Static network baselines won't survive agentic AI
… Because drift is also a leading contributor to outages, adaptive calibration reframes it as an operational condition to be managed continuously rather than a hygiene problem solved periodically. …
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… Because drift is also a leading contributor to outages, adaptive calibration reframes it as an operational condition to be managed continuously rather than a hygiene problem solved periodically. …
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Learning mappings between infinite-dimensional function spaces, or operator learning , is essential for many machine learning applications. Although transformer-based operators are popular, they…
Papers arxiv:2605.13834 Topology-Preserving Neural Operator Learning via Hodge Decomposition Published on May 13 Submitted by Tao Zhong on May 15 Princeton University Authors: , Tao Zhong , Abstract Physical field equations…
… With memory, they build operational intelligence that compounds over time, making them more effective with each interaction. …
What I learned using AI to build a Kubernetes Operator for Supabase's Multigres
Hi HN, Francesco from Cua here. I hacked this project together last weekend, inspired by the Codex Computer-Use release and lessons learned from deploying GUI-operating agents for our customers.The main problem: when a U…
Hi HN, Alexey from Chainstack here.We built Chainstack Self-Hosted to package everything we’ve learned from 8+ years of running blockchain nodes into a single control panel. The goal we’re building this product around is…
I believe I landed a jack of all trades role and im having severe imposter syndrome. Not trying to be too detailed here, but I also have the ability or opportunity to also *possibily* redesign the network. Granted it's a…
Hi, in the last ~month I've learned a lot about ECS [1,2].I'm currently developing a robotics simulator from scratch (python+raylib) and, due to lack of game dev experience I went "full OOP" on it. A SceneObject with a l…
… TCG ensures that operational evidence remains tied to the correct system state before it influences convergence decisions. Causality Before Pattern Recognition As AI-assisted operational systems continue scaling, another critical distinction emerges. …
…What I did not learn was Linux itself, as an operating system. Earlier generations of Linux users learned Linux differently because Linux was the host machine. If the audio broke, you fixed…
…Deep Koopman methods learn flexible coordinates, whereas structure-preserving methods enforce operator identities on fixed dictionaries. We combine these ideas by introducing Deep Embedded Multiplicative Dynamic Mode Decomposition (DeepMDMD), a method that…
…Abstract Deep reinforcement learning framework L2C2 addresses prior mismatch in tabular foundation models by sequentially applying data cleaning operators to align real-world data with synthetic training distributions, improving both accuracy and…
… Breaking Operational Silos Traditional dashboards reflect organizational boundaries, not necessarily system reality. …
…Quantum Transformer (2026) Toward General Quantum Control with Physics-Informed Large Language Models (2026) Learning Logical Operations for Arbitrary Quantum Error Correction Codes (2026) Please give a thumbs up to this comment…