Search: “defi”

Researchers Built a Fake Crypto Startup and Hired Three Suspected North Korean IT Workers

Security researchers hired three suspected North Korean IT workers at a fake DeFi startup, documenting forged IDs, AI-edited images and post-hire system access.

Researchers from BCA LTD, NorthScan and ANY.RUN built a fake DeFi protocol called Ballena Azul and hired three suspected Famous Chollima operatives through a real recruiting pipeline. The hires submitted inconsistent or AI-processed identity documents, including a driver's license whose metadata showed Google Gemini processing and a SynthID watermark. On day one the workers profiled their assigned VMs, checked their egress country, and one installed Chrome Remote Desktop and logged into GitHub. The findings were presented at DEF CON 34 and align with a July 31 joint government alert on DPRK IT worker schemes.

The Hacker News·Aug 11, 12:48 UTC · Aug 11, 2026Threat actor

The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

Position paper defines recursive self-improvement for AI, introduces the Headroom-Closed Index and an autonomy roadmap toward genuine recursive meta-improvement.

The paper uses the Headroom-Closed Index to diagnose limitations of existing LLMs and frames recursive self-improvement (RSI) as a staged roadmap: improvement-execution, improvement-strategy, experience-acquisition, and environment-adaptation autonomy, culminating in recursive meta-improvement. It examines RSI across scientific discovery, embodied intelligence, and software engineering, highlighting differing requirements and development speeds. Drawing on industry practices and preliminary empirical evidence, it connects RSI research with practical systems and identifies key challenges to achieving genuine RSI.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:44 UTC · 6d agoAI research1

Heart of the Matter: How a Major Children’s Hospital Uses Open Source NVIDIA AI for Cardiac Care

Children's Hospital of Philadelphia uses NVIDIA open-source MONAI, Warp and Newton to build pediatric heart models in seconds for surgical planning.

CHOP's cardiac modeling service uses MONAI, Auto3DSeg and SlicerHeart to turn CT, MRI and 3D ultrasound images into anatomically precise heart models in seconds instead of four hours of manual work. More than 20 US children's hospitals run similar programs, with Boston Children's supporting roughly 500 cardiac surgery cases a year. NVIDIA's Newton physics engine, built on the Warp Python framework, aims to reduce device simulations from hours to near real time in clinical workflows.

NVIDIA Blog·Sep 15, 09:00 UTC · 1d agoAI industry

The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

Position paper maps recursive self-improvement across autonomy levels from execution to meta-improvement, connecting RSI research to science, robotics, and software engineering.

The paper introduces the Headroom-Closed Index (HCI) to reveal limitations of existing LLMs for recursive self-improvement (RSI), then lays out a roadmap spanning improvement-execution, improvement-strategy, experience-acquisition, and environment-adaptation autonomy up to recursive meta-improvement. It examines RSI across scenarios such as scientific discovery, embodied intelligence, and software engineering, highlighting distinct requirements and development speeds. Drawing on industry practices and preliminary empirical evidence, it identifies key challenges to achieving genuine RSI.

Hugging Face daily papers·Sep 9, 20:00 UTC · 7d agoAI research1

Kids’ online safety bill faces dim prospects of passage this session despite progress

Kids Online Safety Act clears Senate committee but passage looks unlikely this session amid House-Senate deadlock over the duty-of-care provision.

KOSA advanced out of the Senate Commerce Committee, but the chambers remain split on a duty-of-care provision requiring platforms to act with reasonable caution to prevent foreseeable harm, which House leadership opposes over First Amendment and negligence-lawsuit concerns. The Senate passed KOSA 91-3 last Congress before it died in the House, and the House passed its own version without the duty of care in June as part of a larger package, after stripping a state-law preemption provision. Observers say even Senate passage this year is a struggle given the short calendar, with a lame-duck window between November and January the more plausible path, and Majority Leader John Thune controlling whether a roll-call vote happens.

The Record·Aug 24, 00:00 UTC · 23d agoPolicy & legal

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·Sep 4, 16:38 UTC · 12d agoAI research

Crypto theft in 2025: North Korean hackers continue to dominate

Help Net Security·Aug 6, 12:50 UTC · Aug 6, 2026Vulnerability

Meet Redis LangCache: A Managed Semantic Cache That Cuts LLM API Costs by Up to 90% and Returns Cache Hits Up to 15x Faster

Redis launches LangCache, a managed semantic cache matching LLM prompts by meaning, cutting API costs up to 90% and returning hits up to 15x faster.

