Quantum computers promise to speed calculations dramatically in some key areas such as computational chemistry and high-speed networking. But they're so different from today's computers that ...

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 ...

Read the new whitepaper from the Microsoft AI Red Team to better understand the taxonomy of failure mode in agentic AI.

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 ...