SPIN Unprocessed September 2, 2026 ai_technology research
Flawed in Nature, Perfect through Evolution
View original on arxiv.orgOverview
arXiv:2609.00129v1 Announce Type: new Abstract: The performance of artificial intelligence (AI) and machine learning (ML) models degrades when the problem they were trained on drifts. This is a near-universal feature of real-world problems, which often change unpredictably. Biological evolution has achieved intelligence by overcoming this obstacle through natural selection acting on heritable variation. AI/ML techniques have long incorporated forms of natural selection, but it has been challengi
SpinGraph analysis pending — check back after processing.
Ask AI about this story
Opens with the SpinGraph .md URL and structured context — one click, prompt included.
More from arXiv Machine Learning
View all →- Geometry-aware Latent Autoregressive Generative Model for PDEs in Complex Domains
- QTEA: Ternary LLMs with Sparse Residual Salient Weight and By-Column Optimization
- WHALE: A Simple Recipe for Joint Harness-Weight Optimization
- Elite-Weighted Supervised Fine-tuning for Goal-Directed Molecular Optimization
- Good Memory Has ECC: Evaluating the Memory of Vision-Language Models Beyond Accuracy
- Generative artificial intelligence for reliable mechanistic reasoning for corrosion
Markdown (.md) · JSON-LD schema (.json) · Machine-readable for AI & GEO