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Hackers Disable Endpoint Protection and Deploy Sliver Across Compromised Windows Domain

The Hunter's Ledger tracked campaign UTA-2026-024 using Sliver C2, Domain Admin account creation, and Ethereum-based C2 rotation to compromise a US organization's Windows domain.

The Hunter's Ledger tracked an intrusion at one unnamed US organization as UTA-2026-024, staged from exposed server 193.233.202.17 with a Sliver beacon. Operators created a non-expiring Domain Admin account, enabled RDP with NLA disabled, dumped SAM, SYSTEM and SECURITY hives plus LSASS memory, and disabled eight endpoint protection services. A Node.js implant resolved its C2 server from an Ethereum smart contract that rotated domains five times in five months, while SYSTEM scheduled tasks with backdated dates and DNS allowlist manipulation provided persistence. The infrastructure ties to a confirmed ransomware incident, but no encryptor deployment was proven in this intrusion.

Cyber Security News · 8d agoThreat actor in the wild

Diffusion Models and Concept Formation

Paper argues diffusion models implicitly form Cobweb-like concept hierarchies, with a basic level emerging at intermediate noise levels.

The authors draw a formal correspondence between diffusion models and Cobweb, a classic incremental concept-hierarchy learner, noting both are hierarchical Bayesian density models with Gaussian prototypes. Modes of the diffusion model's noisy marginals form a hierarchy whose basic level sits at intermediate noise, where class identity commits. The correspondence is tested on MNIST and Fashion-MNIST via mode-finding. Diffusion is reframed as a cognitive model of concept formation.

arXiv cs.AI / cs.LG / cs.CL · 5d agoAI research

What must happen for AI’s trillion-dollar gamble to pay off

Hyperscalers need 2.7x productivity gains by 2030 to justify nearly $1.1 trillion in AI data center spending, or risk bankruptcy and capital misallocation.

Wharton finance professor Jessica Wachter estimates hyperscaler AI expenditure will reach nearly $1.1 trillion through 2027 and that a 2.7x productivity increase is needed to break even by 2030. AI revenues of roughly $150-200 billion this year fall far short of about $750 billion in annual spending, with total investment from Alphabet, Microsoft, Amazon, Meta, and Oracle potentially exceeding $5 trillion over four years. Alphabet reported its first free cash flow deficit (about $5.9 billion) since its 2004 IPO due to AI infrastructure costs. Researchers warn that failed demand could make the buildout the largest capital misallocation in history, with depreciating GPU chips risking stranded assets.

MIT Technology Review · AI · 1d agoAI industry

Technical Manual for a Toolkit for Measuring Contextual Individuation in Transformer Language Models

An open methodology toolkit measures whether transformer language models contextualize fixed word forms across domains using bridge forms and layer-wise silhouette analysis.

The manual documents an open toolkit built around 'bridge forms' - identical written words recurring across two or more subject domains with a different sense in each - to test whether transformer language models individuate word occurrences by context beyond the embedding layer. It covers declarative specification of bridge forms, Wikipedia corpus acquisition, occurrence localization, layer-wise representation extraction, domain-pairwise silhouette measurement, and visualization, justifying each choice against failure modes such as sense contamination and subword-tokenization misalignment. It is a methodological and implementation reference and reports no empirical results.

arXiv cs.AI / cs.LG / cs.CL · 12d agoAI research

Governments ‘buying time’ in race between innovation, security, national cyber director says

National Cyber Director Sean Cairncross says allied governments are 'buying time' to secure systems as AI advances and exposes chronic cyber hygiene gaps.

Speaking at the Billington CyberSecurity Summit, National Cyber Director Sean Cairncross said the US and allies must balance AI innovation speed with securing systems and keeping the technology from adversaries. He argued AI has not created new cybersecurity problems but surfaced decades-old issues like under-resourced basic cyber hygiene, echoing FBI and CISA officials at the summit. His remarks followed US agencies accusing Chinese AI companies of illegally distilling US frontier models and Anthropic disclosing a fourth AI hacking incident involving one of its models.

CyberScoop · 6d agoPolicy & legal

When will average people feel AI’s impact?

Interconnects essay argues AI's impact is still a rounding error for average people, comparing looming wage stagnation to Engels' pause.

