Towards a quantum computer that learns from its errors
Machine Intelligence
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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.
Researchers improve weather forecasts looking two to six weeks out
A new machine-learning approach broke records for weather forecasting for an important time frame in emergency planning.
Google DeepMind and Singapore Government announce new AI tool to protect citizens against scams
Learn how Google DeepMind and GovTech Singapore uses lightweight on-device Gemma models to intercept conversational scams in private chats with zero cloud data egress.
How artificial neural networks build their own learning machinery
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.
Related papers
Time for AI (Ethics) Maturity Model Is Now
It is argued that AI software is still software and needs to be approached from the software development perspective, and whether the focus should be on AI ethics or the quality of an AI system, called a maturity model for the development of AI systems is discussed.
ChargeNet: E(3) Equivariant Graph Attention Network for Atomic Charge Prediction
This work introduces an advanced equivariant graph attention neural network specifically engineered to model long-range atomic electrostatic interactions with high precision, and improves the model's accuracy, generalization, and robustness in complex scenarios.
Blockchain-Enabled Artificial Intelligence and AI Agents for Secure Data Sharing and Cybersecurity Applications
This paper presents a meta-synthesis that draws together four constituent studies covering adversarial machine learning, AI-powered anomaly detection in cloud environments, automated vulnerability patching by multi-agent large language model (LLM) pipelines, and the broader landscape of securing AI systems across their...
Is the Algorithm an Epistemic Agent? A Critical Analysis of Computational Epistemology and the Emergence of Algorithmic Agency
The question of whether algorithms can be considered epistemic agents represents one of the most profound challenges at the intersection of philosophy of mind, epistemology, and artificial intelligence. This paper develops a novel theoretical framework for understanding algorithmic epistemic agency through the introduc...