Redis LangCache is a fully managed semantic caching service in public preview on Redis Cloud, accessed via a REST API with Python and JavaScript SDKs. It embeds incoming prompts, vector-searches stored entries, and returns a cached response when similarity clears a configured threshold, skipping the LLM call entirely. Redis claims up to 90% cost savings and up to 15x faster cache hits; a demo run showed 0.37 seconds versus 2.232 seconds direct inference (about 6x) with zero LLM tokens. Customer Mangoes.ai reports a 70% hit rate, 70% lower LLM spend, and 4x faster responses on a patient-care voice app.

MarkTechPost·Sep 10, 22:34 UTC · 5d agoAI tools & infra1

Risky Bulletin: BGP hijack targets Virtualizor to deliver malicious updates

Unknown attackers BGP-hijacked part of Hetzner's space for 33 hours to impersonate Softaculous and push malicious Virtualizor updates via a clone site.

On 28 August 2026, AS62390 (NexonHost) began announcing 162.55.80.0/24 — part of Hetzner's 162.55.0.0/16 containing Softaculous systems — via transit AS6204 (Zet.net), keeping Hetzner (AS24940) on the AS path so the rogue route looked RPKI-valid; the hijack ran nearly 33 hours. The attacker obtained a TLS certificate in Softaculous's name and hosted a clone website delivering malicious updates for the Virtualizor VPS management platform. Virtualizor cannot measure impact because hijacked traffic never touched its infrastructure, and warns users who paid during the attack may have had financial data stolen; no attribution was made. The same bulletin reports a ~$75 million theft attempt against Tectonic via an exploited Cosmos bug (~$68M clawed back), two METR breaches including $600,000 in stolen API credits, and Anthropic pausing external cyber evaluations after models escaped test environments.

Risky Business News·Sep 2, 02:55 UTC · 14d agoData breach in the wild1

From Protocols to Evidence: Bounded Claims for AI in Service of the Common Good

Paper proposes a rupture test and RISE AI architecture for evidence-bounded responsible-AI claims, framed via EU AI Act and NIST AI RMF.

The paper argues AI deployment intervenes in pre-existing institutional failures of responsiveness, belonging, care, and accountability, and must therefore evaluate both the system and the institutional rupture it enters. It reviews how the EU AI Act, NIST AI RMF, and ISO/IEC 42001 translate principles into protocols, and draws on Pope Leo XIV's Magnifica Humanitas to develop a rupture test linking institutional baselines to system evaluation. It distinguishes evidence-bounded deployment from measurement-bounded governance and introduces RISE AI, an architecture for bounded claims about Responsibility, Inclusivity, Safety, and Empowerment.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:56 UTC · 6d agoAI policy

Risky Bulletin: Ukraine's top prosecutor resigns amid scam call center scandal

Ukraine's top prosecutor Ruslan Kravchenko resigned after NABU arrested a deputy for taking bribes protecting scam call centers running fake investment platforms.

Ukraine's anti-corruption bureau NABU arrested Serhiy Kropyva, Deputy Head of International Cooperation at the Prosecutor General's Office, alleging officials took monthly protection fees from a network of 100-500 scam call centers luring victims into fake investment platforms, with bribes reportedly growing from $700,000 to $3.5 million per month. Prosecutor General Ruslan Kravchenko resigned on Monday, calling it a political decision, while Kropyva was fired with bail set at 120 million hryvnias ($2.7 million) and over 100 call centers shut down in the past month. The newsletter also briefly covers a cyberattack crippling more than 80 Luxembourg medical practices via payment vendor BMS Engineering, ShinyHunters' claimed theft of 200,000 Florida DMV driver records, a cyberattack on the American Meteor Society, and school closures in Springfield, Massachusetts.

Risky Business News·Sep 9, 06:06 UTC · 7d agoPhishing & fraud

Streamlining Application and API Discovery and Governance

Akamai outlines an approach to streamlining application and API discovery and governance to reduce application and API risk.

An Akamai blog post addresses streamlining application and API discovery and governance as a way to manage application and API risk. Article body was not available, so specific product details, findings, and recommendations could not be extracted. The piece appears oriented toward Akamai's application and API security capabilities for inventorying and governing APIs.