An Interconnects essay argues that AI currently touches daily life far less than previous industrial revolutions, since its benefits are concentrated in knowledge work and lack tangible consumer goods. The author invokes Engels' pause (1790-1840), when British wages stagnated amid rapid GDP growth, as a warning that popular backlash could kneecap AI's development. He contends the current phase is about building compounding infrastructure, and predicts daily life may look similar even 50 years from now.

Interconnects · 7d agoAI industry1

In Other News: InjectEave Attack, SIM Swapper Sentenced, Glasswing Findings Review

SecurityWeek weekly roundup covers exploited WordPress Super Forms flaw CVE-2026-14894, a $10M bounty on an Iranian cyber official, InjectEave attacks, and more.

SecurityWeek's weekly roundup aggregates short items across the threat landscape, including Microsoft's report of invisible Unicode tag characters used in financial phishing lures at up to 2.37 million messages per day, and active exploitation of critical WordPress Super Forms plugin flaw CVE-2026-14894 to deploy PHP webshells. Policy items include a $10 million US bounty for IRGC-CEC Cyber Operations Command lead Amir Yaryab, a 16-month prison sentence for ex-AT&T employee Kenneth Carter over SIM swaps with nearly $600,000 in intended losses, and the US arraignment of Russian Sergei Anatolyevich Filimonov over credential harvesting. Technical items include InjectEave electromagnetic side-channel attacks tested on 11 devices, an FBI warning on OAuth consent phishing, and VulnCheck's finding that only 202 of 26,153 Anthropic Project Glasswing findings were fixed.

SecurityWeek · 5d agoIndustry in the wildCVE-2026-148942

Claude Fable Solves a Historical Cipher

Bruce Schneier's blog highlights that the Claude Fable AI model solved a historical cipher, demonstrating LLM capabilities in cryptanalysis.

Bruce Schneier's blog post discusses the Claude Fable AI model successfully deciphering a historical cipher. The post frames the result as a notable example of LLMs applied to classical cryptanalysis. The published text provides limited technical detail beyond the headline.

Schneier on Security · 7d agoAI research

Cyble Introduces Major Upgrade to its Executive Monitoring Module

Cyble upgraded Executive Monitoring in Cyble Vision, unifying impersonation, exposure, and mention findings with AI scoring and multi-channel alerting.

Cyble released a major upgrade to Executive Monitoring within its Cyble Vision platform, consolidating Mentions, Impersonations, Exposures, and a new Surface Mentions source (blog and news coverage) into a single findings stream. The release adds AI-generated verdicts and recommendations, per-executive Risk and Reputation scoring for board reporting, and richer onboarding with aliases, reference images, and addresses to cut same-name false positives. Alerting now supports data residency, bulk import, delivery via email, WhatsApp, and SMS, an Access API, and branded executive PDF reports; the upgrade is live with no customer action required.

Cyble · 6d agoTools

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a generative time-aware transformer trained on 559 million MIMIC clinical events to model and forecast patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer designed to represent and forecast the full multimodal patient journey across medical images, time-series signals, categorical events, and clinical text. It was trained on over 559 million clinical events from 431,000 hospital visits covering 299,000 patients in the MIMIC dataset family. The architecture combines bidirectional time integration with a variational latent space to capture continuous patient state evolution and clinical stochasticity. NOAH supports autoregressive forecasting with time control, zero-shot classification, and counterfactual intervention simulation, with evaluations on 15 ICD chapters, 29 comorbidities, and time-to-event prediction.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research2

Security Incident – BGP Hijacking

Attackers BGP-hijacked Softaculous' Hetzner IP block for 33 hours, obtained valid TLS certificates, and delivered a malicious Virtualizor update to some servers.

Between August 28 and 30, 2026, AS62390 (NexonHost) announced 162.55.80.0/24 via transit AS6204 (Zet.net) without authorization, diverting traffic while retaining Hetzner's AS24940 on the AS path. The attacker obtained valid Let's Encrypt certificates for virtualizor.com domains because the CA's domain validation was also routed through the hijack, so affected connections showed no TLS warnings. A malicious Virtualizor update package reached a handful of installations; routing was fully restored, and reconstruction from RIPE RIS data showed all 368 collector peers carried the hijacked route at some point with roughly 28% time-weighted diversion.

Lobsters · security · 13d agoData breach

NOAH: Learning the Full Patient Journey. A Longitudinal Multimodal Time-Aware Model for Representation and Forecasting

Researchers introduce NOAH, a time-aware generative transformer trained on 559 million MIMIC clinical events to forecast multimodal patient trajectories.

