Search: “renewable-energy”

Hackers Actively Exploiting Gitea n-day RCE Vulnerability in the Wild to Hijack Instances

Chinese-speaking Red Heron actors mass-exploit Gitea n-day RCE CVE-2026-60004 to steal source code, credentials, and pivot into victim networks.

Acronis Threat Research Unit reports active in-the-wild exploitation of Gitea RCE CVE-2026-60004 (CVSS 9.8, versions 1.17-1.27.0, fixed in 1.27.1) by a Chinese-speaking actor dubbed Red Heron. The actor scanned 1,386 Gitea servers across seven countries, held a separate list of 477 Taiwan-based targets, and confirmed victims in Canada, Argentina, Taiwan, the US, and Sri Lanka. Intrusions deployed the JITTERLY Linux implant with the SIXZUT LD_PRELOAD rootkit, stole password hashes and SSH keys, and in one case gained root admin access to a three-node Proxmox cluster.

Cyber Security News·updated Sep 15, 11:16 UTC · 1d ago·first Sep 15, 10:00 UTC · 1d agoExploit / PoC in the wild 3 sourcesCVE-2026-600041

US data centers could consume more natural gas than Germany and Japan combined by 2035

BloombergNEF projects US data centers will consume about 18 billion cubic feet of natural gas daily by 2035, exceeding Germany and Japan combined.

A new BloombergNEF report forecasts US data centers will consume roughly 18 billion cubic feet of natural gas per day by 2035, nearly double the estimate from nine months ago. On-site gas plants planned by Meta, Microsoft, Google, and Amazon would use 2.9-3.4 billion cubic feet per day, while grid-connected data centers drive an additional 15 billion cubic feet per day of power-sector gas demand. The added demand would generate about 1 million metric tons of extra greenhouse gas pollution daily, roughly 12% of current US emissions.

TechCrunch · AI·Sep 15, 18:29 UTC · 1d agoAI industry

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

Researchers release Explainability Assistant, an open-source conversational XAI tool using LLM function calling, lifting intent-parsing accuracy from 76.8% to 94%.

The paper introduces the Explainability Assistant, an open-source conversational XAI system for interpreting energy consumption forecasting models such as genetic-programming symbolic regressors. It uses LLM function calling instead of rigid custom grammars, achieving 94% intent-parsing accuracy versus 76.8% for prior work TalkToModel, and adapts to different ML problem types without task-specific fine-tuning. Comparative evaluation with energy domain specialists against a traditional XAI dashboard showed improved usability, with all experts preferring the conversational interface.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:40 UTC · 6d agoAI research1

A battery storage cyberattack would look exactly like a badly tuned controller

Risk modeling suggests a few hundred compromised grid-scale batteries dispatched through cloud optimizers could trigger blackouts in Texas or Great Britain.

Centrii analysis estimates 1,500 compromised one-megawatt units (5.4% of ERCOT's ~28 GW fleet) or 400 units (about 29% of Great Britain's ~1,400-unit fleet) could destabilize the grids, with modeled damage of $12-65 billion in Texas and a national blackout costing £2-10 billion in Britain. The study puts the probability of a major attack affecting at least one million people by 2031 at 92.1%, dropping to 61.4% with IEC 62443 certification and quarterly drills, based on 10,000 Monte Carlo runs. Because hostile battery swings are phased like legitimate frequency response, control rooms would see nothing unusual; Centrii proposes hunting for a reverse-governor signature where inverter output feeds oscillations. Spain's April 2025 blackout took an expert panel until March 2026 to rule out cyberattack, partly because key plants had no recordings.

Help Net Security·Sep 2, 00:00 UTC · 15d agoResearch

Bridging Control, Inference, Transport, and Thermodynamics: From Theory to Applications in Learning

Review connects control theory, optimal transport, probabilistic inference, thermodynamics, and machine learning via free-energy optimization under constraints.

