Online Inference


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.