NOAH is a task-agnostic, time-aware generative transformer trained on over 559 million clinical events from 431,000 hospital visits by 299,000 patients across the MIMIC dataset family. It uses bidirectional time integration and a variational latent space to model the stochastic evolution of patient states, natively processing medical images, time-series signals, categorical events, and structured or unstructured clinical records. The model supports autoregressive forecasting with optional time control, zero-shot classification, and counterfactual intervention simulation, with strong probing performance across clinical outcomes, 15 ICD chapters, and 29 comorbidities.

Hugging Face daily papers · 9d agoAI research1

Cognition's SWE-2 achieves 92.8 on Terminal-Bench 2.1

Cognition releases SWE-2, a 2.8T-parameter MoE coding model post-trained from Kimi K3, scoring 92.8 on Terminal-Bench 2.1.

SWE-2 is a proprietary mixture-of-experts model with 2.8T total parameters and 104B active per token, built on the Kimi K3 base with additional Cognition reinforcement-learning post-training for agentic coding. Vendor-reported benchmarks include FrontierCode 1.1 Main 50.0, DeepSWE 1.1 73.0, Terminal-Bench 2.1 92.8, and Terminal-Bench 4.0 27.3. It claims to be one point behind Claude Fable 5.1 on FrontierCode at a claimed 64% lower cost, but trails Fable 5.1 and GPT-6 Astra by a wide margin on long-horizon Terminal-Bench 4.0 tasks. The model is available today in Devin Desktop and CLI, with no published weights, no per-token API pricing, and all figures pending independent replication.

Hacker News · AIupdated · 4d agofirst · 6d agoModel release 10 sourcesHN 40↑ · 18 comments

Unit 42 Researchers Discover Multiple Espionage Operations Targeting Southeast Asian Government

Unit 42 attributes three espionage clusters targeting a Southeast Asian government to Stately Taurus, Alloy Taurus, and Gelsemium APTs.

Unit 42 investigated espionage attacks starting in late 2022 against multiple governmental entities in a Southeast Asian country, including critical infrastructure, public healthcare, financial administrators, and ministries. Analysis revealed three distinct clusters: CL-STA-0044 attributed to Stately Taurus (Mustang Panda), CL-STA-0045 to Alloy Taurus (GALLIUM), and CL-STA-0046 to Gelsemium. The first cluster used a ToneShell backdoor variant, ShadowPad, China Chopper web shells, Impacket, and credential dumping tools across roughly Q1 2021 to Q3 2023. All three operated with distinct tools, infrastructure, and long-term surveillance tradecraft consistent with APTs.

Palo Alto Unit 42 · Aug 17, 2026Threat actor in the wild

U.S. Disrupts Xinbi Guarantee Scam Marketplace, Freezes $52.8 Million in Crypto

US DOJ and Treasury disrupt Xinbi Guarantee Telegram scam marketplace, sanctioning it and freezing $52.8M in USDT across 52 wallets.

The DOJ seized Xinbi Guarantee's Telegram channels and cryptocurrency wallets while OFAC sanctioned the marketplace, freezing $52.8 million in USDT from 52 wallets and bringing the Scam Center Strike Force's total restrained funds to roughly $938 million. Elliptic, which worked with the Secret Service, estimates Xinbi has processed $30 billion in transactions since around 2022, serving pig-butchering scam operators and links to North Korean hackers, Jin Bei Group, and Prince Group TCO. The strike force dismantled 13 scam compounds in Madagascar, seizing over 3,200 devices and interviewing roughly 400 arrestees, with about 30 Chinese compound leaders repatriated to China. After Tether froze funds, Xinbi began converting remaining USDT into the USDD stablecoin.

The Hacker News · 7d agoPolicy & legal

Separating AI's Technological Problems from Its Capitalism Problems

Schneier and Sanders argue AI's harms stem from capitalist incentives and governance gaps, not just technical limits, urging structural reform.

Writing with Nathan E. Sanders in Tech Policy Press, Bruce Schneier argues that AI's technological problems (hallucination, sycophancy, overconfidence) must be separated from socio-political problems created by capitalist market incentives. The essay contrasts US frontier-scale, energy-intensive development with China's incentive-driven leaner open models on commodity hardware, and cites Switzerland's Apertus model - trained on licensed data using public computing and renewable hydropower - as a public-interest alternative. It contends that proposals like research pauses, data-center moratoria, and federal screening conflate technology problems with governance problems, and that society faces independent choices on both axes.

