In this talk, we look at how Autonomous Optimization (AO) can help us drive quality improvements & growth in our products and services. AO is a new paradigm for leveraging AI (or Machine Learning) without dealing with complex pipelines, algorithms, models, or even data.
We present a complete walkthrough & live demo as well as several case studies including comparisons against traditional methodology such as A/B testing or Custom AI implementations. We also look at how experiments that appear perfectly sensible on the surface can still waste precious time and effort when compared to an AO procedure that can virtually guarantee metric improvements simply by eliminating inherent human biases and allowing relevant segments and personal/contextual behavior to emerge out of the optimization process.
What will you learn?
Autonomous Optimization drive quality improvements & growth
Complete walkthrough & live demo.
Case study comparisons against A/B testing or Custom AI implementations.
Founder & CEO of Scaled Inference. previously an engineer in Google Brain focusing on deep learning, leading several core platform projects