ChatGPT: The Power and Pitfalls of a Leading Language Model
Tags: aiml, chatgpt, automation
Published: 2023-01-23 10:01:57


![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/wfno9ax9ec6kk7o0px4j.png)

ChatGPT is a powerful language model developed by OpenAI that is capable of generating human-like text. It is trained on a massive dataset of internet text and can generate a wide range of content, from short responses to full-length articles. In this blog post, we will take a detailed look at how to learn and use ChatGPT.

First, let’s take a closer look at the architecture of ChatGPT. It is a transformer-based model that uses attention mechanisms to generate text. The model is pre-trained on a massive corpus of text data and can be fine-tuned for specific tasks. The pre-trained model can be used for a variety of natural language processing tasks, such as language translation, text summarisation, and question answering.

ChatGPT was optimised from a GPT 3.5 model trained on Azure AI supercomputers. This is an evolution of GPT3:

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/m2h34r68mno3qdspzs0f.png)

To use ChatGPT, you will need to have access to the pre-trained model and the OpenAI API. Once you have access to the API, you can start using the pre-trained model to generate text. You can also fine-tune the model for a specific task by providing it with a dataset of labeled examples. This process is called transfer learning and allows the model to learn to perform a specific task better.

The fine-tuning process involves training the model on a dataset of labeled examples for a specific task. For example, if you want to fine-tune the model for answering questions, you would provide it with a dataset of questions and their corresponding answers. The model will then learn to generate answers to the questions.

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/znjjm4qr9pmr9b07wyvj.png)

One important thing to note is that fine-tuning the model requires a significant amount of computational resources and can take a long time to complete. Therefore, it’s important to have access to a powerful GPU and a large amount of memory.


Another important thing to keep in mind is that the model can generate text that is not always accurate or appropriate. This is because the model is trained on a large amount of internet text, which can contain a wide range of content, including offensive or misleading information. Therefore, it’s important to use the model responsibly and to verify the generated text before using it.

![Image description](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/3r1lizb7iscba0jjoqbn.png)


## Pitfalls

- ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as: (1) during RL training, there’s currently no source of truth; (2) training the model to be more cautious causes it to decline questions that it can answer correctly; and (3) supervised training misleads the model because the ideal answer depends on what the model knows, rather than what the human demonstrator knows.

- ChatGPT is sensitive to tweaks to the input phrasing or attempting the same prompt multiple times. For example, given one phrasing of a question, the model can claim to not know the answer, but given a slight rephrase, can answer correctly.

- The model is often excessively verbose and overuses certain phrases, such as restating that it’s a language model trained by OpenAI. These issues arise from biases in the training data (trainers prefer longer answers that look more comprehensive) and well-known over-optimisation issues.12

- Ideally, the model would ask clarifying questions when the user provided an ambiguous query. Instead, our current models usually guess what the user intended.

- While we’ve made efforts to make the model refuse inappropriate requests, it will sometimes respond to harmful instructions or exhibit biased behaviour. We’re using the Moderation API to warn or block certain types of unsafe content, but we expect it to have some false negatives and positives for now. We’re eager to collect user feedback to aid our ongoing work to improve this system.

## Conclusion

In conclusion, ChatGPT is a powerful language model that can generate human-like text that can be used for a wide range of natural language processing tasks. It’s important to have access to the pre-trained model and the OpenAI API to use it. The model can be fine-tuned for specific tasks by providing it with a dataset of labeled examples. However, fine-tuning the model requires a significant amount of computational resources, and care must be taken to use the model responsibly.

**Source: https://openai.com/blog/chatgpt**

To start with ChatGPT directly from the browser, register and start here (currently free with limitations): https://chat.openai.com/chat

Interesting? Do you want to integrate ChatGPT with VSCode? Learn how in this blog: https://dev.to/aws-heroes/become-a-code-ninja-with-codegpt-vscode-extension-4bdl