Issue 4: A/B Testing at Etsy, New Adversarial Attach, MLOps Landscape

The Comet Newsletter's fourth issue delves into several developments in AI and machine learning, including a new adversarial attack called DeepSloth, which targets Adaptive Deep Neural Nets to increase latency in model deployments across edge devices and cloud servers. The newsletter also highlights Etsy's use of the CUPED method for more accurate A/B testing by reducing noise with pre-experiment data, allowing for shorter experiments with smaller sample sizes. Furthermore, it explores the application of Transformers in Few-Shot Learning, demonstrating how large language models like GPT-Neo can perform tasks with minimal data input at inference time without domain-specific fine-tuning. Additionally, the newsletter discusses the burgeoning MLOps landscape, offering insights on selecting the right tools for machine learning projects through a decision framework that considers the specific needs and adoption strategies of organizations.

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