The review unifies five fields: control theory, optimal transport, probabilistic inference, non-equilibrium thermodynamics, and machine learning. The common conceptual thread is optimization of free-energy-like functionals under dynamical or statistical constraints. Selected applications are presented in reinforcement learning, variational inference, and generative modeling. The tutorial-style text assumes no prior familiarity and begins from physics principles.

arXiv cs.AI / cs.LG / cs.CL·Sep 14, 17:16 UTC · 2d agoAI research

Previously unseen entry vector used to breach Polish energy plant

Help Net Security·Aug 11, 00:00 UTC · Aug 11, 2026Industry

Trump Targets Foreign Technology in New U.S. Power Grid Security Order

Trump's Executive Order 14420 declares a national emergency to restrict foreign-made bulk-power grid equipment over cyber, sabotage and supply-chain risks.

Executive Order 14420, signed August 26, declares a national emergency regarding the foreign supply of bulk-power system electric equipment to the United States. It empowers the Energy Secretary to restrict transactions with designated Covered Foreign Entities involving equipment, software, firmware, digital services, maintenance services, and remote-access capabilities. Covered equipment includes transformers, generators, inverters, RTUs, PLCs, intelligent electronic devices, and protective relays, with transmission rated 69 kV or higher in scope while local distribution is excluded. Already-installed foreign equipment may be subject to identification, isolation, monitoring, or replacement requirements, with phased compliance and pre-qualified vendor exemptions permitted.

Security Affairs·Aug 28, 18:00 UTC · 19d agoPolicy & legal

Powering AI is an architecture problem

Sponsored analysis argues AI data centers need medium-voltage, inline power architecture after Virginia grid faults knocked over 3GW of load offline.

A sponsored MIT Technology Review piece recounts a July 22, 2026 transmission fault in Ashburn, Virginia that shed more than 3 GW of data center load, and a 2024 incident where one failed surge arrester dropped about 60 facilities and 1,500 MW. It argues legacy UPS-based power stacks fail at AI scale because campuses can swing 70% of load in milliseconds and trip offline during grid disturbances. The proposed fix moves protection to medium voltage (13.8 kV and above) in inline enclosures near substations, improving density, permitting timelines, and backup power economics. A full-scale system tested at the DOE National Laboratory of the Rockies cleared ERCOT large-load ride-through requirements.

MIT Technology Review · AI·Sep 10, 11:00 UTC · 6d agoAI industry1

How much of a problem is AI’s water use?

Analysis finds AI's water footprint growing, with data-center location and cooling technology largely determining the local environmental impact.

The article examines the growing water consumption of AI data centers and argues that real-world impact varies significantly depending on where facilities are sited and which cooling technology they use. It is a contextual analysis of AI's environmental footprint rather than news of a specific incident, breach, or release.

Ars Technica · AI·Aug 27, 13:57 UTC · 20d agoAI industry

Large Language Models for HVAC Operations in Building Energy Systems: A Critical Review of Methods, Applications, and Deployment Readiness

Systematic review of 66 studies finds LLMs for HVAC operations are mostly research-stage, with no ready-now deployment and only four pilot-level studies.

A critical review of 66 peer-reviewed studies from 2023 to March 2026 examines LLMs for HVAC operations in building energy systems. Only four studies reach pilot-level evidence, none reports sustained operational deployment, and 63 of 66 are research-only. Conventional ML, MPC, and RL remain dominant for high-frequency control and short-horizon forecasting, and the evidence supports LLMs primarily as semantic and workflow layers rather than autonomous controllers.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:08 UTC · 12d agoAI research

Evaluating Time-Series Foundation Models and Multimodal Dietary Context for CGM Forecasting

Study finds zero-shot time-series foundation models underperform on CGM forecasting; fine-tuned Chronos-Bolt cuts RMSE up to 18.4% and dietary context adds signal.