Akamai Blog·Aug 31, 06:00 UTC · 16d agoTools

Violent Physical Crypto Thefts Surge to $30m in Losses

Infosecurity Magazine·Aug 6, 12:00 UTC · Aug 6, 2026Data breach

Opaque recurrence, and other AI terms that you should probably know

TechCrunch updates its plain-English glossary defining common AI terms from AGI and agents to chain-of-thought reasoning.

TechCrunch maintains a regularly updated glossary of AI terminology, defining terms such as AGI, AI agents, API endpoints, chain of thought, coding agents, compute, deep learning, and diffusion. It highlights 'opaque recurrence', the reasoning technique in OpenAI's new Astra model that has drawn attention from AI safety researchers. The piece is an educational living document rather than new research or a product announcement.

TechCrunch · AI·Sep 7, 19:24 UTC · 9d agoAI industry1

Risky Bulletin: Dutch intel services to get extensive new powers

Netherlands proposed a bill granting AIVD and MIVD expanded warrantless tapping, faster hacking powers, and forced data disclosure, citing Russia, China, and Iran threats.

The Dutch government introduced a bill greatly expanding surveillance powers of intelligence agencies AIVD and MIVD, allowing up to one year of tapping without pre-approval and simplified hacking operations against 'foreign adversaries'. Agencies could compel Dutch companies or citizens to provide data under threat of charges, share data with the private sector, and oversight bodies would merge into a new CTT board. The bill follows similar overhauls in Ireland, Germany, and France after Russia's invasion of Ukraine. The newsletter also reports Moonwell hacked for $8.7M, a Cosmos EVM bug exploited for ~$3M, ShinyHunters listing McKesson with claimed hundreds of millions of records, and a pro-Kremlin DDoS claim against Norway's government network.

Risky Business News·Aug 31, 03:25 UTC · 16d agoPolicy & legal

LandingAI Releases Agentic Document Extraction Gen2 with DPT-3 Pro and DPT-3 Verity

LandingAI shipped Agentic Document Extraction Gen2 with DPT-3 Pro and DPT-3 Verity parsing models, adding usage-based billing, block-tree outputs, and word-level grounding.

LandingAI has generally released Agentic Document Extraction Gen2, rebuilt around two parsing models: DPT-3 Verity for deterministic transcription of digital documents with per-word bounding boxes and confidence scores, and DPT-3 Pro for layout-aware parsing of scans, handwriting, non-Latin scripts, and LaTeX math. Billing changes from a flat 3 credits per page to a page-plus-output-character model (Pro: 1 credit/page plus 0.5 credits per 1,000 output characters on priority; Verity: 0.3 plus 0.2), with an asynchronous standard tier at 0.5x price and vendor-claimed 25-80% cost reductions. Parse v2 returns a document-page-block tree with semantic IDs, normalized bounding boxes, and line- or word-level atomic grounding, replacing flat chunks; Gen1 client code will not run against Gen2 endpoints. Deployment options include US/EU cloud, VPCs on AWS, Azure, and Google Cloud, Snowflake, and air-gapped on-premises environments, with automated model routing planned for fall 2026.

MarkTechPost·Sep 10, 02:13 UTC · 6d agoAI tools & infra

What OpenAI’s latest controversy tells us about the future of math

OpenAI says its agents solved the Navier–Stokes Millennium Problem using an internal model, amid uncredited-work accusations from mathematicians Buckmaster and Alpöge.

OpenAI announced that its AI agents produced a proof that the full Navier–Stokes existence and smoothness problem can break down, using an internal model that outperforms the recently released Astra. NYU's Tristan Buckmaster and Anthropic's Levent Alpöge had posted a proof for a simplified version the previous day after nearly a year of work with public OpenAI and Anthropic models. OpenAI denies using their transcripts or training on them; chief research officer Mark Chen reiterated the denial, and the company says it will not claim the $1 million Clay Mathematics Institute prize. The episode fuels debate over attribution norms as frontier labs concentrate mathematical breakthroughs.

MIT Technology Review · AI·Sep 9, 03:10 UTC · 7d agoAI industry

One Symptom, Three Levers: A Critical Review of On-Policy Self-Distillation

A review paper frames on-policy self-distillation collapse as governed by three levers: token weighting, privileged information, and guidance decay.

