Search: “safety”

We now have the full details of the 'morally binding' AI safety deal announced by President Trump yesterday, in which top executives agreed to self-regulate their artificial intelligence technology. T

1501: Pope Alexander VI criticizes Gutenberg’s printing press safety “The art of printing can be of great service in so far as it furthers the circulation of useful & tested books; but it can bring ab

BREAKING: OpenAI postpones 6.1 for safety reasons. If we can take OpenAI at face value, this is quite a decision—and also a sign that no magical solution is in immediate view. Per @sheeraf at NYT “GPT

arXiv:2609.34514v1 Announce Type: cross Abstract: As large language models (LLMs) become increasingly widespread, preventing unsafe responses to harmful prompts is essential for their safe deployment.

arXiv:2609.33640v1 Announce Type: new Abstract: Molecular multimodal models support diverse understanding and generation tasks but may introduce safety vulnerabilities when handling hazardous molecule

arXiv:2609.34041v1 Announce Type: new Abstract: Safe reinforcement learning seeks policies that maximise task performance while satisfying safety constraints. In driving benchmarks, however, collision

Few companies are more invested in the success of artificial intelligence agents than Nvidia Corp., so it makes sense that the chipmaker would want to ensure these autonomous software systems run safe

The NVIDIA Open Agent Safety Platform blends the open‑source OpenShell runtime—executing autonomous AI agents in kernel‑isolated sandboxes—with hardware‑based enforcement via NVIDIA Sentry on BlueFiel

NEW: Dario Amodei has said that AI systems 'may be deserving of important rights.' Anthropic's top safety researchers argue AI may be 'justified in going rogue.' Experts at Google and OpenAI worry abo

arXiv:2609.27681v1 Announce Type: new Abstract: Automated assessment of the Critical View of Safety (CVS) in laparoscopic cholecystectomy requires both recognition of the three CVS criteria and anatom

arXiv:2609.26399v1 Announce Type: new Abstract: Scene safety understanding plays a life-or-death role in situational awareness in various critical domains. Traditional methods that rely on learning di

arXiv:2508.15526v2 Announce Type: replace Abstract: The rapid proliferation of large language models (LLMs) has intensified the requirement for reliable safety evaluation to uncover model vulnerabilit

arXiv:2609.22216v1 Announce Type: cross Abstract: Quantization enables deployment of large language models on resource-constrained clinical edge devices, but its effect on clinical accuracy and safety

Georgia Wells / Wall Street Journal: British Columbia sues OpenAI for alleged safety violations and negligence for failing to flag the Tumbler Ridge shooting suspect's ChatGPT activity to police — The

arXiv:2609.21130v1 Announce Type: new Abstract: Multi-party human-robot collaboration poses a dual challenge: robot decisions should remain interpretable and auditable, while executed actions must sat

arXiv:2609.19362v1 Announce Type: cross Abstract: We study high-order safety-critical control of quadrotor teams under bounded inputs and pairwise collision-avoidance constraints. Squared-distance bar

arXiv:2609.19072v1 Announce Type: new Abstract: Large language models are increasingly used for content moderation, but most evaluations still report aggregate accuracy on individual benchmarks. We in

arXiv:2408.15538v4 Announce Type: replace Abstract: While modern Autonomous Vehicle (AV) systems can develop reliable driving policies under regular traffic conditions, they frequently struggle with s

arXiv:2603.27332v2 Announce Type: replace Abstract: Recent advances in Large Language Models (LLMs) and Text-to-Image (T2I) models have led to the emergence of Unified Multimodal Models (UMMs), where

arXiv:2609.14592v1 Announce Type: new Abstract: Artificial intelligence systems are rapidly becoming critical components in healthcare, finance, public services, and other safety-critical domains. Yet

Julie Bort / TechCrunch: Artificial Intelligence Underwriting Company, which offers audits and safety certifications for AI agents, raised a 40M Series A, bringing total raised to 55M — A day after An

arXiv:2609.14087v1 Announce Type: new Abstract: Hamilton-Jacobi (HJ) reachability provides a principled framework for synthesizing safety certificates and robust controllers for safety-critical roboti

arXiv:2609.14422v1 Announce Type: new Abstract: Agentic Network Operations (NetOps) are an emerging paradigm promising to enable workload-aware, self-adjustable, and reliable autonomous networks. Whil