The paper evaluates time-series foundation models for continuous glucose monitoring forecasting across eight public datasets covering Type 1 diabetes, Type 2 diabetes, and non-diabetes populations. Under a unified protocol, zero-shot foundation models did not consistently outperform baselines like Elastic Net and PatchTST, but lightweight fine-tuning did, with fine-tuned Chronos-Bolt reducing RMSE by 6.5%-18.4% in the T1D cohort and 8.6%-18.2% in the non-diabetes/T2D cohort. A residual-based fusion framework adding dietary context from CGMacros reduced overall RMSE by about 3% and postprandial RMSE by about 15% versus CGM-only baselines.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:43 UTC · 6d agoAI research

Suspected Iran-linked attack knocked UK power plant offline for days

Suspected Iranian hackers knocked a small UK power plant offline for four days in July 2026, with no noticeable impact on the national grid.

Sources told The Telegraph that a British power plant was offline for four days in July 2026 following a suspected Iranian cyberattack, reported to the National Cyber Security Centre. The UK energy minister said the incident affected a small-scale energy generator with no noticeable effect on the power supply, and energy CEOs were briefed and given further advice afterward. The attack followed warnings about Iranian cyber activity against US energy, water, and government networks, including a coordinated attack on 30+ US community water utilities.

Help Net Security·Aug 24, 00:00 UTC · 24d agoThreat actor

Schneider Electric Easergy, EcoStruxture, PowerLogic, and Saitel Products (Update A)

CISA updated ICSA-26-169-07: CVE-2026-4827 (CVSS 8.3) insufficient entropy enables session hijacking across dozens of Schneider Electric grid products; fixes available.

CISA republished advisory ICSA-26-169-07 (Update A) for CVE-2026-4827, CWE-331 insufficient entropy in session management, scored CVSS 8.3. Affected lines include Easergy MiCOM relays and C5, EcoStruxure Power Automation (EPAS-GTW, EPAS-UI, iPMFLS), EcoStruxure Power Operation, PowerLogic P5/P7/T300/T500, and Saitel DP/T150 RTUs, with dozens of fixed versions listed. Successful exploitation could enable session hijacking and unauthorized operations on systems in energy, chemical, critical manufacturing, and water sectors. Fixes are available; no exploitation is reported.

CISA Advisories·Sep 3, 12:00 UTC · 13d agoAdvisoryCVE-2026-4827

Generative Marketing Mix Modeling: A Causal Inference Framework Linking GEO and GEM to Business Impact

Paper proposes Generative Marketing Mix Modeling to causally estimate Generative Engine Optimization and Marketing effects on business outcomes.

The authors develop GMMM, a causal inference framework for measuring how often users see and notice a firm's name in generated answers, which standard marketing data ignore. For GEO it combines repeated generated answers with question counts, shares of generative-system usage and notice probabilities; for GEM it uses sponsored placement records with notice probabilities. The framework compares expected business responses under alternative treatment sequences, establishes identification conditions, and is evaluated on simulated product-recommendation answers in English and Japanese.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:57 UTC · 6d agoAI research

Wake-Up Call for CNI After Iranian Attack Shuts Down UK Power Plant

A cyber-attack attributed to Iran shut down a UK power plant, exposing the frailty of critical national infrastructure, security experts warn.

Security experts say an Iranian cyber-attack forced a UK power plant offline, describing the incident as a wake-up call for critical national infrastructure operators. The attack caused physical operational disruption at an energy facility. Technical details about the intrusion path and the affected operator remain limited in initial reporting.

Infosecurity Magazine·Aug 24, 09:01 UTC · 23d agoThreat actor in the wild

Closed-Loop Cooling Explained: The Plumbing Behind Meta’s AI

Meta engineer Tom Shaw explains the closed-loop liquid cooling systems that power Meta's AI data centers more efficiently.

Meta published an explainer describing its use of closed-loop liquid cooling to support AI workloads. The post, authored by Tom Shaw, frames the plumbing and thermal design as key to running AI infrastructure efficiently. The content is primarily corporate/infrastructure marketing rather than a security or product announcement.

