What is fine-tuning in AI/ML?The process of adapting a pre-trained AI model to a specific task or domain by training it on additional data.
Fine-tuning is a technique used in machine learning and generative AI to customize a pre-trained model for a specific task or domain. It involves taking a foundation model that has already been trained on a large dataset and further training it on a smaller, more targeted dataset relevant to the desired application. This process allows the model to learn the nuances and specific characteristics of the target domain, resulting in improved performance and accuracy for that particular task.
Related:
In-package optical interconnects enable new generative AI architectures | Article
Unleashing the full potential of AI with in-package optical I/O | Article
Ayar Labs Optical I/O: Shattering the Barriers to AI at Scale | Video
In-Package Optical I/O for Generative AI Architectures | White Paper
Fine-Tuning Pre-Trained Models for Generative AI | Article
The Power of Fine-Tuning in Generative AI | Article
Fine-tuning in machine learning and AI | Article