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ExecuTorch is the PyTorch inference framework for edge devices developed by Meta with support from industry leaders like Arm, Apple, and Qualcomm. Running machine learning (ML)...
Since January 2025, ten elite university teams from around the world have taken part in the first-ever Amazon Nova AI Challenge, the Amazon Nova AI Challenge...
Meta has developed Privacy Aware Infrastructure (PAI) and Policy Zones to enforce purpose limitations on data, especially in large-scale batch processing systems. Policy Zones integrates with...
Hardware faults can have a significant impact on AI training and inference. Silent data corruptions (SDCs), undetected data errors caused by hardware, can be particularly harmful...
Tabular data powers critical decisions across domains such as healthcare, finance, e-commerce, and the sciences. The machine learning methods traditionally used for tabular data, however —...
Foundation models (FMs) such as large language models and vision-language models are growing in popularity, but their energy inefficiency and computational cost remain an obstacle to...
Large language models (LLMs) have come a long way in enforcing responsible-AI standards through robust safety mechanisms. However, these mechanisms often err on the side of...
Meta has developed an open-source AI tool to design concrete mixes that are stronger, more sustainable, and ready to build with faster—speeding up construction while reducing...
In many of today’s industrial and online applications, identifying anomalies — rare, unexpected events — in real-time data streams is essential. Anomalies can indicate manufacturing defects,...
Have you ever worked is legacy code? Are you curious what it takes to modernize systems at a massive scale? Pascal Hartig is joined on the...