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NVIDIA-Backed Tests Explore Flexible AI-Factory Power Use During Grid Stress
Emerald AI, NVIDIA, EPRI, National Grid and Nebius tested software that reduced an AI factory’s electricity use during simulated grid emergencies while preserving selected high-priority workloads. One test reported roughly 30% less use within 40 seconds; commercial and grid-wide benefits remain unproven.
blogs.nvidia.comProduk
Ramp launches Router, a multi-model gateway that automatically balances cost and performance
Ramp says Router gives developers one endpoint for multiple AI models and can lower inference costs through automated model selection, but key performance and retention details remain unverified.router.comKeamanan
AWS expands AgentCore policy authoring for natural-language controls on AI agents
AWS says an expanded Policy Authoring feature can convert written rules into Dogwood policies that restrict agent actions over time, enforce prerequisites and limits, inspect free-form text with Bedrock Guardrails, and constrain tool inputs.aws.amazon.comInovasi
Microsoft expands access to Skala 1.1 for predictive chemistry simulations
Microsoft Research says Skala 1.1 improves accuracy over its predecessor while remaining near the computational cost of semi-local density-functional methods, and is now available in CP2K with integrations planned for other major chemistry packages.
microsoft.comInovasi
Code agents lose reliability when code is rewritten without changing its meaning, study finds
An arXiv preprint reports that code agents can perform differently on semantically equivalent codebases, with effects varying by model, agent framework and benchmark.arxiv.orgInovasi
Enhanced Fuzzy Logic Model for Power Transformer Fault Diagnosis Using IEEE Key Gas Method Improvements
This study presents an enhanced model combining Fuzzy Logic with the IEEE Key Gas Method (FL-KGM) that introduces refined membership functions, optimized fuzzy rule sets, and a novel separation of CO and CO2 to eliminate diagnostic inconsistencies.arxiv.orgInovasi
New preprint reports gains from looped language models in multi-step tool calling
An arXiv study evaluates looped and conventional language models on three tool-calling benchmarks, reporting stronger results on workflows that require multiple dependent API calls and a potentially more efficient adaptive-computation approach.arxiv.orgInovasi
Adversarial Review tests structured disagreement for agentic code review
A new arXiv paper proposes a three-agent code-review protocol in which a reviewer evaluates an agent’s code and a critic audits that review before edits are made. The authors report improved benchmark results over tested baselines, while also identifying false consensus as a failure mode.arxiv.orgInovasi
ArXiv study reports large Roman Urdu hate-speech gains from LoRA adaptation
An arXiv preprint compares zero-shot and parameter-efficient fine-tuning for hate-speech detection in Roman Urdu. The authors report that LoRA adaptation raised F1 performance from 0.56 to above 0.93 on a corpus containing more than 72,000 annotated comments.arxiv.org
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