On March 14, 2023, OpenAI released its latest model, GPT-4. However, the journey leading up to GPT-4 had a fascinating story. Prior to GPT-4, OpenAI had already released GPT-1, GPT-2, GPT-3 and GPT-3.5 models. Here, we will tell you the story of how we’ve come from the past to the present by explaining all of OpenAI’s GPT models and their features.
What is GPT?
GPT stands for Generative Pre-trained Transformers. They are a group of neural network models that utilize the transformer architecture. These models represent a significant breakthrough in the field of artificial intelligence (AI) and play a crucial role in powering various generative AI applications, including ChatGPT.
GPT models can create text and various types of content, including images and music, in a way that closely resembles human-generated content.
Furthermore, they can participate in conversations and offer responses in a conversational manner. Thus, GPT models are being used for a wide array of applications, including Q&A bots, text summarization and content generation.
Below is a table that offers details about OpenAI’s all GPT models so far.
| Model Name | Parameters | First Release Date |
|---|---|---|
| GPT-1 | 117 million | Feb, 2018 |
| GPT-2 | 1.5 billion | Feb, 2019 |
| GPT-3 | 175 billion | June,2020 |
| GPT-3.5 | 175 billion | Nov, 2022 |
| GPT-4 | Estimated to be in trillions | March, 2023 |
| GPT-5 | – | Is not released yet |
GPT-1 Model
GPT-1 is the first large language model released by OpenAI. It was published in February 2018 and utilized the Transformer architecture, which was introduced by Google in 2017. For reference.
The Transformer architecture is a deep learning model for tasks such as understanding and generating language. It helps grasp context and relationships in data efficiently.
GPT-1 has 117 million parameters and was trained by gathering training data from the internet, including websites, books, and Wikipedia.
The use of the Transformer architecture contributed to GPT-1’s performance and improved upon previous models. It showed a 4.2% improvement in semantic similarity compared to the best models before it.
However, GPT-1 has limitations in solving complex problems and avoiding repetitive content when generating long texts. Nevertheless, it served as a foundation for subsequent models.
The source code for GPT-1 is available on GitHub if you wish to access and explore its implementation.
GPT-2 Model
The GPT-2 model was announced by OpenAI on February 14, 2019, through a blog post. It consists of 1.5 billion parameters, which is approximately 12 times bigger than its predecessor, the GPT-1 model, which had 117 million parameters.
Similar to the GPT-1 model, GPT-2 was trained using various resources including books, and Wikipedia. GPT-2 produces text that closely resembles human language and is coherent, often tricking people into thinking they are interacting with a human.
However, GPT-2 is not flawless. It can occasionally produce incorrect or nonsensical responses, and it may struggle with tasks that require deep understanding or reasoning.
The source code for the GPT-2 model has been shared on the GitHub repository.
GPT-3 Model
GPT-3 is the third iteration of the GPT series developed by OpenAI. It was released on June 11, 2020, making significant advancements over its predecessor, GPT-2.
GPT-3 is a massive language model trained with a 175 billion parameters, making it one of the largest language models ever created. It was trained using a vast amount of text data sourced from the internet, books, articles, and websites.
The large-scale training and extensive parameter count of GPT-3 allow it to exhibit impressive capabilities in various natural language processing tasks. It has demonstrated greater performance in tasks such as text completion, text generation, translation, summarization, and even code generation.
GPT-3 can generate coherent and contextually relevant responses, often resembling human-like language.
Compared to GPT-2, GPT-3 exhibits a substantial improvement in its ability to understand and generate complex textual content. Its larger size and increased parameter count contribute to enhanced performance and a wider range of applications.
However, GPT-3 is not without limitations. One is its tendency to generate plausible-sounding but incorrect or nonsensical responses. It may also struggle with tasks that require nuanced reasoning or deep understanding of context.
OpenAI has not released the complete source code for GPT-3. However, the introduction of the GPT-3 model brought about the opportunity for the first-time commercial access to the model through an API. This allowed for the model’s commercial utilization and made it accessible via the API.