Meta Newsroom·Aug 27, 21:44 UTC · 20d agoAI industry

Bipartisan Senate bill aims to prepare energy sector for Q

Bipartisan Senate bill would direct FERC to factor quantum computing threats and post-quantum cryptography into US electric grid cybersecurity reliability standards.

The Quantum Grid Utility Assurance and Resilient Defense (Quantum-GUARD) Act, introduced by Senators Mike Rounds and Chris Coons, would require FERC to consider quantum computing threats when reviewing electric reliability standards and to explore post-quantum cryptography use in both IT and OT systems, plus a technical sandbox to study quantum impacts. It aligns with NIST's post-quantum algorithm work, and a June executive order moved the federal PQC migration deadline from 2035 to 2030. Industry experts noted the hard part is upgrading infrastructure such as SCADA communications and software update integrity ahead of those deadlines.

CyberScoop·Aug 24, 19:01 UTC · 23d agoPolicy & legal

Separating AI's Technological Problems from Its Capitalism Problems

Schneier and Sanders argue AI's harms stem from capitalist incentives and governance gaps, not just technical limits, urging structural reform.

Writing with Nathan E. Sanders in Tech Policy Press, Bruce Schneier argues that AI's technological problems (hallucination, sycophancy, overconfidence) must be separated from socio-political problems created by capitalist market incentives. The essay contrasts US frontier-scale, energy-intensive development with China's incentive-driven leaner open models on commodity hardware, and cites Switzerland's Apertus model - trained on licensed data using public computing and renewable hydropower - as a public-interest alternative. It contends that proposals like research pauses, data-center moratoria, and federal screening conflate technology problems with governance problems, and that society faces independent choices on both axes.

Schneier on Security·Aug 15, 00:00 UTC · Aug 15, 2026AI policy

Water sector example added to the NCSC’s Secure connectivity principles

NCSC UK adds a water sector example to its Secure Connectivity Principles, the first ICS community-authored content on its site.

The UK NCSC has added a water sector example to its Secure Connectivity Principles guidance. It is the first content authored by the Industrial Control System Community of Interest to appear on ncsc.gov.uk. The guidance helps ICS operators apply secure connectivity practices.

NCSC UK·Aug 11, 12:00 UTC · Aug 11, 2026Advisory

Deep Learning-Based Detection of Electrical Faults and Power Quality Disturbances in Aerospace Power Systems

Compact ResNet detects electrical faults in 400 Hz aircraft power systems with 95.87 percent accuracy after deployment on Xilinx Zynq MPSoC.

The study targets multiclass fault and power quality disturbance detection in 400 Hz aerospace networks using a high-fidelity simulation model inspired by the Boeing 787 electrical architecture, covering 21 normal, disturbance, switching, open-circuit, and short-circuit conditions. Two 73,500-sample datasets are built from 1D waveforms and STFT time-frequency representations, augmented with domain randomization and class-specific GANs, and the time-series dataset is released via IEEE DataPort. A compact ResNet with 175,685 parameters achieved 96.94 percent software test accuracy, and 95.87 percent after 8-bit quantization on a Xilinx Zynq UltraScale Plus ZCU102 with 6.90 ms mean accelerator latency per record.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 17:19 UTC · 7d agoAI research

The Convergence of Space and Cyber: Evolving Threats in the Space Race 2.0

Recorded Future whitepaper warns nation-state cyber operations targeting satellites, ground stations and space supply chains will intensify during 'Space Race 2.0'.

Recorded Future's whitepaper argues that cyber operations will be decisive in the second space race, with espionage, destructive attacks, supply chain compromise and signal hijacking already affecting orbital assets and ground infrastructure. It predicts nation-states will extend cyber targeting toward deep-space ambitions such as lunar colonization and asteroid mining. The paper references the SPARTA adversarial framework and forums like Defence Space 24, and highlights US Space Command's integration of cyber and intelligence into space operations.

