OpenAI, the research organization dedicated to creating and ensuring the safe and beneficial use of artificial intelligence, has recently announced the launch of GPT-4 Turbo, a new and improved version of its groundbreaking language model, GPT-3.
In this article, we will explore what GPT-4 Turbo is, how it differs from GPT-3, what are its new features and capabilities. GPT-4 is the result of years of research and development, and it promises to revolutionize the field of natural language processing and beyond.
Table of Contents
What is GPT-4 Turbo?
GPT-4 Turbo is a deep neural network that can generate natural language texts on almost any topic, given some input or prompt. It is based on the transformer architecture, which is a type of neural network that can learn from large amounts of text data and capture long-range dependencies and complex patterns.
It is trained on a massive corpus of text data, consisting of billions of words from various sources, such as books, news articles, social media posts, web pages, and more. It can leverage this data to learn the statistical patterns and relationships between words, sentences, and paragraphs, and use them to generate coherent and fluent texts that match the style, tone, and content of the input.
What are the New Features and Capabilities of GPT-4 Turbo?
GPT-4 Turbo is the latest and most powerful generative AI model from OpenAI. It has several new features and capabilities that make it more useful and versatile for users and developers. Some of the main features and capabilities of GPT-4 Turbo are:
- Larger Context Window: GPT-4 Turbo can accept context with up to 128,000 tokens or 100,000 words, which is four times larger than GPT-4’s context window of 32,768 tokens. This means that GPT-4 can handle longer and more complex inputs, such as an entire book or a long article, and generate more coherent and relevant outputs.
- Vision Support: It can understand both text and images as inputs, thanks to its integration with OpenAI’s vision models. It can generate outputs based on visual information, such as captions, descriptions, stories, or memes, as well as text-based information.
- More up-to-date data: GPT-4 Turbo has been trained with data up to April 2023, which is seven months more recent than GPT-4’s data up to September 2021. It has more current and accurate information about the world, such as news, events, trends, and facts.
- Cheaper and Faster: GPT-4 Turbo costs only $0.01 per 1000 tokens (input), which is one-third of GPT-4’s cost of $0.03 per 1000 tokens (input). It is more affordable and accessible for users and developers. It is also faster than GPT-4, as it can generate outputs in seconds.
- JSON Mode: GPT-4 Turbo has a new feature called JSON mode, which allows users to specify the format and structure of the output they want. It can generate outputs that are more customized and suitable for different applications, such as web pages, tables, graphs, or lists.
- Text-to-speech: It has an improved text-to-speech model, which can generate natural-sounding audio from the text via an API with six preset voices. It can produce outputs that are more engaging and expressive for users and listeners.
What are the GPT-4 Upgrades?
OpenAI has not overlooked the development of GPT-4 while introducing GPT-4 Turbo. The company is initiating an experimental access program for fine-tuning GPT-4. In contrast to the fine-tuning program for GPT-3.5, the previous version of GPT, the GPT-4 fine-tuning program will involve more extensive oversight and guidance from OpenAI’s teams, primarily due to technical challenges.
OpenAI explains in a blog post, “Preliminary results suggest that achieving substantial improvements over the base model with GPT-4 fine-tuning requires more effort compared to the significant gains seen with GPT-3.5 fine-tuning.”
OpenAI is increasing the tokens-per-minute rate limit for all paying GPT-4 customers. However, pricing will remain the same at $0.03 per input token and $0.06 per output token for the GPT-4 model with an 8,000-token context window, or $0.06 per input token and $0.012 per output token for the GPT-4 model with a 32,000-token context window.
GPT 4 Turbo Pricing
The price of GPT-4 Turbo varies depending on the input and output tokens, the context window, and the model type. The input tokens are the pieces of words that are used to prompt the model, and the output tokens are the pieces of words that the model generates in response. The context window is the amount of text that the model can remember and use from previous interactions. The model type is the level of capability and knowledge that the model has.
Here are some examples of the prices for different models and scenarios:
- If you want to use the GPT-4 Turbo model with a 128K context window, which is the most capable and up-to-date model, you will pay $0.01 per 1000 input tokens and $0.02 per 1000 output tokens.
- If you want to use the GPT-3.5 Turbo model with a 16K context window, which is a cost-effective and dialog-optimized model, you will pay $0.003 per 1000 input tokens and $0.004 per 1000 output tokens.
- If you want to fine-tune your own custom model based on the GPT-3.5 Turbo model, you will pay $0.008 per 1000 tokens for training, $0.012 per 1000 tokens for input usage, and $0.016 per 1000 tokens for output usage.
Frequently Asked Questions
How can I Access and use GPT-4 Turbo?
You can access and use GPT-4 Turbo through a simple and intuitive API, which provides various options and parameters to customize and optimize the generation process.
How Accurate and Reliable is GPT-4 Turbo?
It excels in text generation but isn’t flawless. Verify and edit its output for accuracy, consistency, and potential biases, especially in critical contexts.
How to use GPT 4 Turbo API?
To use GPT-4 Turbo API, you will need to create an OpenAI account and sign up for the API. Once you have an account, you will be able to generate an API key. You can then use this API key to make requests to the GPT-4 Turbo API.
Conclusion
GPT-4 Turbo is the latest and most advanced language model from OpenAI, which can generate natural language texts on almost any topic, given some input or prompt. It is an improved and enhanced version of GPT-3, which addresses its limitations and challenges, and introduces several new features and capabilities.
It is also a versatile and powerful technology, which can be used for a wide range of applications and domains, and which could have significant implications for the society and the world. It is a remarkable achievement and a promising opportunity for the field of natural language processing and beyond.
