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Safety Research

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Monday, 14 September 2026

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

MarkTechPost 1 month ago 26

Sakana AI researchers introduced Augmented Lagrangian Predictive Coding (PC-ALM), a layer-local learning method meant to replace backpropagation’s global credit assignment with predictive-coding updates. They report training 1000-layer residual MLPs on MNIST for 5 epochs while staying within about 2 percentage points of backprop accuracy. The method adds per-layer Lagrange multipliers and improves accuracy over standard predictive coding, with released MIT-licensed JAX reference code reproducing results on CPU.

While Barack Obama urges Democrats to make AI a campaign issue, Trump downplays the need to slow development despite dire warnings

Fortune 11 ● 125 sources

Trump downplayed the need for his administration to check artificial intelligence development, arguing the U.S. should keep its lead in competition with China and saying wins matter more than slowing down. He said the U.S. is leading China in AI development while also suggesting unspecified “guardrails,” with no concrete rules described. As a result, calls from Democrats and AI leaders for concrete safety steps and slower development are met with promises of meetings but no specific congressional or regulatory plan, keeping the debate unresolved.

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