Recorded Future·Sep 9, 00:00 UTC · 8d agoResearch

Emerald AI, Google and NVIDIA Launch Alliance to Advance Flexible AI Data Centers

Emerald AI, Google, and NVIDIA launched the AI Energy Management Alliance to promote power-flexible, grid-responsive AI data centers.

Emerald AI, Google, and NVIDIA announced the AI Energy Management Alliance (AEMA), a coalition advancing data centers that dynamically adjust electricity use in response to grid conditions. The technology-neutral, performance-based alliance will standardize flexibility requirements, define ride-through and curtailment obligations, and create faster interconnection pathways for facilities making verifiable flexibility commitments. It plans to convene AI platforms, data center operators, utilities, power producers, and grid operators to support US AI infrastructure growth.

NVIDIA Blog·Sep 16, 13:00 UTC · 16h agoAI industry

Lightweight Vision Transformer Compression for On-Device Plant Disease Detection in Resource-Constrained Agricultural Field Conditions

A unified ViT compression pipeline (H-BAC pruning, quantization, distillation) cuts plant-disease models 54.5x to 6.01 MB while keeping 95.13% accuracy.

Researchers combined Hessian-Balanced Adaptive Block Pruning (H-BAC), guided by second-order sensitivity estimation, with quantization and attention-based knowledge distillation to compress Vision Transformers for on-device chilli plant disease detection in India. On a 3-class cross-village, cross-device out-of-distribution dataset, the integrated pipeline reduced model size from 327.42 MB to 6.01 MB (54.5x) at 95.13 +/- 2.32% accuracy, matching the 95.13% FP32 baseline. Ablations also show a directly trained 6.01 MB INT8 student reaches 94.87% accuracy, indicating where pruning and distillation add limited value.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:40 UTC · 12d agoAI research

Saving Jet Fuel

Tutorial optimizes flight paths to cut jet fuel costs using open-source Scikit-decide planning framework and OpenAP aircraft performance models.

A technical walkthrough demonstrates wind-aware flight path optimization using Scikit-decide, an open-source framework for reinforcement learning and automated planning, paired with OpenAP fuel-consumption models built by Dr. Junzi Sun at TU Delft and NOAA wind data. A Boeing 787-9 flying EWR to FCO can require roughly $68K in fuel, and adjusted routing could save thousands. The post uses Python 3.12, DuckDB with spatial extensions, and QGIS for map rendering.

Hacker News · AI·Sep 15, 23:17 UTC · 1d agoAI tools & infraHN 45↑ · 19 comments

Learning-Guided Planning in Large Dynamic Action Spaces: Budgeted Tree Search for One-to-Many Mobile Charging

LP-BTS uses graph proposal policies, learned critics, and budgeted PUCT search to plan mobile charging across dynamic action spaces up to 2,813 stops.

LP-BTS is a learning-guided planning architecture for one-to-many mobile charging, where N=250 sensors induce roughly 1,125 initial candidate charging stops. A graph proposal policy concentrates candidate support, a learned value critic evaluates leaves, and edge-budgeted PUCT compares simulated futures, letting a single frozen checkpoint cover action universes from 736 to 2,813 stops. On a sealed 30-scenario confirmatory bank it attains the highest observed survival (0.4545) and alive-AUC (0.8031), though its +0.0066 survival edge over the strongest engineered comparator is statistically unresolved.

arXiv cs.AI / cs.LG / cs.CL·Sep 15, 16:42 UTC · 1d agoAI research

Lessons from the hacks

The recent run of cyberattacks by in-development frontier models has got me thinking a lot about how our current incentive systems are not well suited for such fast technological transitions. The two primary power structures here are the rapidly growing technology companies and the federal government. The companies are incentivized to grow, so they can keep growing and keep scaling – in what is…

Interconnects·Aug 9, 14:57 UTC · Aug 9, 2026AI research

Cyber threats nudge Trump to sign executive order on foreign equipment in U.S. energy infrastructure

Trump signed an executive order declaring an emergency to bar foreign bulk-power equipment deemed a national security cyber risk.