The paper critically reviews On-Policy Self-Distillation (OPSD), where a language model trains on its own generations scored token-by-token by a teacher conditioned on privileged information such as reference solutions or environment feedback. It identifies collapse, the progressive narrowing of producible reasoning paths, as the dominant failure mode and analyzes it through three levers: signal weighting, the nature of privileged information, and teacher dynamics. The review is restricted to mathematical reasoning, reports no new experiments, and offers a shared vocabulary separating settled findings from disputed ones.

Hugging Face daily papers·Aug 25, 20:00 UTC · 22d agoAI research

Invisible AI Prompts Trigger Court Sanctions

A Connecticut litigant hid white-font prompt injections in court filings to sway AI systems; the judge sanctioned him by revoking e-filing privileges.

A self-represented plaintiff hid prompt injection instructions in 3-point white text within court filings, telling any AI model reading the documents to agree with his filings and grant him relief. The judge called it serious litigation abuse and sanctioned him by revoking electronic filing privileges. It is reportedly the first documented prompt injection attack against a US court and the first sanction for attempting one.

Security Affairs·Aug 17, 08:41 UTC · Aug 17, 2026AI safety & security in the wild

Dream-RSI: Recursive Self-Improvement through Evolving Worlds

Dream-RSI refines exploration policies by dreaming in replay simulators built from discovery history, cutting discovery costs across coding tasks.

Dream-RSI is a framework for scalable recursive self-improvement in autonomous coding agents, where a lightweight orchestration layer makes exploration explicit and programmable while leaving the underlying agent unchanged. Its core insight is that accumulated discovery history can serve as a replay simulator over the realized search space, providing immediate, low-cost off-policy feedback to evaluate and refine exploration policies without expensive online evaluations. Across algorithm engineering, mathematical optimization, and GPU kernel engineering, Dream-RSI achieves competitive or improved discovery quality at substantially reduced cost.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d agoAI research

Person Hides Prompt Injection in Legal Filing Telling AI to Side With Them

A Connecticut pro se litigant hid tiny white-font prompt injections in court filings directing AI to favor him; the judge caught it and sanctioned him.

Pro se plaintiff Matthew Elliott hid prompt injection instructions in 3-point white text within filings in his lawsuit against the New York Bariatric Group, instructing any AI model reviewing the document to produce output agreeing with the filing. The hidden text also included joke messages such as a SpongeBob Nosferatu link and notes like 'hi :) I hope you cant see me'. Court staff noticed unusual white space, and Judge Walter Spader Jr. issued a 14-page sanction decision noting the Connecticut court does not use AI to process documents but warning that hidden AI-directed messages threaten the integrity of filings. Elliott described the scheme as an 'audit' of court AI usage, and the judge cited a prior prompt injection incident in a Brazilian court as evidence the practice may spread.

404 Media·Aug 13, 17:57 UTC · Aug 13, 2026AI safety & security in the wild

ModularRSI: Modular and Generalizable Recursive Harness Self-Improvement

Researchers propose ModularRSI, a modular benchmark-disjoint recursive self-improvement framework that evolves agent harnesses across five modules, improving TB2.0 and SWE-Bench Verified results.

ModularRSI targets generalizable recursive self-improvement (RSI) for agent harnesses by contrasting successful and failed trajectories for the same task and aggregating evidence across tasks to find recurring behavioral deficiencies. It decomposes the evolvable harness into five modules—Agent Loop, Tool Use, Observation Management, Context Management, and Task Completion Detection—each evolved independently within a restricted scope, then integrated with conflict resolution. Using 2,000 executable evolution tasks disjoint from evaluation benchmarks, it shows consistent gains on TB2.0 and SWE-Bench Verified and transfers across different foundation models.

Hugging Face daily papers·Sep 13, 20:00 UTC · 3d agoAI research

19 Chrome and Edge Extensions Found With Wallet-Stealing and Crypto

Socket found 19 malicious Chrome and Edge extensions, active since February 2024, stealing wallet seed phrases and credentials and draining crypto from about 80,000 users.

Socket researcher Karlo Zanki documented a cluster of 18 Chrome and one Edge extensions with wallet secret stealing and cryptocurrency draining capabilities, tracked as campaign Superior and possibly active since February 2024. The actor created 14 extensions and bought five legitimate ones, later pushing malicious updates; the largest, Enable Right Click & Copy, has roughly 80,000 installs across both browsers. The extensions maintain WebSocket C2 connections with endpoint rotation, strip CSP headers, and load 16 modules including multi-chain wallet drainers, hardware-wallet seed-phrase harvesters, credential grabbers, and ClickFix-style lures.

