← Library · Advanced concept
Meta-Learning (Learning to Learn)
Meta-learning involves training models not just on data, but on how to learn from data. Instead of directly solving a specific task, a meta-learner learns an optimal inductive bias or an efficient learning algorithm that can then be applied to new, unseen tasks with minimal data and training. This allows models to adapt quickly to new scenarios.
In plain terms
It's like teaching a student how to study effectively for any new subject, rather than just teaching them the content of one specific subject.
Why it matters
It's crucial for achieving greater AI adaptability and data efficiency, especially in few-shot learning scenarios where data is scarce.
Learn one new AI thing every day.
Daily Deck sends you seven plain-English cards like this every morning. Free.
Start free