Continuous tech-debt monitoring & governance Tech debt removal is typically reactive and ad-hoc exercise. AI can help run periodic scans, update debt scores, and feed insights into tech governance ...
Going to the database repeatedly is slow and operations-heavy. Caching stores recent/frequent data in a faster layer (memory) ...
Abstract: Anchor-based clustering methods have attracted increasing attention due to their ability to provide efficient and scalable solutions in clustering tasks, such as subspace, multi-view and ...
Abstract: The density peaks clustering algorithm is one of the density-based clustering algorithms. This algorithm has several advantages, including not requiring a preset number of clusters, ...
Real-world test of Apple's latest implementation of Mac cluster computing proves it can help AI researchers work using massive models, thanks to pooling memory resources over Thunderbolt 5. One month ...
The introduction of RDMA over Thunderbolt in macOS 26.2 marks a significant leap forward for local AI and HPC workflows. This feature allows Mac Studio systems to pool memory seamlessly, allowing ...
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