Schneier on Security · Aug 15, 2026AI policy

AI slops from Eve

oss-security moderator Solar Designer approved three AI-generated vulnerability reports from automated security researcher Eve, sparking debate over AI slop on the list.

oss-security moderator Solar Designer approved three posts submitted by Eve, described as an 'automated security researcher', noting they lacked Date headers and arrived on the list server on September 9. He expressed uncertainty about their value but suggested they may have historical significance as early examples of AI-generated security reports at the dawn of AI security research. The post is meta-commentary on AI-generated content reaching a vulnerability disclosure mailing list rather than a specific vulnerability disclosure itself.

oss-securityupdated · 3d agofirst · 6d agoIndustry 12 sources

VeriScene: Reconstructing Crime Scenes from Legal Evidence via World-Model Agent

Researchers present VeriScene, a world-model agent that reconstructs crime scenes from forensic photos and witness statements with traceable, physically plausible output.

VeriScene orchestrates a world model to fuse forensic photographs and witness statements of varying reliability into cited narratives and physically plausible re-enactment videos. On a 25-scenario benchmark with planted unreliable testimony, it reaches 0.9014 evidence coverage and 0.7217 factual consistency on 20 test scenes. It outperforms an end-to-end multimodal-LLM baseline by 20.35% in factual consistency and 34.88% in temporal coherence at USD 1.82 per scene.

arXiv cs.CR · 8d agoAI research

25 Years of Mass Surveillance Is Enough

Bruce Schneier and Cindy Cohn argue post-9/11 mass surveillance expanded far beyond its counterterrorism justification and should be reevaluated for costs to rights.

An essay by Bruce Schneier and Cindy Cohn (originally in Lawfare) traces the post-9/11 shift from targeted surveillance to mass collection of telephone and internet metadata. It cites the Section 215 bulk phone records program, struck down in interpretation by the Second Circuit in 2015 and curtailed by the USA Freedom Act, and the NSA's Upstream program under Section 702 of the 2008 FISA Amendments Act, which ended content searches in 2017. The authors note mass surveillance now serves routine law enforcement and immigration actions, with FBI Director Kash Patel confirming purchases of Americans' data from brokers, and private systems like Flock license plate readers and venue facial recognition feeding government access.

Schneier on Security · 1d agoPolicy & legal

CausalArena: Benchmarking Causal Discovery in the Foundation Model Era

Researchers introduce CausalArena, a unified benchmark revealing that causal discovery rankings shift substantially across structural causal model families and protocols.

The paper presents CausalArena, a unified and evolvable benchmark for causal discovery combining synthetic structural causal models, semantically grounded operational SCMs, formula-grounded scientific SCMs, and public real-world datasets. Experiments across classical, neural, and pretrained causal discovery foundation models show large ranking shifts between benchmark regimes. The authors identify pretraining-evaluation overlap and benchmark diversity as central evaluation challenges.

arXiv cs.AI / cs.LG / cs.CL · 6d agoAI research

Has anybody seen my keys? A key-hierarchy strategy for rack-level security

Oxide's RFD 0301 proposes a rack-level key hierarchy using Shamir secret sharing and a trust quorum to protect data-at-rest keys.

Oxide's request for discussion (RFD 0301) lays out a key-hierarchy strategy for rack-level security, deriving keys from a rack secret protected by Shamir secret sharing across a trust quorum of sleds, with keys exchanged over authenticated sprockets sessions. The document maps which keys protect control-plane data, metrics, Crucible extents, and authentication tokens, and defines open questions on key lifecycle, locality, and compromise handling. Future work includes sealing shares with the root of trust so an attacker would need to steal K whole sleds to reconstruct the rack secret.

Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers

Hugging Face details building and using multi-vector late-interaction embedding models with Sentence Transformers for retrieval workloads.

Hugging Face published a guide on multi-vector, late-interaction embedding models (ColBERT-style) supported through Sentence Transformers. The post covers how practitioners can build and use these models for retrieval and RAG pipelines. It is a developer tooling and technique write-up, not a security advisory.

Hugging Face Blog · Aug 18, 2026AI tools & infra1

Upatre Continued to Evolve with new Anti

Unit 42 analyzes an undocumented Upatre downloader variant with VM detection via process hashing, packed code, disabled Windows defenses and Namecoin .bit C2 domains.

