Topic

A/B testing: a key engine in the era of big AI models

Synopsis: A/B testing, as a scientific experimental method, has become an important tool for enterprises to build an efficient data infrastructure through accurate data analysis and continuous optimization. It not only improves the accuracy of business decisions, but also promotes data-driven innovation and growth. In the era of AI big models, the quality and accuracy of data directly affects the performance of the model. A/B testing improves the effectiveness of AI models by optimizing model training data, ensuring that enterprises take the lead in an intelligent and data-driven future. Through this sharing, we aim to provide attendees with a comprehensive understanding of the core role of A/B testing in the new data infrastructure, especially in the data infrastructure in the era of AI big models. It is hoped that the practical examples and in-depth analysis will help organizations better leverage A/B testing to drive data-driven innovation and growth. Outline: 1.Introduction and A/B overview 2.Importance of A/B testing to drive new data infrastructure 3.Data Infrastructure and A/B Testing in the Age of AI Big Models 4. future plans and outlook