Verifying Rust cryptography in SymCrypt, from standards to code
Cryptographic code supports vital protections in modern computing systems. Learn how a new method helps verify code as developers write it while preserving speed and adaptability as it gets implemented and evolves. The post Verifying Rust cryptography in SymCrypt, from standards to code appeared first on Microsoft Research.
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Proof-based general-purpose computing with Magnetar
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
MIT students gain a humanist lens on technical innovation in Tulsa, Oklahoma
The PKG Center for Social Impact expands Code.Tulsa experiential learning program.
GPT-Lab
· gpt-lab.eu
Sep 3, 2026
Adaptive AI Agents in Construction Workflows
Adaptive AI agents can help make BIM data more machine-readable by navigating IFC models, interpreting inconsistent information, and mapping it to defined standards. In this blog, Alok Rawat shares findings from a real-world pilot in construction workflows. The post Adaptive AI Agents in Construction Workflows appeared first on GPT-Lab.
How Hugging Face Inference Endpoints, Jobs, and Buckets Power Search on Papers with Code
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
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PepPCBench is a Comprehensive Benchmarking Framework for Protein-Peptide Complex Structure Prediction
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The Q‐GEM comprises a GNN embedded with the molecular electronic and complete 3D geometrical structural information as well as several well‐designed multiscale SSL tasks, achieving superior absolute molecular conformation prediction and conformational discrimination.