IEEE (Organization): news timeline & CVEs

Building a safer path to autonomous industrial AI

AVEVA's chief technologist outlines human oversight and guardrails for autonomous industrial AI.

In a sponsored MIT Technology Review Business Lab episode, AVEVA chief technologist Arti Garg discusses deploying foundation models, physical AI, and agentic systems in industrial environments. She says adoption in the sector has risen sharply, citing a study suggesting about a 78% increase in two years, while less predictable models complicate safety in plants and power systems. AVEVA's responsible-AI framework emphasizes security, efficiency, and human oversight rather than removing people from critical decisions. Garg also participates in an IEEE working group developing methods to measure AI's electricity, water, and carbon footprint.

MIT Technology Review · AIOct 8, 08:17 UTC · 2d agoAI industry1

What makes software development engineering

An essay argues software engineering means systematic, constrained design, tracing the idea to the 1968 NATO conference.

The essay asks why software engineer implies more rigor than coder, programmer, or developer. It traces the idea to the 1968 NATO Software Engineering Conference, the software crisis, and debates over ALGOL 68 and structured programming associated with Edsger Dijkstra. It cites UNESCO, the US National Academies, and IEEE, and notes that SWEBOK defines software engineering as a systematic, disciplined, quantifiable approach to building and maintaining software.

Hacker News · AISep 29, 13:31 UTC · 11d agoOther HN 40↑ · 46 comments1

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.CLSep 9, 17:19 UTC · Sep 9, 2026AI research

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Building a safer path to autonomous industrial AI

What makes software development engineering

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