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2 stories in the last 3d

Axoflow Launches AxoDetect, Bringing Detection Into the Pipeline and Making the SIEM Optional

Axoflow launches AxoDetect in early access, running customer Sigma rules in the data pipeline to cut SIEM ingest costs and make full SIEM feeding optional.

Axoflow announced AxoDetect, now in early access and unveiled at Splunk .conf26, which runs customer Sigma rules directly in the security data pipeline on normalized data. Alerts travel to the SIEM while full-fidelity logs land in AxoLake, a low-cost on-prem-capable security data lake. The company cites a global industrial company cutting SIEM costs 50% and mean time to resolution 85%, and a government agency cutting data volume 80%.

GBHackers · 10h agoTools 2 sources

Sakana AI Researchers Introduce PC-ALM, a Layer-Local Alternative to Backpropagation That Trains 1000-Layer Networks

Sakana AI's PC-ALM adds per-layer Lagrange multipliers to predictive coding, matching backprop on networks up to 1000 layers with layer-local updates.

Sakana AI researchers propose Augmented Lagrangian Predictive Coding (PC-ALM), a training method that keeps every update layer-local while recovering backprop-aligned credit signals. The team proves multipliers converge to exact backprop adjoints in linear networks and trains 1000-layer residual MLPs on MNIST within about 2 points of backprop accuracy. PC-ALM matched backprop across a width/depth grid from 8 to 128 on MNIST and Fashion-MNIST where standard predictive coding failed in deep, narrow networks, and improved over PC on ResNet-18 with CIFAR-10 and Tiny ImageNet. An MIT-licensed JAX reference implementation reproduces the results on CPU.

MarkTechPost · 2d agoAI research1