Adam Englander has been architecting and developing systems for over 30 years. He's also been a maintainer or contributor to significant projects in the OSS ecosystem. Most recently, Adam has been using artificial intelligence to revolutionize the insurance industry.
Session en anglais - Débutant
Integrating AI into your application transforms the traditional software development and DevOps lifecycle. Unlike standard code, LLM outputs can vary for the same input, leading to different accuracy levels. This affects both pre-deployment testing and post-deployment monitoring. To achieve and maintain quality, you will learn to apply ML/LLM Ops practices from data science within your software development and DevOps lifecycles.
Session en anglais - Débutant
In this emerging AI era, delivering AI-based applications no longer requires data scientists. This shifts responsibility for AI output quality to QA and software engineers. Traditional tools and methods, however, are inadequate for measuring quality in these applications. Learn how to apply data science best practices to develop and maintain high-quality AI solutions.