ChatGPT, the AI tool garnering significant attention nowadays, exhibits commendable performance across various tasks. However, what if its performance doesn’t align with the rigorous standards set by you or your company? Addressing this, OpenAI, the creator of ChatGPT, has introduced a solution aimed at assisting companies using the ChatGPT 3.5 API to refine and train the AI assistant, enabling it to generate content that precisely meets their requirements.
OpenAI tweeted that “fine-tuning allows you to train the model using your company’s data and deploy it at scale.” The organization further asserts that the customized models resulting from fine-tuning can even rival or surpass the capabilities of GPT-4 for specific tasks.
The concept of fine-tuning involves tailoring the model to suit business needs. OpenAI disclosed that since the launch of GPT-3.5 Turbo—an API accessible to businesses and organizations—users have expressed interest in personalizing the model to create unique and exceptional interactions. With this recent launch, developers can now engage in supervised fine-tuning to enhance the model’s performance for their specific use cases.
OpenAI clarified that, akin to ChatGPT, the GPT-3.5 API will remain pre-trained using data up until September 2021. Additionally, any custom training and fine-tuning applied by organizations to the API for their specific purposes will remain isolated to their applications, with the custom data not being utilized to enhance any other OpenAI applications.
Wondering how companies can leverage this new GPT feature? Here’s an illustrative example: Suppose your company operates a customer care service, utilizing the GPT 3.5 API to power an AI tool that engages with customers. With the new feature in place, you can instruct and educate GPT-3.5 to respond to customers using your distinct approach and tailored solutions.
This innovative feature arrives just days after OpenAI introduced custom instructions for ChatGPT users. This functionality enables the AI chatbot to tailor its responses based on user preferences. Users are prompted to furnish an introduction that answers questions such as “What information should ChatGPT be aware of about you?” and “How should ChatGPT adapt its responses to your preferences?”
Once the introduction is provided, ChatGPT incorporates the user’s customized instructions into all ensuing conversations. The model consistently factors in these instructions when generating responses, negating the need for users to specify their preferences repeatedly in each conversation.
For instance, a novelist can inform ChatGPT about the genre, tone, and target audience of their work. This enables ChatGPT to produce text that aligns with the author’s creative vision. Similarly, a student preparing for an exam can apprise ChatGPT of the subject matter, empowering it to generate relevant practice questions and study materials tailored to the student’s requirements.