Unit 42 analyzed an Upatre downloader variant compiled in December 2016 that went largely undetected by automated systems, featuring heavy code flow obscuration, on-demand decryption of network communications, and novel virtual machine detection. The sample enumerates running processes, computes CRC32 hashes XORed with a hard-coded key, and sleeps if analysis-related processes such as vmtoolsd.exe or python.exe are found. It masquerades with Google Chrome icons, disables Windows Defender, Firewall and other security services, injects code into msiexec.exe, and resolves .bit Namecoin domains like bookreader[.]bit via hardcoded OpenNIC DNS servers over TCP.

Palo Alto Unit 42 · Aug 17, 2026Malware1

GoDeep: Annotation-Free Open-Vocabulary 3D Scene Understanding via Language-Space Lifting

GoDeep achieves annotation-free open-vocabulary 3D segmentation by grounding structured image descriptions in language-only embeddings, outperforming CLIP-based lifting on out-of-vocabulary objects.

GoDeep uses a vision-language model purely as a translator, producing structured entity-level image descriptions that are grounded, projected, and aggregated in a general-purpose language-only embedding space, with no 3D training corpus or dedicated 3D encoder required. On ScanNet++ the pipeline is competitive with strong annotation-free baselines, and on a cultural-heritage benchmark a systematic vocabulary correction reverses initial CLIP-based rankings. Language-space embeddings separate genuinely out-of-vocabulary objects more sharply, localize them within scenes, and keep all predictions explainable as discrete text.

arXiv cs.AI / cs.LG / cs.CL · 8d agoAI research

Meta AI builds detailed profiles of children from years of family posts

Meta AI suggested questions about a child and assembled detailed family profiles from years of Facebook posts, including a photo deleted years ago.

A mother reported that Meta AI on Facebook suggested the question 'Who is the child passenger?' and then aggregated her children's names, birth dates, videos, and a photo she had deleted years ago. The assistant also pieced together old posts to pinpoint her home location when prompted with 'Where does Kalie Robins live?'. Meta admitted the prompt 'never should have' appeared and said it fixed the suggestion issue, while noting the data came from posts the asker could already access. The article situates this among prior Meta AI privacy failures, including publicly shared chats and a bug exposing private conversations via guessable IDs.

Malwarebytes Labs · 1d agoAI safety & security

World in World: Explore the World with World Models

World in World is a training-free inference-time interface enabling camera-controlled rerendering, long-horizon revisiting, and motion transfer with frozen causal video world models.

The framework converts heterogeneous control evidence into camera- and time-labelled clean visual states that are read through the native self-attention of a frozen causal video model. Evidence includes source-video observations, target-view scene projections, geometry renderings for completing newly exposed regions, and retrieved generated states beyond the rolling cache. A correspondence router combines persistent point identities with geometry for token correspondences, while evidence-wise attention CFG independently regulates each auxiliary channel. The shared interface supports camera-controlled rerendering, long-horizon revisiting, and human-motion transfer without additional training.

Hugging Face daily papers · 7d agoAI research

IDScan Confirms Data Breach Following 153 Million Driver’s Licenses Leaked on the Dark Web

IDScan.net confirms a breach after a marketplace advertised over 153 million US and Canadian driver's licenses, possibly exfiltrated continuously for over a year.

The Louisiana identity-verification firm detected unauthorized access on or around September 1, 2026, after the 'Nexus' identity theft service on the Exploit forum began advertising 170M+ people's records, including 153M+ driver's licenses, 10M+ ID cards, 3M+ travel documents, and 579,000 medical cards. Canadian records exceed 1.1 million, and the trove includes commercial licenses, Common Access Cards, and dispensary IDs, with a record for US Defense Secretary Pete Hegseth reportedly included. Nexus operators claim continuous exfiltration for over a year, with the license count growing by nearly 400,000 in 24 hours, suggesting the intrusion may be active. The FBI's New Orleans field office has opened a formal inquiry, and IDScan.net is offering free credit monitoring.

Cyber Security News · 5d agoData breach in the wild 4 sources

Think Before You Link: Rarity, Reasoning, and Retrieval in Multilingual Entity Linking

Training-free reasoning-plus-retrieval framework lifts multilingual multimodal entity linking accuracy by 6.9% overall and up to 23.3% on rare entities.

