Abstract: This work presents the design and implementation of a data-driven Nonlinear Model Predictive Control (NMPC) framework for an Uncrewed Aerial Vehicle (UAV) equipped with a 3-DOF robotic arm.

Washington-based Starcloud launched a satellite with an Nvidia H100 graphics processing unit in early November, sending a chip into outer space that's 100 times more powerful than any GPU compute that ...

The Power Grid Model DS project extends the capabilities of the power-grid-model calculation core with a modelling and simulation interface. This is aimed at building data science software ...

Abstract: FL is vulnerable to model poisoning attacks due to the invisibility of local data and the decentralized nature of FL training. The adversary attempts to maliciously manipulate local model ...

Accurate simulation of crop growth processes for predicting final yield is critical for optimizing resource management, particularly in regions with variable climates and limited resource availability ...

Enterprise software giant SAP SE is expanding its Business Data Cloud offering and doubling down on AI-ready data architectures, with product roll-outs and enhancements focused on bringing data and AI ...

It seems like everyone wants to get an AI tool developed and deployed for their organization quickly—like yesterday. Several customers I’m working with are rapidly designing, building and testing ...

Access: Setup our MCP servers in your LLM application in 2 clicks via our CLI tool (starting with Claude, see Roadmap for next steps). Publish: Use provided templates and guidelines to quickly ...

Behavioral information from an Apple Watch, such as physical activity, cardiovascular fitness, and mobility metrics, may be more useful for determining a person's health state than just raw sensor ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

When AI models fail to meet expectations, the first instinct may be to blame the algorithm. But the real culprit is often the data—specifically, how it’s labeled. Better data annotation—more accurate, ...