Scaling quantum computing beyond a single device requires networking many quantum processing units (QPUs) into a coherent quantum-HPC system. We propose the Mod...
With the development of large-scale models, traditional distributed bilevel optimization algorithms cannot be applied directly in low-resource clients. The key ...
'Series: From “Just Put It on a Server” to Production DevOps Reading time: 15 minutes Level: Intermediate
As LLMs and foundation models scale, checkpoint/restore has become a critical pattern for training and inference. With 3D parallelism (tensor, pipeline, data), ...
The real estate sector remains highly dependent on manual document handling and verification, making processes inefficient and prone to fraud. This work present...
Federated Learning (FL) enables mobile edge devices, functioning as clients, to collaboratively train a decentralized model while ensuring local data privacy. H...
Survey findings include respondents noted that AI tools are increasing the blast radius of the amount of bad code that needs to be debugged....
DevOps isn’t dying – it’s evolving. That’s the perspective of Andi Grabner, who recently transitioned from DevOps Activist to Platform Engineering Advocate at D...
Terraform's type constraints help write IaC that is reliable, reusable, and easily maintained when building out AWS-based infrastructures. Ensuring your AWS var...
As Kubernetes adoption grows, so does operational complexity. What starts as a small cluster running a handful of services can quickly evolve into dozens of app...
DevOps practices are the core of contemporary organizational activities. Integrating artificial intelligence AI and machine learning ML into DevOps practices ca...
Modern cloud architectures demand self-adaptive capabilities to manage dynamic operational conditions. Yet, existing solutions often impose centralized control ...
