machine learning

The rise of real-time AI and machine learning is reshaping the competitive landscape. Traditional batch-trained models struggle with model drift, leading to inaccurate predictions and missed opportunities. Platforms like Apache Kafka and Apache Flink enable continuous model training and real-time inference, ensuring up-to-date, high-accuracy predictions. This blog explores TikTok’s groundbreaking AI architecture, its use of data streaming for real-time recommendations, and how businesses can leverage Kafka and Flink to modernize their ML pipelines. I also examine how data streaming complements platforms like Databricks, Snowflake, and Microsoft Fabric to create scalable, adaptive AI systems.