online learning
What It Means
Online learning refers to AI systems that continuously update and improve their models as new data arrives in real-time, rather than being trained once on a fixed dataset. The system learns and adapts on-the-fly as it processes each new piece of information, making it highly responsive to changing patterns and conditions.
Why Chief AI Officers Care
This approach enables AI systems to stay current with rapidly changing business conditions without requiring expensive retraining cycles or downtime. It's particularly valuable for applications like fraud detection, recommendation engines, and market analysis where patterns shift frequently and outdated models quickly lose effectiveness.
Real-World Example
A credit card company's fraud detection system uses online learning to immediately incorporate each new transaction and its fraud status into the model, allowing it to instantly recognize emerging fraud patterns like new scam techniques or seasonal shopping behaviors without waiting for monthly model retraining cycles.
Common Confusion
People often confuse online learning with e-learning or web-based education platforms. In AI, 'online' refers to real-time data processing and model updates, not internet-based learning environments.
Industry-Specific Applications
See how this term applies to healthcare, finance, manufacturing, government, tech, and insurance.
Healthcare: In healthcare, online learning enables AI systems to continuously adapt to evolving patient populations, treatment proto...
Finance: In finance, online learning enables trading algorithms, fraud detection systems, and credit scoring models to adapt cont...
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Includes:
- 6 industry-specific applications
- Relevant regulations by sector
- Real compliance scenarios
- Implementation guidance
Technical Definitions
NISTNational Institute of Standards and Technology
"fitting [one's] model incrementally as the data flows in (streaming data)."Source: Ben_Auffarth_2021
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