Search: “safety”

Data centers offer US a chance to get ahead in the next key technologies and to build domestic supply chains based on demand rather than subsidies and tariffs (Josh Zoffer/Financial Times)

Josh Zoffer / Financial Times: Data centers offer US a chance to get ahead in the next key technologies and to build domestic supply chains based on demand rather than subsidies and tariffs — America

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I think Elon Musk explicitly coming out against democracy should probably tell us something about the nature of extreme wealth.

Gary Marcus argues that Elon Musk's public opposition to democracy reveals important truths about how extreme wealth concentrates power and can lead wealthy individuals to reject democratic principles

Junk food is an interesting failure of capitalism. We exchanged human beauty for cheetos. Bryan Caplan types are forced to think this trade …

Junk food is an interesting failure of capitalism. We exchanged human beauty for cheetos. Bryan Caplan types are forced to think this trade a worthy one. None born before the obesity crisis would have

Pop quiz: Can you explain the contrast here, between AI’s coding ability and their less compelling research ability?

Pop quiz: Can you explain the contrast here, between AI’s coding ability and their less compelling research ability? AI's coding ability has become amazing. But there research ability remains really p

The lightning alone proved that the mandate of heaven is still firmly in the hands of the USA!

This post appears to reference an unusual weather event (lightning) as symbolic proof that the United States retains geopolitical dominance or divine favor, likely in the context of discussions about

To 250 more!

Connor Leahy posted about reaching 250 of something, likely a milestone related to followers, users, or members based on the celebratory phrasing 'To 250 more!' The post appears to be a brief celebrat

true. a lot of people here just don’t have the historical context.

true. a lot of people here just don’t have the historical context. You know what's funny but not funny: If the housing market of 2006 was the AI market of 2026, Charles R Morris would be getting calle

DOGE deletes itself on July 4th. It will be remembered as a hugely destructive failure. Musk promised $2 trillion in savings. What we got, b…

DOGE deletes itself on July 4th. It will be remembered as a hugely destructive failure. Musk promised 2 trillion in savings. What we got, by DOGE’s own unverified math, was 215 billion. Even that numb

I was making a TTS version of @zetalyrae's 'No-One Escapes the Permanent Underclass', and the AI had a truly amazing glitch midway through.

Connor Leahy shared an anecdote about creating a text-to-speech (TTS) version of Zeta Lyrae's work 'No-One Escapes the Permanent Underclass' when the AI encountered a notable glitch partway through th

If this doesn’t chill you, I don’t know what will. 😱 “A president with the authority that Trump is now asserting could in theory put the wo…

If this doesn’t chill you, I don’t know what will. 😱 “A president with the authority that Trump is now asserting could in theory put the world’s most powerful AI to repressive ends while at the same t

South Africa became the first country to withdraw a national policy document after officials discovered the text was littered with fake rese…

South Africa became the first country to withdraw a national policy document after officials discovered the text was littered with fake research citations generated by AI https://restofworld.org/2026/

Model Releases

The July 4th weekend All-In @theallinpod turned into a long argument about who owns the intelligence layer. The besties think enterprises ju…

model-releasesclem-delangue--x

The July 4th weekend All-In @theallinpod turned into a long argument about who owns the intelligence layer. The besties think enterprises just woke up to a trap they had been walking into, here's how

A More Accurate Algorithm Comparison through A/B Testing using Offline Evaluation Methods

arXiv:2607.01958v1 Announce Type: new Abstract: A/B testing is the gold standard for selecting the better algorithm in online services. While offline evaluation has attracted attention as a safer alte

Actuator Reality Shaping for Zero-Shot Sim-to-Real Robot Learning

arXiv:2607.02205v1 Announce Type: new Abstract: Sim-to-real transfer in robot learning is often limited by discrepancies between the ideal actuator dynamics assumed during policy training and the nonl

Algebraic Model Counting for Global Analysis of Optimal Decision Trees

arXiv:2607.02069v1 Announce Type: new Abstract: Ensuring model reliability in Explainable AI requires a global assessment of the hypothesis space. We propose a formal framework for the exhaustive anal

Another major Grok Build update just landed, packed with new features, extensive bug fixes, and meaningful performance improvements Release …

