Anthropic Dials Back AI Safety Commitments - WSJ
Anthropic Dials Back AI Safety Commitments WSJ
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FORMULA: FORmation MPC with neUral barrier Learning for safety Assurance
arXiv:2604.04409v1 Announce Type: cross Abstract: Multi-robot systems (MRS) are essential for large-scale applications such as disaster response, material transport, and warehouse logistics, yet ensuring robust, safety-aware formation control in cluttered and dynamic environments remains a major challenge. Existing model predictive control (MPC) approaches suffer from limitations in scalability and provable safety, while control barrier functions (CBFs), though principled for safety enforcement, are difficult to handcraft for large-scale nonlinear systems. This paper presents FORMULA, a safe distributed, learning-enhanced predictive control framework that integrates MPC with Control Lyapunov Functions (CLFs) for stability and neural network-based CBFs for decentralized safety, eliminating
Governance-Constrained Agentic AI: Blockchain-Enforced Human Oversight for Safety-Critical Wildfire Monitoring
arXiv:2604.04265v1 Announce Type: cross Abstract: The AI-based sensing and autonomous monitoring have become the main components of wildfire early detection, but current systems do not provide adaptive inter-agent coordination, structurally defined human control, and cryptographically verifiable responsibility. Purely autonomous alert dissemination in the context of safety critical disasters poses threats of false alarming, governance failure and lack of trust in the system. This paper provides a blockchain-based governance-conscious agentic AI architecture of trusted wildfire early warning. The monitoring of wildfires is modeled as a constrained partially observable Markov decision process (POMDP) that accounts for the detection latency, false alarms reduction and resource consumption wit
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“Alignment” and “Safety”, part one: What is “AI Safety”?
If you’re already familiar with the history of the field, you might wanna skip this one… I like to imagine future historians trying to follow the discourse around AI during the time I’ve been in the field… “Wait, so the AI ethics people think that the AI safety people are the same as the accelerationists and hate them? And the accelerationists think the safety people are the same as the ethicists and hate them ? And the AI safety people want to be friends with both of them!?” In a recent conversation with a researcher, they told me: “Yeah, I work on that, but I just do alignment, not that crazy safety stuff”. Five years ago, they might’ve said the opposite! When I wrote my PhD thesis in 2021, I said: > Until recently, “AI safety” was the most commonly used term for technical work on reduci
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