MLOps Community Mini Summit #1

Let's highlight a comprehensive agenda addressing the security and ethical challenges of deploying Large Language Models (LLMs). We'll cover topics ranging from LLM security and the risks of prompt injection, denial of service, and model theft to concerns surrounding insecure plugins and overreliance on LLMs. The agenda also includes strategies for tackling these issues and explores data poison mitigation through differential privacy.

In this talk, Uri introduces a new OSS we've developed named GeniA, and discusses its role as an enabler for the future of platform engineering using Gen AI.

Time series data is ubiquitous across science, engineering, and business. Proper statistical analysis of time series requires quantifying uncertainty in models and forecasts. Bootstrapping is a powerful resampling technique for this, but classical bootstrap methods fail for time series because they disrupt dependencies. This talk introduces tsbootstrap, an open-source Python library implementing state-of-the-art bootstrapping tailored for time series. It covers essential techniques like block bootstrapping along with cutting-edge methods like Markov and sieve bootstrapping. We'll provide an intuitive overview of key time series bootstrapping approaches and demonstrate tsbootstrap functionality for resampling financial data. Users can leverage tsbootstrap for robust confidence intervals, model validation, and distribution-free inference.