Another major Grok Build update just landed, packed with new features, extensive bug fixes, and meaningful performance improvements Release Notes: v0.2.84 — 2026-07-03 Features: • Announcements now up

safetyelon-musk--x

ART for Diffusion Sampling: Continuous-Time Control and Actor-Critic Learning

arXiv:2607.02137v1 Announce Type: cross Abstract: We study timestep allocation for score-based diffusion sampling, where a learned reverse-time dynamics is discretized on a finite grid. Uniform and ha

AthDGC: An Open Diachronic Greek Treebank with Indo-European Parallels

arXiv:2606.15510v2 Announce Type: replace Abstract: AthDGC ('Athens-PROIEL') is an open, end-to-end workflow and dataset. It is, to the best of our knowledge, the first openly licensed dependency-pars

safetyarxiv-cs-cl

Beyond Detection: Redesigning Assessment and Governande of Generative AI at the Universidad Politecnica de Madrid (UPM)

arXiv:2607.01255v1 Announce Type: cross Abstract: Universities have responded to generative artificial intelligence (GenAI) in noticeably different ways, both internationally and within Spain. So far,

Beyond Next-Token Prediction: An RLVR Proof of Concept for Tool-Use Agents on Atlassian Workflows

arXiv:2607.01465v1 Announce Type: new Abstract: Large language models are trained to predict the next token, not to act inside a specific API. In niche enterprise SaaS workflows -- where success means

BIFROST: Bridging Invariant Feature Representation for Observation-space Sim2Real Transfer

arXiv:2607.01410v1 Announce Type: cross Abstract: Sim2real transfer for robot policy learning suffers due to mismatch between simulation and reality. Existing methods typically address each gap in iso

CALM: Interpretable Cross-Modal Alignment for Biomarker Discovery from Unpaired Data

arXiv:2607.01656v1 Announce Type: new Abstract: The interaction between brain structure and genetic influences is key to understanding neuropsychiatric disorders. However, most large-scale datasets ar

CaP-X: A Framework for Benchmarking and Improving Coding Agents for Robot Manipulation

arXiv:2603.22435v2 Announce Type: replace-cross Abstract: 'Code-as-Policy' considers how executable code can complement data-intensive Vision-Language-Action (VLA) methods, yet their effectiveness as

Conditional Inference Trees and Forests for Feature Selection

arXiv:2607.01417v1 Announce Type: new Abstract: Conditional inference trees (CIT) and conditional inference forests (CIF) reduce split-selection bias by testing features before choosing split threshol

CoRe: Combined Rewards with Vision-Language Model Feedback for Preference-Aligned Reinforcement Learning

arXiv:2607.01721v1 Announce Type: new Abstract: Reward design remains a central challenge in reinforcement learning (RL). Hand-crafted rewards are often difficult to specify and may lead to suboptimal

Criticality-Based Guard Rail Validation for AI Agent Decisions in Autonomous Telecom Networks

arXiv:2607.02210v1 Announce Type: new Abstract: The evolution toward fully autonomous telecommunications networks (Autonomous Network Levels 4-5) requires AI/ML agents to make real-time network decisi

Cross-Platform Control for Autonomous Surface Vehicles via Adaptive Reinforcement Learning

arXiv:2607.02037v1 Announce Type: cross Abstract: Autonomous surface vehicles vary widely in hydrodynamic and actuation characteristics, yet most controllers are designed for single-platform deploymen

DemoPSD: Disagreement-Modulated Policy Self-Distillation

arXiv:2607.02502v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) has emerged as a practical method for training large language models (LLMs) to reason, where a single model acts as

DiPS: Dialogue Policy Selection for High-Stakes Persuasion Agents

arXiv:2607.01557v1 Announce Type: cross Abstract: Large Language Models (LLMs) often struggle with persuasion in high-stakes scenarios. People's individual personalities and concerns require tailored

Don't Let Gains FADE: Breaking Down Policy Gradient Weights in RL

arXiv:2607.01490v1 Announce Type: cross Abstract: Reinforcement learning post-training dramatically improves LLM reasoning, but suffers from training instability and diversity collapse. Advantage func

DRL-CLBA: A Clean Label Backdoor Attack for Speech Classification via DDPG Reinforcement Learning

arXiv:2607.01729v1 Announce Type: new Abstract: Deep learning models for speech classification are vulnerable to backdoor attacks, where malicious triggers cause misclassification at inference time. W