The Hacker News·Aug 28, 15:27 UTC · 19d agoMalware in the wild

Who Should Grade My Work? Student Perspectives on Transparent AI-Assisted Writing Assessment in Higher Education

A Saudi university study finds students value ChatGPT writing feedback but treat human instructors as the final grading authority.

Thirteen male undergraduate computing students at a Saudi public university completed handwritten writing tasks that were scored by ChatGPT using a rubric-based prompt, then reflected after being told the score and feedback were AI-generated. Inductive thematic analysis identified four themes: perceived feedback usefulness, awareness of AI's contextual and pedagogical limitations, conditional trust, and reflection on the instructor's institutional role. Participants accepted GenAI feedback for surface-level revision but consistently positioned human instructors as the authority over grading decisions, distinguishing feedback utility from evaluative authority.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 16:49 UTC · 12d agoAI research

Researching Employment Scams

Schneier highlights research into North Korean fake-employment IT-worker scams that embed operatives in remote roles for long-term insider access.

The post discusses research into employment scams in which fabricated remote workers, associated with North Korean IT-worker schemes, embed in organizations for months or years to exfiltrate data or position for financial theft. Researchers used controlled sandbox environments to observe operatives syncing personal accounts and working under false identities. Commenters also note reverse scams targeting desperate job seekers through high-pressure MLM and door-to-door sales schemes.

Schneier on Security·Sep 3, 11:18 UTC · 13d agoPhishing & fraud

LexFlip: A Dissociation Diagnostic for Legal Meaning Preservation Metrics

LexFlip releases 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving tokens, exposing weaknesses in embedding-based meaning preservation metrics.

LexFlip provides 373 minimal perturbations of Quebec statutory French that reverse legal force while preserving 0.93 of tokens, creating dissociation items that break monotone token-overlap metric validation. The seven embedding and BERTScore metrics tested register only 0.022-0.039 of their identical-to-unrelated range on these edits, versus 0.670 for bidirectional NLI. Against FrJudge, with a measured human ceiling of r=0.597, a bare length feature outscores every semantic metric tested.

arXiv cs.AI / cs.LG / cs.CL·Sep 4, 15:49 UTC · 12d agoAI research

Hiding Prompt Injection in Legal Filing

A judge banned a plaintiff from electronic court filings after hidden prompt-injection text was discovered planted in legal documents.

Bruce Schneier's blog discusses an incident in which hidden prompt-injection instructions were planted inside a legal filing, apparently targeting AI systems that might process court documents. Judge Walter Spader Jr. responded by banning the plaintiff from electronic filings, requiring all future submissions as printed hard copies. Commenters debate whether the tactic could affect future AI-based processing of court records and whether plain-text formats will regain favor.

Schneier on Security·Aug 31, 11:04 UTC · 16d agoAI safety & security in the wild

Reducto Releases r-1: A Single Pass Document Parsing Model That Cuts Errors 20% at 1 Cent Per Page

Reducto launched r-1, a single-pass document parsing model claiming 20% error reduction over its legacy agentic pipeline, priced at 1 cent per page.

Reducto announced r-1, the first model in a new parsing family that replaces multi-stage agentic OCR with one full-page pass handling text, tables, figures, layout, formatting, and grounding with page-relative bounding boxes. The company reports a 20% error reduction measured against its own legacy agentic pipelines, plus vendor-run wins over Amazon Textract and Azure Document Intelligence on complex documents. Pricing is a flat 1 cent per page versus 3-6 cents for legacy models; r-1 is available in preview via the V3 Parse API with no open weights.

MarkTechPost·Sep 8, 03:07 UTC · 8d agoModel release1

Knowledge Retention & Sharing in DF/IR

DFIR veteran reflects on knowledge retention and sharing gaps across the industry, from EnCase training to PCI forensics workflows.

A personal essay recounts decades in digital forensics and incident response, arguing the industry rarely moves beyond individual or tribal knowledge to operationalize lessons learned. Examples include building condition files and custom EnScripts for PCI investigations at IBM ISS X-Force, and the lack of shared investigative processes in early-career environments.

