Online Inference
About #
Inferencing is the process of an AI model using what it learns to answer a question. This means the AI model takes the data (your question) and uses its training (all the information its been taught) to provide a response.
Online (real-time) inferencing is when an AI model processes data as soon as it gets it. When you have a conversation with a chatbot or use a language translation app, you are likely experiencing online inferencing.
Real World Use Cases #
-
Customer Service Chatbots: These chatbots use online inferencing to understand and respond to customer queries on the spot, providing instant assistance.
-
Fraud Detection in Financial Transactions: Banks use online inferencing to quickly analyze transactions as they happen to spot any signs of fraud and take immediate action.
Key Characteristics #
Key characteristics of online inferencing include:
-
Immediate Response: The main feature of online inferencing is its ability to provide instant results or decisions, crucial for applications requiring immediate feedback.
-
Continuous Data Processing: Unlike batch processing, online inferencing constantly analyzes data as it comes in, perfect for scenarios where data is generated continuously.
-
Resource Intensity: Because it requires immediate processing, real-time inferencing can be more demanding on computational resources.