Researchers at the University of Southern California (USC) have developed a new approach to machine learning known as Lifelong Learning (LL). This approach allows AI agents to continuously learn and retain knowledge from previous tasks as they encounter new ones.
To facilitate this shared knowledge approach, the researchers introduced the SKILL (Shared Knowledge Lifelong Learning) tool. AI agents using SKILL were able to master 102 distinct tasks, including categorizing car models, flower species, and chest X-ray diseases.
SKILL employs algorithms that enable AI agents to learn simultaneously in parallel, significantly reducing the time needed for learning. The study found that when AI agents individually learn a task and then share, the time needed decreases by a factor of 101.5.
This groundbreaking approach has the potential to be expanded to encompass thousands or even millions of tasks. It holds the promise of transforming various aspects of human life and fostering a profoundly interconnected and intelligent global community.
The researchers view the SKILL tool as a promising advancement in Lifelong Learning (LL) research, primarily due to the extensive array of natural tasks explored in their study.
They believe that this approach can be expanded to encompass thousands or even millions of tasks, leading to potential transformations in various aspects of human life.
Furthermore, future research can explore more sophisticated tasks that AI agents can undertake, opening up countless opportunities for advancements and innovation in various fields.
The capability to share knowledge, similar to humans' ability to exchange information, has the potential to revolutionize various professions and foster an interconnected global community.