A new communication-collective system, OptiReduce, speeds up AI and machine learning training across multiple cloud servers by setting time boundaries rather than waiting for every server to catch up, ...

Real-time performance in ML enabled distributed systems requires more than just good engineering. It’s about building ...

Abstract: Decentralized quantum machine learning (DQML) represents an innovative fusion of two cutting-edge technologies: quantum computing and decentralized ...

Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various ...

After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, researchers organized them into a 'periodic table of machine learning' that can help scientists ...

Researchers have created a unifying framework that can help scientists combine existing ideas to improve AI models or create ...

Abstract: Geo-distributed machine learning (GDML) can facilitate collaborative learning among geographically-dispersed data centers to meet the demands of distributed and privacy-preserving training ...

Global AI advisor Zack Kass discusses the 'rush' to adopt artificial intelligence amid the ongoing tariff turmoil. Boosted.ai CEO and co-founder Josh Pantony on how artificial intelligence can ...

The first stage implements a custom data loader for MNIST dataset using C++ and OpenMP for parallel data loading and preprocessing. your_project/ ├── data/ │ └── mnist/ # MNIST dataset files ├── src/ ...

The third edition of the FLY AI Forum will be held on 22-23 April 2025 at our Brussels Headquarters, gathering key stakeholders to explore the transformative impact of AI in the aviation sector.

DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical ...