Deploying a new machine learning model to production is one of the most critical stages of the ML lifecycle. Even if a model performs well on validation and test datasets, directly replacing the ...

Abstract: Deep Learning (DL) frameworks are fundamental components of DL systems in their development, deployment, and execution, while defects in DL frameworks can cause severe consequences. Ensuring ...

As new large language models, or LLMs, are rapidly developed and deployed, existing methods for evaluating their safety and discovering potential vulnerabilities quickly become outdated. To identify ...

In December, Howard Marks published an investment memo titled, “Is it a bubble?” that expressed some of his skepticism and reservations about artificial intelligence and the stock-market boom it had ...

Abstract: This paper focuses on constructing a Selenium-based Web automation testing framework to address issues such as high testing costs, low efficiency, poor script maintainability, and ...

We collaborate with the world's leading lawyers to deliver news tailored for you. Sign Up for any (or all) of our 25+ Newsletters. Some states have laws and ethical rules regarding solicitation and ...

Learn how to build and test narrowboat steps with this companionway tutorial, covering precise measurements, secure installation, and safety checks. Perfect for DIY narrowboat owners aiming to improve ...

In this tutorial, we show how we treat prompts as first-class, versioned artifacts and apply rigorous regression testing to large language model behavior using MLflow. We design an evaluation pipeline ...

The National Institute of Standards and Technology is asking industry, government and research stakeholders to weigh in on a new draft framework aimed at improving how language models are evaluated ...

ServiceNow implementations evolve through frequent configuration changes, scoped application releases, and scheduled platform upgrades. These changes elevate regression risk across mission-critical ...