A MarkTechPost tutorial walks through NVIDIA's new Structured Data Models library, which exposes several pretrained foundation models for tables through a single PyTorch interface. It bundles TabICLv2 and KumoTabular for single tables and KumoRelational for full relational databases, all predicting through in-context learning rather than training.
MIT researchers have developed work that helps AI models represent crystalline materials in three dimensions. The approach is meant to let models reason about the properties of those materials.
Google Research released Harness2 under the Apache 2.0 license, a framework that rewrites an agent's harness at test time. A single refinement step raised GLM-5's score on WorkBuddy-Bench by 11.5 points without touching the model's weights.
Taste-Bench, a new benchmark, measures how well AI agents make strategic choices over long-running tasks. Even the top performer, GPT-5.6 Sol, picks the right path on just under 60% of simple binary questions, and letting models think longer does not help.
Microsoft has proposed an AI method that corrects the errors of existing weather models for forecasts several weeks out, without heavy computing requirements. Results are encouraging, though the approach still cannot predict the weather with certainty.
Clubic examines how chatbot suggestions might steer users away from some ideas even as they help find others. As these tools enter daily life, the diversity of how people think, create and see the world could be affected.