The introduction of GPT-3 has sparked significant interest and discussions in the field of natural language processing. It has showcased the potential of large-scale language models and their impact on tasks involving text generation and understanding.
GPT-3.5 Model
OpenAI introduced new versions of its AI models, GPT-3 and Codex, to their API on March 15, 2022. These enhanced models, named “text-davinci-002” and “code-davinci-002,” had the ability to edit and insert text. Compared to their predecessors, these models were more advanced, with their training based on data up until June 2021.
Fast-forward to November 28, 2022, OpenAI rolled out another AI model called “text-davinci-003”. A couple of days later, on November 30, 2022, OpenAI began categorizing these new models under the “GPT-3.5” series. Within this series, OpenAI launched ChatGPT.
Despite its name, GPT-3.5 is not part of the original GPT-3 model.
The GPT-3.5 model eventually became the base for the standard model used in ChatGPT, turning into the fastest and most efficient GPT product utilized by OpenAI. It has the lowest usage cost among the current API models. Take a look at OpenAI API Pricing for more information.
You can find a simplified example code below on how to call the GPT-3.5 API in Python.
import openai
# Set your API key
api_key = "your-api-key"
# Create a prompt
prompt = "Translate the following English text to French: 'Hello, how are you?'"
# Call the API
response = openai.Completion.create(
engine="davinci",
prompt=prompt,
max_tokens=50,
api_key=api_key
)
# Get the generated text
translated_text = response.choices[0].text
# Print the translation
print(translated_text)
GPT-4 Model
GPT-4 was announced on March 14, 2023, through a blog post. It is the most advanced and capable model to date.
OpenAI did not officially disclose the exact number of parameters contained in it, but it is expected to have at least ten times more parameters than its predecessor, GPT-3, surpassing a 1 trillion parameters.
What sets GPT-4 apart isn’t only its number of parameters. Unlike previous models that were solely language models, GPT-4 is a multimodal. It doesn’t just accept text as input but can also take images as input.
Its expanded capabilities make GPT-4 more proficient at comprehending and deciphering complex issues. It demonstrates a higher level of creativity and reasoning, and it performs more effectively in any languages.
GPT-4 model also performed really well in the tests administered. Take a look at the test results of the GPT-4 model on the USA’s widespread exams.
GPT-4’s 32K model comes with a character limit of 32,000 tokens. This means it has the ability to understand and interpret several pages of text in a single instance, or provide responses at this length.
However, the usage fee for GPT-4’s API is at least 20 times higher than GPT-3, making it a more expensive tool to use. Furthermore, it responds about 1.7 times slower compared to the GPT-3 model.
Despite these downsides, GPT-4’s enhanced capabilities set a new benchmark in the field of AI language models. It is the most reliable, creative and sophisticated language model in GPT models.
GPT-5 Model
OpenAI has recently applied for a trademark for GPT-5, which indicates that they are working on the next iteration of their large language model. This filing was submitted to the United States Patent and Trademark Office on July 18.
Despite GPT-4 being only a few months old, it seems that OpenAI is already looking ahead to the next generation.
While specific technical details about GPT-5 are not yet available, it is expected to be a significant improvement over its predecessors. GPT-4 demonstrated substantial advancements over GPT-3, which itself was a major leap from GPT-2.
The trademark application describes GPT-5 as “downloadable computer software and programs” designed for tasks like artificial speech and text generation, natural language processing, understanding, analysis, and other functions like translation and transcription.
The trademark also emphasizes its capabilities in generative AI, claiming that it can develop, run, and analyze algorithms for tasks such as data analysis, classification, and taking actions based on data. Additionally, it highlights its application in developing and implementing artificial neural networks.
As for the release date of GPT-5, no specific timeline has been provided in the submission.
Conclusion
We’ve covered all of OpenAI’s GPT models. The GPT model, first announced in 2018, gained significant popularity with the release of ChatGPT and showcased the remarkable advancements in artificial intelligence technology with the introduction of GPT-4 in 2023.
The exact number of GPT models OpenAI will release remains unknown. However, features like GPT-4’s image input capability and its enhanced reasoning abilities have made a significant impact for now.