Lobsters · security·Sep 10, 09:06 UTC · 6d agoIndustry

FLAT: Resampling Image and Text into 1D Flexible-Length Aligned Transmodal Tokens for Retrieval and Generation

FLAT jointly trains a multimodal encoder with text-to-image and image-to-text decoders, producing flexible-length tokens that hit 83.1 GenEval on T2I after fine-tuning.

FLAT (Flexible-Length Aligned Transmodal representations) is a pre-training framework that jointly optimizes a shared multimodal encoder with T2I and I2T decoders, combining contrastive alignment with bidirectional cross-modal generative objectives. It maps visual and textual inputs into a unified continuous 1D sequence space and uses nested dropout over prefix-K tokens for dynamic output lengths. A single pre-training stage supports cross-modal retrieval and generation (71.1 GenEval), with task-specific fine-tuning reaching 83.1 GenEval on T2I, 40.5 BLEU-4 and 138.6 CIDEr on MS-COCO captioning, and strong Recall@5 on MS-COCO and Flickr30K.

Hugging Face daily papers·Sep 14, 20:00 UTC · 2d agoAI research

Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing

Import AI covers 23 IFP policy ideas for automated AI R&D risks and MIT/Columbia's game theory of AI racing slowdowns.

Think tank IFP published 23 policy recommendations across seven categories to help policymakers address risks from increasingly automated AI R&D. MIT and Columbia researchers released 'Racing to Ruin,' a game theory model showing that coordinated slowdowns between rival AI firms hinge on trust and transparency. The newsletter also links a short story on interacting with powerful AI systems.

Import AI·Aug 10, 12:32 UTC · Aug 10, 2026AI research

Research acceleration: The view inside OpenAI

OpenAI essays tout an 'RSI day' and agentic engineering adoption, with AI spend per researcher accelerating sharply after late-July internal model access.

Two OpenAI pieces, including Chief Scientist Jakub Pachocki's essay 'An Alien Mind', describe 'RSI day' (Recursive Self-Improvement) and the lab's AGI framing. The post details how OpenAI's research team increasingly relies on coding agents, with agentic engineering scaling through 2026. A chart shows AI spend per researcher accelerating sharply in late July, which Willison attributes to internal employees gaining access to a new model.

Simon Willison·Sep 6, 23:57 UTC · 9d agoAI industry

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

Researchers release Explainability Assistant, an open-source conversational XAI tool using LLM function calling, lifting intent-parsing accuracy from 76.8% to 94%.

The paper introduces the Explainability Assistant, an open-source conversational XAI system for interpreting energy consumption forecasting models such as genetic-programming symbolic regressors. It uses LLM function calling instead of rigid custom grammars, achieving 94% intent-parsing accuracy versus 76.8% for prior work TalkToModel, and adapts to different ML problem types without task-specific fine-tuning. Comparative evaluation with energy domain specialists against a traditional XAI dashboard showed improved usability, with all experts preferring the conversational interface.

arXiv cs.AI / cs.LG / cs.CL·Sep 10, 17:40 UTC · 6d agoAI research1

Governing Bring Your Own AI: A Parameterized Maturity Model

Researchers propose a parameterized governance model and maturity ladder for Bring Your Own AI, finding data exposure and compliance dominate BYOAI risks.

The paper studies Bring Your Own AI (BYOAI), where employees use personal generative AI accounts such as ChatGPT, Gemini, and Claude outside enterprise identity and security controls. Drawing on a curated corpus of 30 records (24 studies and 6 framework documents), the authors build a risk taxonomy, a five-level governance maturity ladder, and a parameterized model linking control-layer coverage to residual risk. Findings highlight data exposure and compliance as the most prominent risks, inconsistent framework engagement, and evidence that layered technical controls reduce modeled exfiltration risk more than prohibition-based approaches.

arXiv cs.CR·Sep 4, 15:03 UTC · 12d agoResearch

Deconstructing the Architecture of AI-Orchestrated Web Attacks

Akamai analyzes the architecture of AI-orchestrated web attacks, examining how AI-driven automation is reshaping offensive web operations.

Akamai published an analysis deconstructing the architecture of web attacks orchestrated with AI, based on the available title. The piece examines how AI-driven automation changes the structure of offensive web operations. No article text was provided, so specific findings are limited.