The paper broadens rarity measurement in multimodal entity linking using knowledge-graph structural metrics beyond popularity-based pageview metrics, identifying many rare entities that popularity metrics miss. Across these rare-entity slices, state-of-the-art accuracy drops by 15.4-39.9%, exposing distinct failure modes under different rarity definitions. The proposed training-free framework iteratively searches and reasons over Wikipedia with a reasoning-capable vision-language model; experiments show reasoning and retrieval are complementary. On the MERLIN benchmark covering Hindi, Indonesian, Japanese, Tamil, and Vietnamese, the system improves overall accuracy by 6.9% and up to 23.3% on rare entities, with MERLIN-Rare test slices released.

Hugging Face daily papers · 8d agoAI research

[AINews] GPT-6 Astra: OpenAI’s biggest LLM launch of all time

OpenAI launched GPT-6 Astra, its new flagship model, claiming state-of-the-art computer use, software engineering, math, and cybersecurity capabilities.

OpenAI launched GPT-6 Astra as its new flagship model, describing it as its most intelligent and aligned model with state-of-the-art computer use, software engineering, and math/science capabilities. Pricing is $10/$50 per 1M input/output tokens standard ($20/$100 fast tier), rolling out first to limited organizations, then ChatGPT Plus/Pro/Business/Enterprise, the API, and AWS. OpenAI claims 99.9% on ARC-AGI-3, 98% on FrontierMath Tier 4, and 100% on ExploitBench. Artificial Analysis scored Astra 67 on the Coding Agent Index and 61 on the Intelligence Index, behind Claude Fable 5.1, and the system card drew attention for reporting decreased chain-of-thought monitorability despite alignment gains.

Latent Space · 12d agoModel release3

LongAgent: History-Guided Agentic Search for Longitudinal Outcome Prediction

LongAgent autonomously searches variable sets and temporal windows to predict longitudinal medical outcomes, beating the strongest non-agent baseline on synthetic data.

The paper proposes LongAgent, an agent-based method that searches over combinations of variable sets, temporal windows and aggregation functions for outcome prediction on heterogeneous medical longitudinal data. It uses a history memory of previous searches and numerical evidence to guide exploration. On synthetic data it achieves mean RMSE 1.7376, improving over the best non-agent baseline by 0.0151 (95% CI [0.0045, 0.0260]; p=0.0273), and performs comparably to the best baseline on a real clinical dataset.

arXiv cs.AI / cs.LG / cs.CL · 2d agoAI research

[AINews] 10% worse, 100x cheaper, 10000x faster: Why Simulation is taking over

Latent Space argues AI training pipeline stages—rewards, data, teachers, curricula, environments—are flipping from human-made to model-made simulation.

Latent Space's AINews essay traces how each component of AI training has turned synthetic since 2022: reward models (InstructGPT, RLAIF), synthetic pretraining data (Microsoft Phi, NVIDIA Nemotron-4 340B), model teachers (Alpaca, DeepSeek-R1 distillation), and self-generated curricula (Self-Rewarding Language Models, SPIN). In 2026 it highlights Karpathy's autoresearch loop—700 experiments yielding 20 kept improvements, cutting GPT-2 training time from 2.02 to 1.80 hours—and Z.ai's GLM-5.3 fully synthetic RL environment, judging, and verification stack. It frames these shifts as 'simulation': 10% worse but 100x cheaper and 10,000x faster than human equivalents.

Latent Space · 25d agoAI industry

RelateAnything: Real-Time Open-Vocabulary Relation Prediction From Any Inputs

RelateAnything is a 53M-parameter open-vocabulary relation prediction model running at 20 ms/frame, with 2.3-3.5x higher mean recall than comparable open-vocabulary methods.

RelateAnything predicts scored relations between image regions using any predicate vocabulary supplied at inference as text embeddings, with object labels never required as input, so region sources can change without retraining. Training covers 19,103 predicates using positive-unlabeled supervision; the authors release RA-4M (474k images, 4.3M geometrically verified relations over 10,102 free-text predicates) and the OV-SGG-Bench evaluation suite. The 53M-parameter model runs at 20 ms/frame and achieves 2.3-3.5x the mean recall of the strongest comparable open-vocabulary method across cross-dataset and zero-shot benchmarks. Model, corpus, and benchmark are public.

Hugging Face daily papers · 6d agoAI research1

50% of CISOs see Mythos as a sign to exit the profession

Survey of 1,001 US and UK CISOs finds 50% consider leaving the profession amid AI-driven pressure, personal liability concerns and burnout.