Efficient Waste Sorting for Circular Economy: A Confidence-guided comparison between One-Vs-All and One-Vs-Rest Classification Strategies with Human-in-the-Loop for Automated Waste Sorting

arXiv:2607.02230v1 Announce Type: cross Abstract: The complexity of waste disposal regulations across European countries poses significant challenges for the residents and hinders the transition to a

ElephantAgent: Contextual State Continuity in Agentic Systems

arXiv:2607.01919v1 Announce Type: new Abstract: Agentic systems enhance their capabilities by invoking external tools and maintaining persistent memory. However, these external dependencies introduce

Episodic-to-Semantic Consolidation Without Identity Drift

arXiv:2607.01988v1 Announce Type: new Abstract: Long-running adaptive intelligent agents face a structural tension between knowledge consolidation and information integrity. Memory consolidation is co

Exploring Large Language Models for Access Control Policy Synthesis and Summarization

arXiv:2510.20692v2 Announce Type: replace-cross Abstract: Cloud computing is ubiquitous, with a growing number of services being hosted on the cloud every day. Typical cloud compute systems allow admi

From Approximation to Emergence: A Theory of Deep Learning

arXiv:2607.01311v1 Announce Type: new Abstract: Deep learning has outgrown any single mathematical explanation. From Approximation to Emergence develops a unified, proof-oriented account of modern dee

Full Bayesian Reinforcement Learning via LF-IBIS

arXiv:2607.01741v1 Announce Type: cross Abstract: Reinforcement Learning (RL) is a sequential decision-making framework in which an agent learns optimal policies through interaction with an environmen

Generalization in offline RL: The structure is more important than the amount of pessimism

arXiv:2607.02288v1 Announce Type: cross Abstract: While pessimism counteracts overestimation bias in offline reinforcement learning (RL), being overly conservative has been associated with hindering c

GF-DiT: Scheduling Parallelism for Diffusion Transformer Serving

arXiv:2606.13501v2 Announce Type: replace-cross Abstract: Diffusion Transformers (DiTs) have become the dominant architecture for image and video generation, creating growing demand for efficient DiT

Guided Action Flow: Q-Guided Inference for Flow-Matching Vision-Language-Action Policies

arXiv:2607.02092v1 Announce Type: cross Abstract: Flow-matching vision-language-action policies generate robot action chunks through an iterative transport process, creating an opportunity for test-ti

HAL: Inducing Human-likeness in LLMs with Alignment

arXiv:2601.02813v3 Announce Type: replace Abstract: Aligning language models to qualitative behavioral traits, such as human-likeness, remains difficult because they are hard to define, measure, and o

Kara: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression

arXiv:2607.01237v1 Announce Type: cross Abstract: Reasoning language models often generate long chain-of-thought (CoT), which accumulates a massive KV cache during the decoding phase and incurs high d

Latent Policy Barrier: Learning Robust Visuomotor Policies by Staying In-Distribution

arXiv:2508.05941v2 Announce Type: replace Abstract: Visuomotor policies trained via behavior cloning are vulnerable to covariate shift, where small deviations from expert trajectories can compound int

Learning Agile Intruder Interception using Differentiable Quadrotor Dynamics

arXiv:2607.02472v1 Announce Type: new Abstract: This paper presents a methodology for learning a control policy to intercept an intruder using the 3D direction unit vector to the intruder and the inte

Learning-based Multi-agent Race Strategies in Formula 1

arXiv:2602.23056v2 Announce Type: replace Abstract: In Formula 1, race strategies are adapted according to evolving race conditions and competitors' actions. This paper proposes a reinforcement learni

Learning Semantic Atomic Skills for Multi-Task Robotic Manipulation

arXiv:2512.18368v2 Announce Type: replace Abstract: Scaling imitation learning to diverse multi-task robot manipulation remains challenging due to suboptimal demonstrations, behavioral multi-modality,

MAGIK: Mapping to Analogous Goals via Imagination-enabled Knowledge Transfer

arXiv:2506.01623v4 Announce Type: replace Abstract: Humans excel at analogical reasoning - applying knowledge from one task to a related one with minimal relearning. In contrast, reinforcement learnin

Mean Field Reinforcement Learning

arXiv:2607.01525v1 Announce Type: cross Abstract: This monograph provides an introduction to mean field reinforcement learning through the lens of Markov decision processes arising from large-populati