Harness, Scaffold, and the AI Agent Terms Worth Getting Right
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GPT-Lab
· gpt-lab.eu
Oct 30, 2026
Black October? The Week AI Changed the Cybersecurity Conversation
Critical flaws, compromised release channels and agentic AI threats landed within days of each other in mid-October 2026. Why “Black October” may say more about how well we now find weaknesses than about the attacks themselves. The post Black October? The Week AI Changed the Cybersecurity Conversation appeared first on GPT-Lab.
Microsoft Research Focus – Edition #97
Host Sowbhagya Suresh shares some of the latest news and cutting-edge research from across Microsoft—from understanding the challenges facing coding agents to uncovering how people use AI at work and improving extended-range weather forecasting. The post Microsoft Research Focus – Edition #97 appeared first on Microsoft Research.
Turning Database Grading into RL Rewards: Post-Training Agents with ThinkingBox
A Blog post by Microsoft on Hugging Face
Flint-interactive: A language for creating interactive data visualizations
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
Related papers
mRNABERT: advancing mRNA sequence design with a universal language model and comprehensive dataset
The authors develop mRNABERT, a foundational AI model that designs entire mRNA sequences and demonstrates superior performance across comprehensive benchmarks, which signifies a substantial leap forward in mRNA research and therapeutic development.
Computational and AI-Driven Ecosystem for Structure-Based Covalent Drug Discovery.
This Account describes a computational and AI-driven ecosystem for structure-based covalent drug discovery and dives into a suite of cutting-edge, AI-driven computational methods, exploring the potential of deep learning in tasks such as molecular docking, covalent binding site prediction, and lead optimization.
Facilitating structure-based drug discovery with an artificial intelligence-driven virtual screening platform.
The Comprehensive VS Platform with AI Engine (CVSP-AIE) for drug discovery from compound libraries integrates three AI models: KarmaDock, a fast docking model that directly updates atomic coordinates; CarsiDock, an accurate docking model that predicts protein-ligand distances and reconstructs binding poses; and RTMScor...
The Synthetic Consensus Trap: Correlated AI Errors, Verification Overload, and the Mathematics of Institutional Epistemic Cascades
Institutions are beginning to use multiple large language models, AI agents, automated reviewers, and human overseers as if agreement among them were independent corroboration. That assumption can fail. This paper develops the Synthetic Consensus Cascade (SCC) framework, a multidisciplinary mathematical model linking c...