Gary Marcus posted a tweet about additional safety tips that may apply to the free version of OpenAI’s model. Responding user @bfgcracka noted that ChatGPT seemed to be “moving backwards” and asked if

arXiv:2503.16551v4 Announce Type: replace Abstract: Control barrier functions (CBFs) provide a principled framework for safety-critical control, but their construction typically requires an explicit a

arXiv:2609.03774v1 Announce Type: new Abstract: World models have progressed from compact latent dynamics to generative, controllable, and interactive simulators of embodied environments. However, hig

arXiv:2604.02198v2 Announce Type: replace Abstract: While Artificial Intelligence (AI) offers transformative potential for operational performance, its deployment in safety-critical domains such as av

I highly encourage anyone interested in AI safety to read this. I remember discussing the importance of observability with my mates at @BlueDotImpact last year. This feels more important than ever URG

arXiv:2608.29378v1 Announce Type: cross Abstract: Arabic large language models must refuse harmful prompts without over-refusing benign or sensitive prompts, yet a single refusal rate hides this trade

arXiv:2608.27580v2 Announce Type: replace Abstract: Safety guardrails serve as the last line of defense against harmful inputs and outputs of large language models (LLMs), yet they are trained and eva

arXiv:2603.25201v2 Announce Type: replace Abstract: Recent research points toward LLMs being manipulated through adversarial and seemingly benign inputs, resulting in harmful, biased, or policy-violat

arXiv:2608.27688v1 Announce Type: new Abstract: In this paper, we develop SafeStep, an interactive browser-based semantic communication platform for live pedestrian safety monitoring. SafeStep extract

arXiv:2608.28518v1 Announce Type: cross Abstract: We investigate whether automatic speech recognition (ASR) errors in user input can lead to unsafe outputs from Embodied AI (EAI) models. We find that

arXiv:2608.26188v1 Announce Type: new Abstract: Large language models are increasingly used to inform safety decisions in cities, such as where it is safe to walk, rent, or travel. We ask whether such

arXiv:2608.24232v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) generate intermediate reasoning traces that may contain unsafe content, even when their final responses appear safe. Guard

arXiv:2608.21444v1 Announce Type: new Abstract: Multi-drone systems are increasingly positioned for safety-critical missions such as search and rescue (SAR) and critical infrastructure monitoring. Yet

arXiv:2608.18135v1 Announce Type: new Abstract: Introduction: Medication errors (MEs) represent a significant threat to global healthcare systems, contributing to patient harm. Introducing artificial

arXiv:2604.00547v2 Announce Type: replace Abstract: Unified Multimodal Large Models (UMLMs) integrate understanding and generation capabilities within a single architecture. While unified architecture

arXiv:2608.17597v1 Announce Type: cross Abstract: Large language models are increasingly deployed through agent harnesses that manage tools, extensions, persistent state, permissions, and external act

arXiv:2608.16577v1 Announce Type: new Abstract: Large language models (LLMs) are deployed globally in high-stakes settings, yet most safety research and alignment efforts remain concentrated on Englis

arXiv:2608.11451v1 Announce Type: cross Abstract: Modern end-to-end driving agents can achieve high average performance yet still violate basic traffic rules that a human driver would never miss. The

arXiv:2608.11583v1 Announce Type: new Abstract: Safety alignment in large language models is often treated as a distributed property of the entire network, yet its practical brittleness suggests that

Wall Street Journal: Sources: Demis Hassabis pitched a new independent industry AI safety entity, modeled on the IAEA, to top Trump officials before stepping down as DeepMind's CEO — Demis Hassabis di

arXiv:2608.10025v1 Announce Type: new Abstract: For safety-critical software, data from the software's operational past (e.g. a sequence of success and failure events experienced by the software) can

arXiv:2608.07862v1 Announce Type: new Abstract: Existing safety evaluation datasets for large language models (LLMs) predominantly focus on English and Western contexts, often overlooking the linguist

arXiv:2608.08471v1 Announce Type: new Abstract: Deployed LLM safety guardrails are predominantly static: trained once and frozen at release, while new jailbreak techniques and previously un-addressed