History of GPT Models

Here’s a brief overview of each version of the GPT series: GPT-1: Released in 2018, GPT-1 was the first version of the GPT series. It had 117 million parameters and was trained on a large corpus of text data to generate coherent and grammatical text. While GPT-1 was a major breakthrough in natural language processing at the time, its text generation capabilities were still limited compared to later versions.

• Capable of generating coherent and grammatically correct text, but with limited context awareness

• Can complete short prompts or generate text of a fixed length

• Trained on a corpus of web pages, books, and articles

• Used in language tasks such as language translation, summarization, and conversation modeling

GPT-2: Released in 2019, GPT-2 was a significant improvement over GPT-1. It had 1.5 billion parameters, which was over ten times larger than GPT-1, and was trained on a much larger corpus of text data. GPT-2 was able to generate text that was more fluent and contextually coherent than GPT-1, and it was even capable of generating coherent paragraphs and articles.

• Capable of generating more fluent and contextually coherent text than GPT-1

• Generates longer pieces of text, such as paragraphs or articles

• GPT-4 supports multiple language output

• Used in language tasks such as language translation, summarization, and question-answering

GPT-3: Released in 2020, GPT-3 was the most advanced and powerful version of the GPT series to date. It had a staggering 175 billion parameters, which was over one hundred times larger than GPT-2, and was trained on an even larger corpus of text data. GPT-3 was a major breakthrough in natural language processing, capable of generating high-quality text that was difficult to distinguish from text written by humans. GPT-3 can perform various language tasks, including text, questionanswering, and translation.

• Capable of generating high-quality text that is difficult to distinguish from text written by humans

• Can perform a wide range of language tasks, such as translation, summarization, and question-answering

• Capable of understanding and generating text in multiple languages

• Can perform few-shot or zero-shot learning, meaning it can generate text in a new domain or language with only a few or no examples provided

GPT-4 is the latest version of OpenAI’s language model, which has been developed to improve model “alignment” – this capability allows the model to follow exact user intentions and generate less offensive or less dangerous output.

Improved Performance: GPT-4 makes fewer factual errors and is more “steerable”

One major improvement in GPT-4 is its performance. It scores approximately 40% higher than GPT-3.5 on OpenAI’s internal factual performance benchmark, making fewer factual or reasoning errors. It also improves “steerability,” which allows users to change its behavior according to their requests, such as commanding it to write in a different style or tone.

Image Inputs: GPT-4’s ability to use image inputs for any vision or language task.

Another major change is GPT-4’s ability to use image inputs (currently only available in research preview). As a GPT-4 user, you can specify task vision or task language by entering text or images. It can also understand and interpret complex imagery.

Human-level Performance:

GPT-4 achieved human-level performance on various professional and academic benchmarks.

OpenAI evaluated GPT-4 on various professional and academic benchmarks, such as the Uniform Bar Examination and LSAT for lawyers, and the SAT for university admission. These benchmarks helped GPT-4 in achieving human-level performance. This model indicates a good deal of OpenAi’s progress in developing advanced AI Models.

Accessing GPT-4:

Currently available to ChatGPT Plus users with a waitlist for the GPT-4 API.

To gain access to GPT-4, its text input capability is currently available to ChatGPT Plus users, with a waitlist for the GPT-4 API. Public availability of the image input capability has not yet been announced.

OpenAI Evals:

Open-sourced framework for automated evaluation of AI model performance

OpenAI has also open-sourced OpenAI Evals, a framework for automated evaluation of AI model performance, to allow anyone to report shortcomings in their models and guide further improvements.

Good News! WriteMe.Ai will soon be shifted to GPT-4!

Model Alignment

Limited

Improved for better alignment with user intentions and less offensive/dangerous output

Factual Performance

Lower accuracy, higher number of factual or reasoning errors

40% improvement in factual performance benchmark, lower number of errors

Steerability

Limited ability to change behavior according to user requests

Image Inputs Not available

Improved steerability for changing writing style or tone

Supports image inputs in research preview

Performance Benchmarks

Achieved high performance on traditional machine learning benchmarks

Achieved human-level performance on professional and academic benchmarks

Access

Open-source Framework

Widely available to developers and researchers

Text input available for ChatGPT Plus users, waitlist for API access

OpenAI has released some code and tools for developers

OpenAI Evals framework released for automated evaluation of AI model performance