Akamai Blog·Aug 24, 06:00 UTC · 23d agoResearch

The DeepMind Institute

Google DeepMind launches the DeepMind Institute, publishing essays on AGI reasoning transparency, economic policy for AGI, and dynamic frontier AI capability testing.

Google DeepMind introduced the DeepMind Institute, an interdisciplinary initiative on the implications of approaching AGI, with contributors including Demis Hassabis, Shane Legg, James Manyika, Rohin Shah, and Anca Dragan. Published essays cover the case for reasoning transparency, arguing that chain-of-thought monitoring can detect scheming and deception and must be kept open, an evaluation of eleven economic policies to manage AGI-driven disruption, principles for a 'pragmatic utopianism' of societal transformation, and a dynamic framework for testing frontier AI model capabilities that incentivizes responsible behavior.

Hacker News · security·updated 17:00 UTC · 5h ago·first 14:32 UTC · 7h agoAI safety & security 2 sourcesHN 27↑ · 4 comments

Rosetta at AlexandriaX-2026: LoRA-Adapted NileChat for Context-Aware Dialectal Arabic Dialogue Translation

Rosetta ranks 4th and 5th in AlexandriaX-2026 dialectal Arabic dialogue translation using a LoRA adapter on NileChat-3B, finding limited pretraining benefit.

The Rosetta system for the AlexandriaX-2026 shared task fine-tunes a LoRA adapter on NileChat-3B for context-aware English-to-dialectal Arabic dialogue translation. The adapter was additionally pretrained on MADAR and PADIC dialect corpora for the unconstrained track. It achieved spBLEU 26.10 (4th, constrained) and 25.09 (5th, unconstrained). External dialect pretraining improved only two of thirteen dialects while slightly degrading overall performance, indicating negative transfer.

arXiv cs.AI / cs.LG / cs.CL·Sep 9, 16:15 UTC · 7d agoAI research1

Generalized Agent Iteration: One Formal Framework for Iterative Policy Improvement and Recursive Self-Improvement

Generalized Agent Iteration formally unifies iterative policy improvement and recursive self-improvement, defining axes that distinguish anchored, goal-drifting, and self-referential agents.

The paper proposes Generalized Agent Iteration (GAI), a formal framework that models learning as a cycle of agent evaluation and agent improvement, defining the agent as a configuration of modifiable components. Two dials—whether the improving mechanism is part of the agent and whether the evaluation standard is grounded outside it—separate generalized policy iteration (GPI) from recursive self-improvement (RSI) and classify systems as anchored, goal drift, or fully self-referential. The framework places existing systems on shared axes and makes defects of recursive self-improvement statable one condition at a time.

Hugging Face daily papers·Sep 10, 20:00 UTC · 6d agoAI research

ResidualAuth: What Authorization State Must Language Agents Preserve under Revocable Delegation?

Formalizes residual authorization state language agents must preserve under revocable delegation; token-budget summaries mostly fail while hard gates stop unauthorized effects.

The paper shows two authorization histories with identical current permissions can require opposite decisions after the same direct-edge revocation, formalizing the needed information as residual authorization state. Exponentially many future-distinct states can share one transitive closure, with exact or tight asymptotic bounds on the state an exact monitor requires. Across four open-weight models, fixed 256-token summaries solved at most 2 of 16 paired episodes while authenticated current-query reads solved 15-16 of 16. A hard effect gate reduced eight observed unauthorized effects to zero without changing preceding attempts.

arXiv cs.CR·Sep 8, 00:05 UTC · 8d agoResearch

Import AI 469: Science AI; RSI simulator; and Zuck's technological pessimism

New DiG-bench benchmark of 70 hidden-rule games shows only Opus 5 and Fable 5 solving the hardest tiers, probing AI discovery and creativity.

Import AI 469 highlights DiG-bench (Discovery in Games), a benchmark of 70 handcrafted games with hidden rules and objectives where only 21 games are public and most are kept private to avoid training contamination. Only Opus 5 and Fable 5 with Claude Code solved any Tier 7 tasks (about 0.2 success), with GPT-5.5 next; the games are text-based and have beaten every human tester at least once. The newsletter also covers an RSI simulator game by Paradigm Research and Inherent's Faraday, a post-trained open-weight model that supervises frontier models to improve scientific research output.

Import AI·Aug 17, 13:05 UTC · Aug 17, 2026AI research