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Engineering is viewed here not merely as a collection of technical disciplines, but as a distinct mindset focused on solving practical problems through decomposition and synthesis. In this collection, we explore the design of resilient systems – ranging from fundamental hardware solutions to flexible software architecture. Our focus lies in the logic behind design decisions: why specific materials are chosen, how fault tolerance is ensured, and the ways in which theoretical models are transformed into working mechanisms.
Researchers have demonstrated how to fine-tune AI models to replace complex physics simulations – making them faster and cheaper than running calculations from scratch.
Amazon Bedrock now supports persistent orchestration and memory for AI agents, changing the approach to building multi-step workflows.
AI: Events
Technical context • Development
The TorchAO developers have expanded their toolkit for quantization-aware training, now supporting new architectures, modes, and tasks.
Kubetorch has joined the PyTorch ecosystem, simplifying the process of running ML tasks on Kubernetes by abstracting complex infrastructure behind simple Python code.
What if you could train a massive neural network using half the memory – without breaking anything? That's exactly what the creators of FlashOptim are exploring.
NeuroBlog
Science & Technology • Computer Systems
From the first server at CERN in Switzerland to a global network of five billion users, we break down exactly how the technology we use every day works.
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