Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.

MIT News · Artificial Intelligence · news.mit.edu Jul 15, 2026

3 Questions: Neural transparency and the future of AI design

Assistant Professor Pat Pataranutaporn describes a new interface that lets everyday users glimpse inside an AI's neural network before their chatbot ever says a word.

Microsoft Research Blog · microsoft.com Jul 13, 2026

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.

MIT News · Artificial Intelligence · news.mit.edu Jul 6, 2026

graph neural networks

Multi-scale junction temperature modeling and lifetime assessment of IGBT power modules using graph neural networks

Knowledge graph visualization and anomaly detection from cyber threat intelligence dataset using graph neural networks based methods

FedGNN-SFCP: Federated graph neural networks for ship fuel consumption prediction with heterogeneous data fusion and missing data imputation

Graph neural network-accelerated multi-objective design optimization of fractal flow fields for anion exchange membrane electrolyzers

Secure and efficient sixth-generation spectrum allocation via holographic interpretable graph convolutional neural network and blockchain-enabled resource management

Fusing semantics and graph neural networks: A multi-dimensional survey and technological evolution

Physics-informed graph neural network surrogates for real-time transmission–distribution co-optimization

A physics aware graph neural network with similarity condition regularization for electromagnetic loss optimization in high power giant magnetostrictive transducers

A structure-aware and explainable approach to website fingerprinting using graph neural networks

A fault diagnosis method for rotating machinery based on spline-modulated wavelet and energy topology-guided graph convolution neural network

Remote sensing optical image matching through neighborhood-aware global propagation in graph neural networks

Bus passenger flow prediction with a dynamic graph neural network and bidirectional gated recurrent unit

From tech blogs

How artificial neural networks build their own learning machinery

3 Questions: Neural transparency and the future of AI design

Verifying Rust cryptography in SymCrypt, from standards to code

Toward a future that preserves benefits of neurotechnology for all

NeuralGCM harnesses AI to better simulate long-range global precipitation

Neural Super Sampling is here!