Harness, Scaffold, and the AI Agent Terms Worth Getting Right
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Putting Earth AI to work: Geospatial agents for our planet's biggest challenges
Earth AI
GPT-Lab
· gpt-lab.eu
Oct 14, 2026
Building trustworthy AI: The role of AI harnesses, intent contracts and evals
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post Building trustworthy AI: The role of AI harnesses, intent contracts and evals appeared first on GPT-Lab.
Run fast, private agents on-device with LFM2.5-24B-A2B
GPT-Lab
· gpt-lab.eu
Oct 12, 2026
AI Has Grown Up. Have We?
AI is moving beyond impressive demos. After World Summit AI 2026 in Amsterdam, GPT-Lab's Muhammad Waseem reflects on what organizations need to make AI agents reliable, responsible and genuinely useful in everyday work. The post AI Has Grown Up. Have We? appeared first on GPT-Lab.
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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...
Policy Drift in Learning AI Agents: A Dynamical Systems Perspective on Security Degradation
Policy drift takes shape through a nonlinear differential equation - framed within the policy state space - with support from Lyapunov stability concepts alongside bifurcation methods alongside bifurcation methods, and the Intent Drift Rate appears: a concrete number per dialogue turn built as the time-based change in...