# GPT-4 (Generative Pre-Trained Transformer-4)

## Generative Pre Trained Transformer -4 (GPT-4)

GPT-4 is a significant improvement over GPT-3 and offers a number of new capabilities. The main difference between GPT-3 and GPT-4 is the amount of data they have been trained on. GPT-4 has been trained on 45 gigabytes of data, which is 10 times more than GPT-3's 17 gigabytes. This means that GPT-4 has a much larger vocabulary and can generate more complex and nuanced text.

Another major improvement in GPT-4 is that it is **'Multimodal'.** It can accept and produce text and image inputs and outputs, making it much more diverse.  GPT-3 on the other hand was **'Unimodal'**, meaning it can only accept text inputs. It can process and generate various text forms, such as formal and informal language, but can't handle images or other data types.&#x20;

### Training Parameters:

In the context of language models, parameters are the **'weights'** and **'biases'** that are used to model the relationships between words and phrases. The more parameters a model has, the more complex the relationships it can model.

GPT-3 has 175 billion parameters. This means that it can model the relationships between a very large number of words and phrases. As a result, it can generate more complex and nuanced text than models with fewer parameters. GPT-3 can understand and respond to more complex prompts. It can also generate more original text and is less likely to generate repetitive or nonsensical text.

GPT-4 on the other hand has over **100 trillion parameters**, which means it can model much more complex relationships.

Here are some other key differences between GPT-3 and GPT-4:

* **Dataset size:** GPT-4 is trained on a dataset of 45 gigabytes of text and code, while GPT-3 is trained on a dataset of 17 gigabytes of text.
* **GPT-4 has a larger vocabulary and can generate more complex and nuanced text.** This is because it has been trained on more data.
* **GPT-4 can understand and respond to more complex prompts.** This is because it has a better understanding of context and nuance.
* **GPT-4 is more creative and can generate more original text.** This is because it has been trained on a wider variety of data.
* **GPT-4 is more efficient and can generate text faster.** This is because it has been optimized for speed and performance.
* **Architecture:** GPT-4 uses a new architecture that allows it to better understand and respond to complex prompts.&#x20;
* **Reliability:** GPT-4 is more reliable, creative, and able to handle more nuanced instructions than GPT-3. GPT-4 is more reliable and can generate more accurate text. This is because it has been trained on a more diverse set of data.

Below is a table comparing the major features of GPT-3 and GPT-4:

| Feature              | GPT-3                                         | GPT-4                                      |
| -------------------- | --------------------------------------------- | ------------------------------------------ |
| Number of parameters | 175 billion                                   | 100 trillion                               |
| Training data        | 500 billion words                             | 45 gigabytes                               |
| Max context length   | 1024 tokens                                   | 8192 tokens                                |
| Cost per token       | $0.01                                         | $0.03 (prompt) / $0.06 (completion)        |
| Availability         | Limited access                                | Public beta                                |
| Strengths            | Accuracy, creativity, reliability, efficiency | Size, performance, multimodality           |
| Weaknesses           | Cost, bias, potential for misuse              | Maturity, lack of fine-tuning capabilities |

As you can see, GPT-4 is a significant improvement over GPT-3 in terms of size, performance, and multimodality. However, it is also more expensive and less mature. It is still too early to say for sure how GPT-4 will be used in practice, but it has the potential to revolutionize the way we interact with computers.

Here are some additional details about the differences between GPT-3 and GPT-4:

* **Size:** GPT-4 has 100 trillion parameters, which is 6 times more than GPT-3's 175 billion parameters. This means that GPT-4 has a much larger vocabulary and can generate more complex and nuanced text.
* **Performance:** GPT-4 is significantly faster than GPT-3. It can generate text at a rate of 20,000 words per minute, which is 10 times faster than GPT-3.
* **Multimodality:** GPT-4 can process and generate text, as well as images and code. This makes it more versatile and can be used in a wider range of applications.
* **Cost:** GPT-4 is more expensive than GPT-3. The cost per token is $0.03 for the prompt and $0.06 for the completion.
* **Maturity:** GPT-4 is less mature than GPT-3. It is still under development and has not been fine-tuned for specific tasks.
* **Bias:** GPT-4 may be more biased than GPT-3. This is because it has been trained on a dataset that is more representative of the internet.
* **Potential for misuse:** GPT-4 has the potential to be misused. For example, it could be used to generate fake news or to create harmful content.

Overall, GPT-4 is a significant improvement over GPT-3. However, it is also more expensive and less mature. It is still too early to say for sure how GPT-4 will be used in practice, but it has the potential to revolutionize the way we interact with computers.







Overall, GPT-4 is a significant improvement over GPT-3. It is more accurate, creative, reliable, and efficient. It can also understand and respond to more complex prompts. As a result, GPT-4 has the potential to be used in a wider range of applications, such as chatbots, virtual assistants, and content generation.

Here are some examples of how GPT-4 is being used:

* **Chatbots:** GPT-4 can be used to create chatbots that are more human-like and can have more natural conversations.
* **Virtual assistants:** GPT-4 can be used to create virtual assistants that can answer questions, provide information, and complete tasks.
* **Content generation:** GPT-4 can be used to generate content, such as articles, blog posts, and social media posts.
* **Education:** GPT-4 can be used to create educational resources, such as interactive lessons and quizzes.
* **Research:** GPT-4 can be used to help with research by generating hypotheses, finding relevant data, and writing reports.

GPT-4  has the potential to revolutionize the way we interact with computers. It is a powerful tool that can be used for a variety of purposes.

For more details on GPT-4 please visit:  [https://openai.com/research/gpt-4](https://openai.com/research/gpt-4)

