How does Google Workspace handle spam filtering?

Google Workspace employs advanced machine learning algorithms alongside user-defined filters to effectively handle spam filtering. The advanced machine learning technology analyzes vast amounts of data to identify patterns and characteristics of spam messages, enhancing its ability to detect and filter out unwanted emails before they reach a user's inbox. This intelligent system continuously learns and adapts, improving its accuracy over time as it processes new types of spam.

In addition to this sophisticated machine learning approach, Google Workspace allows users to set their own filters based on specific criteria they deem important. Users can define rules regarding which emails to block or prioritize, giving them greater control over their inbox. The combination of machine learning and customizable filters ensures a comprehensive and flexible spam filtering system that maximizes protection against unwanted emails.

Other methods mentioned, like manual reviews or simple keyword blocking, lack the efficiency and effectiveness of the machine learning approach. Manual reviews would be highly impractical given the volume of emails processed, while a basic keyword blocking system could easily fail to catch more sophisticated spam attempts that don't fit defined keywords.