John J Boren | Data + ML + Visualization
Four laws for engineers using AI to learn faster without mistaking leverage for understanding. The piece ties expertise research, cloud blast radius, metacognitive blind spots, and AI tutoring into one operating principle: fundamentals first, acceleration second.
Equivariant GNNs are critical for physics-informed molecular modeling but are too expensive for large-scale deployment — naive quantization breaks symmetry guarantees, and this is the first principled solution to that tension.
City Detect's $13M Series A reflects a strong bet on the intersection of computer vision/AI and municipal infrastructure...
Data collection is the real bottleneck for scaling imitation learning, and this bridges the gap between convenient handheld collection and targeted DA...
Diffusion Language Models are a compelling alternative to autoregressive generation, but scattered token acceptance destroys memory locality — this pa...
Four laws for engineers using AI to learn faster without mistaking leverage for understanding.
Today's top 5 papers from arXiv covering AI, machine learning, NLP, and computer vision
When AI content engines and defense contractors become the same company, authenticity isn't a philosophy problem — it's a procurement one.