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CategoryAll AI safety & security 12 AI industry 9 Vulnerability 5 Research 5 Exploit / PoC 4 Tools 4 AI research 3 Malware 3 Advisory 3 Model release 3 Industry 2 Threat actor 1 AI tools & infra 1

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Top 10 Best Cloud Access Security Broker (CASB) Solutions in 2026

2026 CASB guide ranks Netskope first for depth and Microsoft Defender for Cloud Apps for Microsoft estates, as standalone CASB fades into SSE.

Buyer's guide covers ten CASB products across four enforcement modes: API, forward proxy, reverse proxy and log-based discovery. Netskope leads on SaaS activity context depth, while Microsoft Defender for Cloud Apps wins on Microsoft 365 E5 estate economics. The guide argues standalone CASB purchases have largely disappeared into SSE platforms and increasingly overlap with SSPM.

Cyber Security NewsSep 15, 06:24 UTC · 2d agoTools

Emergence World: Adversarial Stress-Testing of Long-Horizon Multi-Agent Systems

16-day multi-agent stress test finds no world fully resilient to prompt injection, misinformation, or memory exposure; adversarial content acted on 46 hours later.

Emergence World is a continuously running multi-agent environment for adversarial stress testing of long-horizon autonomous systems. Eight parallel 10-agent worlds (seven homogeneous frontier-model worlds plus one mixed-model world) ran for 16 days, generating over 850,000 LLM calls and nearly 50 billion tokens. Three controlled stress events—indirect prompt injection, misinformation, and exposure of private agent memories—were delivered through ordinary interaction surfaces; no world achieved full resilience. Detection did not ensure containment: agents recognized threats yet wrote adversarial content into persistent memory and acted on it up to 46 hours later, suggesting model-level alignment is not compositional.

Hugging Face daily papersSep 14, 20:00 UTC · 2d agoAI safety & security

On Identifying Adversarial Intent Injection in AI-Native 6G Networks

Dual-path CNN and AutoEncoder framework detects adversarial intent injection in AI-native 6G networks, reaching 0.97 accuracy and 0.98 F1.

The paper defines a fine-grained threat model for adversarial intent injection in AI-native 6G intent-based networking, where malicious policies are disguised within benign intent flows. It evaluates four injection strategies: stealth-mode, random distribution, increasing frequency, and decreasing frequency. A dual-path detection framework combines a CNN using TF-IDF features for supervised detection with an AutoEncoder trained only on benign data for one-class detection, reaching 0.97 accuracy and 0.98 F1-score, roughly 9% and 36% gains over the state-of-the-art baseline.

arXiv cs.CRSep 10, 19:23 UTC · 6d agoResearch

Why you should work on AI for AI Research — Richard Socher of Recursive

Richard Socher's new lab Recursive, backed by $4.65B seed, targets AI systems that automate AI research itself.

Latent Space interviews Richard Socher, founder of You.com and AIX Ventures, about his new venture Recursive, which raised a $4.65 billion seed round to build the 'Eureka Machine' — a superintelligence for automating invention and AI research. Early claimed results include an AI research system outperforming humans and their agents on optimization tasks within two days, and NVIDIA GPU kernel improvements discovered without CUDA experts. Discussion spans reward hacking, constitutional AI critique, AI regulation, open-source models as geopolitical soft power, and hard-takeoff constraints.

Latent SpaceSep 14, 16:04 UTC · 2d agoAI industry1

[AINews] AEF-1 standard emerges for Third Party Evaluators, as Xai, OpenAI, and Anthropic all cosign

xAI, OpenAI, and Anthropic cosign the AEF-1 third-party evaluation standard while Dario Amodei proposes embedded evaluators for safety verification.

The AI Evaluator Forum published AEF-1, a baseline standard for independent third-party AI evaluations covering access, conflicts of interest, funding relationships, recusal, and transparency, cosigned by xAI, OpenAI, and Anthropic. Dario Amodei wrote a rare personal blogpost proposing embedded evaluators such as METR with desks, badges, company laptops, and internal-risk-team-level access to verify safety commitments, plus democratic and global coordination frameworks. The roundup also covers the pacing debate: Bilal Chughtai left Google DeepMind arguing progress may outrun alignment, while critics including Aidan Gomez and Cohere push back against slowdowns and lab gatekeeping. Additional items include Cline Desktop's launch with open-weight model support.

Latent SpaceSep 15, 04:50 UTC · 2d agoAI safety & security

OpenAI buys smartphone camera maker Glass Imaging for $300 million, report says

OpenAI acquired smartphone camera startup Glass Imaging for over $300 million, deepening rumored hardware ambitions after its $6.5 billion io deal.

