Brookhaven, Princeton Plasma Physics Laboratory, DIII-D and Great Sky demonstrated a superconducting neural-network chip on plasma-control tasks. Two tasks used DIII-D data sampled at one million points per second; another used simulated data.
A preprint presents CEMA-Router, an infrastructure-aware method for routing batches of language-model inference requests across cloud and edge resources. The design considers differences in compute capacity, energy efficiency, network conditions and model quality.
US oil and gas producer Chord Energy said its third-quarter 2026 production volumes exceeded the high end of prior guidance for oil, natural gas and natural gas liquids. The financial figures were preliminary and not yet finalized.
The paper introduces a type system for describing clock-sensitive communication protocols between hardware components. It aims to identify mismatches that can lead to unsynchronized exchanges or stalled progress when separately designed components are combined.
Del Monte Foods North America announced two new canned vegetable products: whole-kernel corn seasoned with Hidden Valley Ranch flavor and cut green beans with an Italian-inspired vinaigrette profile.
Eni and Libya’s National Oil Corporation say the Bouri project is complete and entering start-up, with recovered gas planned for domestic supply and possible exports.
US battery maker Eos Energy estimated third-quarter revenue of $82 million to $83 million and a gross margin of negative 55% to negative 53%. The company said the figures are preliminary and it will publish its full financial report later.
Researchers propose UnO-NeSy, a unified ferroelectric field-effect transistor in-memory architecture for neuro-symbolic AI. The paper targets the memory demands of combining neural perception with symbolic reasoning and hyperdimensional computing.
A FERMA notice invited the Bureau of Public Procurement to witness a 19 October bid opening for urgent road rehabilitation and maintenance work under the 2026 appropriation, phase two.
The paper studies a hybrid architecture that pairs GPUs with processing-near-memory resources and shared DRAM for large language model inference. It focuses on prefill and decode phases, which stress compute and memory bandwidth differently when serving requests.
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