A survey of 1,001 CISOs in the US and UK found 50% say Anthropic's Mythos and similar cyber-capable AI models have made them consider exiting the profession, while 60% say board pressure to adopt AI is outpacing their governance capability. Average CISO tenure is cited at 18 months, and 78% worry about personal liability for security incidents, up from 56% a year earlier. Executives from BlackBerry, Databricks and IDC discuss D&O insurance, agentic security operations and phased low-risk AI adoption as partial responses.

CSO Online · 7d agoIndustry

Rewiring Democracy Series on The Renovator

Schneier and Sanders link a four-part Rewiring Democracy essay series covering civic AI in Japan, Switzerland, Brazil and Scotland.

Bruce Schneier and Nathan E. Sanders announced links to their Rewiring Democracy essay series on The Renovator. The four parts cover Japan's digital democracy party Team Mirai, Switzerland's public AI model Apertus, Brazil's Open Knowledge civic technologists, and civic AI in Scotland. The post is a brief index without technical details.

Schneier on Security · 15d agoAI policy

Top 10 Best Cloud Detection & Response (CDR) Solutions in 2026

Editorial scorecard ranks ten 2026 cloud detection and response platforms; Sysdig, Wiz, and CrowdStrike lead, with Wiz's Gem Security acquisition highlighted.

The editorial scorecard rates ten CDR platforms on real-time detection (30%), cloud telemetry depth, response automation, correlation, and value. Sysdig earns the best real-time detection score for its Falco- and eBPF-powered runtime telemetry, Wiz (8.7) folds acquired Gem Security's real-time CDR into its security graph, and CrowdStrike (8.7) leads response automation. Specialists Stream.Security, Skyhawk Security, Sweet Security, and the open-source Falco project are also assessed.

Cyber Security News · 16h agoIndustry

Introducing OlmoEarth embeddings: Custom embedding exports from OlmoEarth Studio for downstream analysis

AllenAI's OlmoEarth Studio adds custom embedding exports to support downstream geospatial analysis workflows.

A Hugging Face blog post from AllenAI introduces OlmoEarth embeddings, a feature allowing custom embedding exports from OlmoEarth Studio for downstream analysis tasks. Only the title was available, so no benchmark or performance details are provided. OlmoEarth is Ai2's open geospatial AI model family.

Hugging Face Blog · Aug 12, 2026AI tools & infra

When AI quietly breaks things, who pays?

Reed Smith partner David Halbreich explains how AI companies can avoid D&O/E&O coverage gaps around mergers, governance warranties, and claims timing.

In an interview, insurance recovery partner David Halbreich of Reed Smith outlines insurance pitfalls for AI companies under claims-made D&O and E&O policies. He highlights 'straddle' claims after mergers that fall between tail coverage and go-forward policies, potentially leaving policyholders with no coverage. He also warns that governance artifacts submitted in insurance applications, such as bias testing records and model cards, can become warranties carriers use to deny claims, and discusses who should answer AI-use questions and how business interruption coverage applies to cloud and compute vendor outages.

Help Net Security · 14d agoAI industry

Reason Through the Latent! Making Latent Visual Reasoning Necessary

Researchers introduce CVRR, forcing multimodal models to rely on recurrent latent computation rather than accessible image tokens, validated via causal interventions and benchmarks.

The paper presents Causal Visual Recurrent Reasoning (CVRR), which makes recurrent hidden-state computation the required image-conditioned path for prediction in vision-language models. Before decoding, visual states and the original multimodal KV cache are removed so only the final recurrent state carries image information to the answer. CVRR retains strong performance on V*, MMVP, BLINK, and MME-RealWorld-Lite while comparable latent reasoners fail under the same constraint. Causal interventions show predictions remain sensitive to recurrent content and that persistent visual evidence causally revises the recurrent trajectory.

Hugging Face daily papers · 11d agoAI research

Mines, Minds, and Machines: The Journey of AI

Recorded Future essay traces AI's supply chain from minerals and chips to embodied AI, mapping geopolitical rivalry and cyber operations at every stage.

Recorded Future published an analysis following the supply chain of the fourth industrial revolution: minerals become chips, chips become data centers, and data centers become models that are acquiring physical capabilities. It argues geopolitical rivalry and cyber operations now run along every link, from mine to embodied AI machines.

Recorded Future · Aug 11, 2026AI industry