capability leaps: Artificial intelligence is a rapidly developing field, and we don’t necessarily understand everything that happens in the “mind” of a trained AI model, so minor changes could inadvertently lead to unexpected leaps in capability. OpenAI will plan for such unpredictable capability leaps and take appropriate measures to monitor and manage model behavior.

In general, the future direction is to pay more attention to the safety, transparency, and controllability of the model to ensure the good application of AI technology and the minimization of potential risks. OpenAI will continue to work with the community, listen to user feedback, and continuously improve and develop the GPT series of models to adapt to changing needs and challenges.