Fine-tuning FLAN, instructGPT, and chatGPT: Protecting Privacy & Improving Accuracy

Instruction Tuning: Comparing FLAN, instructGPT, and chatGPT
In the world of artificial intelligence and natural language processing,Instruction Tuning is a critical component of improving the performance of models. This article focuses on three specific models - FLAN, instructGPT, and chatGPT, and highlights the key phrases and concepts associated with each.
FLAN (Federated Language Models)
FLAN is a type of machine learning model that focuses on training language models without the need for centralized data collections. This is achieved through a process called “federated learning,” which involves training models on decentralized data sources spread across multiple devices or locations.
FLAN’s primary advantage is its ability to protect user privacy while improving model accuracy. By training models on local data sources, sensitive information is never exposed to a central server, reducing the risk of data breaches or unauthorized access. Additionally, FLAN’s decentralized approach allows models to benefit from a larger, diverse dataset without the need for centralized