The executive order, 'Declaring a National Energy Emergency to Secure the United States Bulk-Power System,' prohibits acquiring, importing, transferring, or installing foreign-produced bulk-power equipment and software deemed risky, citing fears of digital backdoors in Chinese-made grid gear. China supplies roughly 85% of solar supply chain capacity and is a major transformer manufacturer. The Energy Department has 120 days to develop implementing rules; the order revives a 2020 Trump-era measure the Biden administration had suspended after utilities found compliance difficult.

CyberScoop·Aug 26, 21:47 UTC · 21d agoPolicy & legal1

Securing the Infrastructure of Intelligence

NVIDIA positions AI factories combining chips, networking, power and data as the defining infrastructure of the AI economy needing full-stack security.

NVIDIA's blog argues that AI factories are the defining infrastructure of the AI era, transforming energy and data into intelligence that powers businesses and countries. It frames compute as revenue and lists the full stack of critical resources required: advanced chips, packaging, memory, networking, land and power. The piece is a corporate positioning article about securing this infrastructure, with no specific incident or product announcement detailed in the excerpt.

NVIDIA Blog·Aug 17, 12:34 UTC · Aug 17, 2026AI industry

Multi-Task Learning for Sparsely-Labeled Time Series: A Case Study on Cold-Hardiness Modeling

Multi-task RNN architectures pooling sparse cultivar data improve grape cold-hardiness and budbreak prediction over single-task and scientific baselines.

Researchers apply recurrent neural networks to daily grape cold-hardiness prediction from weather time series, where per-cultivar labels are temporally sparse and limited. They design multiple multi-task learning architectures that treat cultivars as tasks and evaluate them in both MTL and transfer learning settings. Certain architectures consistently outperform single-task learning and state-of-the-art scientific models, and a single MTL model jointly learning cold hardiness and budbreak improves accuracy on both tasks.

arXiv cs.AI / cs.LG / cs.CL·Sep 8, 17:17 UTC · 8d agoAI research

One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation

A review paper frames on-policy self-distillation collapse as governed by three levers: token weighting, privileged information, and guidance decay.

The paper critically reviews On-Policy Self-Distillation (OPSD), where a language model trains on its own generations scored token-by-token by a teacher conditioned on privileged information such as reference solutions or environment feedback. It identifies collapse, the progressive narrowing of producible reasoning paths, as the dominant failure mode and analyzes it through three levers: signal weighting, the nature of privileged information, and teacher dynamics. The review is restricted to mathematical reasoning, reports no new experiments, and offers a shared vocabulary separating settled findings from disputed ones.

Hugging Face daily papers·Aug 25, 20:00 UTC · 22d agoAI research

From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production

NVIDIA detailed DSX power-management results: Lambda gained 24% token throughput at fixed power, and an AI factory auto-shed 1MW via Emerald AI's grid program.

NVIDIA says Lambda's first validation of DSX MaxLPS on HGX B200 servers ran 19 nodes within a 16-node power budget, lifting cluster token throughput 24% (roughly 4M to 5M tokens/second) and improving performance per watt by 23%. NVIDIA projects DSX MaxLPS can enable up to 40% more GPU capacity for Vera Rubin NVL72 factories within the same megawatt budget. Emerald AI's Conductor platform, running at NVIDIA's Eos factory with Silicon Valley Power, responded to over 200 utility demand signals, automatically dropping power from 4MW to 3MW without interrupting priority workloads. The first dedicated DSX Flex commercial deployment is planned at a 96-megawatt Manassas, Virginia facility.

NVIDIA Blog·Sep 15, 16:55 UTC · 1d agoAI industry