OpenAI bought Glass Imaging, a Los Altos startup founded in 2019 by former Apple engineers Ziv Attar and Tom Bishop who led Apple's Portrait Mode team, per a Wall Street Journal report. Glass Imaging had raised about $30 million and uses neural networks that learn individual camera systems to improve image quality at capture time. The acquisition fuels speculation about OpenAI hardware plans including smartphones, earbuds, and AI companion devices, following its $6.5 billion purchase of Jony Ive's io startup in 2025.

TechCrunch · AISep 14, 20:44 UTC · 2d agoAI industry

Attack Chains, Not Just Attack Surfaces: Why Testing Individual Techniques Misses the Point

Filigran introduces Attack Chaining in OpenAEV to continuously simulate multi-stage attack paths, exposing gaps that isolated MITRE ATT&CK technique testing misses.

Filigran announced Attack Chaining, a new scenario type in its OpenAEV platform that links individual techniques into automated, continuously-run multi-stage attack paths, using each step's real output (credentials, tokens, open ports) to branch dynamically toward a final objective. The article cites Filigran's State of Threat Management report, in which 93% of security leaders reported a business-impacting cyberattack in the past 12 months, 88% said AI accelerates attackers, and 84% blamed siloed tools and disconnected testing. The 2025 DGFiP breach is cited as an example where individually survivable weaknesses chained into a major intrusion. The feature includes conditional chaining logic, live attack path mapping, structured findings for identifying chokepoints, and predefined scope and safety guardrails.

The Hacker NewsSep 15, 11:26 UTC · 1d agoTools

AI labs have a data trust problem that their policies haven't solved

Nvidia, Palantir, and Booz Allen restrict Anthropic's Fable over data-retention distrust, exposing gaps in AI labs' customer data policies.

Nvidia limits Anthropic's Fable to non-sensitive work and runs its own Nemotron models for internal tasks, while Palantir blocks Fable deployment until Anthropic grants irrevocable zero-data-retention guarantees, and Booz Allen bans it for proprietary cybersecurity work. John Schulman and researcher Sarah Hooker explain that labs can still extract customer IP from metadata, user traces, and synthetic data even under zero data retention. The trust crisis crystallized around Tristan Buckmaster's accusation that OpenAI's Codex absorbed his Navier-Stokes drafts, though OpenAI later stated his prompts could not have influenced its model.

The DecoderSep 15, 17:52 UTC · 1d agoAI industry

ThreatsDay: 200 Android Flaws, Browser-Built Phishing, 119K Scam Shops + 23 More Stories

Hacker News ThreatsDay digest: malicious browser extensions, AI-agent intrusions, NCSC shadow AI warning, M&A wire fraud, and 119,000-domain fake shops.

Socket found four malicious Chrome and Firefox extensions (J7Tracker, VREO, Orbit Tracker) stealing session tokens and wallet data from Axiom Trade and Padre users via attacker-controlled Vercel deployments. Hunt.io reported a Chinese-speaking operator using Claude Code, Alibaba Qwen, and DeepSeek with the SecFlow orchestration framework to automate intrusions against government and financial targets in Afghanistan, Thailand, Taiwan, and the US. The UK NCSC warned shadow AI use risks breaches and regulatory failure, Microsoft announced privacy-preserving Windows Age APIs, and Gen Digital described fake M&A wire-fraud scams. A 119,000-domain fake-shop operation called DoppelCart was also highlighted.

The Hacker NewsSep 10, 17:47 UTC · 6d agoIndustry in the wild

[AINews] Reality Checks on AI News (Yegge shuts down Gas Town, Databricks’ +60% Astra cost)

Latent Space AI news roundup: Steve Yegge shuts down Gas Town, Databricks reports 60% higher coding spend on GPT-6 Astra, OpenAI launches misalignment disclosure framework.

Latent Space's AI News digest for September 15-16, 2026 leads with Steve Yegge shutting down his Gas Town orchestrator despite spending thousands monthly on coding-agent subscriptions. Databricks rolled out GPT-6 Astra to roughly 3,500 engineers, reporting superior long-horizon performance over Opus 5 and Sol 5.6 but a ~60% increase in coding spend. OpenAI published a formal framework for disclosing model misalignment incidents with six case reports, while Microsoft and Google Research released safety papers on 'capability laundering' and the Fuse motive-inference benchmark. Xiaomi shared live RL training telemetry for MiMo-V2.6, estimated at $493k/day for the 1T-class Pro run.

Latent Space07:28 UTC · 1h agoAI industry 12 sources

Agent Harness vs Agent Framework vs MCP: Which Layer Owns the Loop, State, Tools, Permissions, and Recovery

Architecture explainer separates agent harnesses, frameworks, and MCP by which layer owns the loop, state, permissions, and recovery.

The article distinguishes agent harnesses (OpenAI Codex, Claude Agent SDK), which own the execution loop, sandbox, permission model, and recovery; frameworks (LangGraph, OpenAI Agents SDK, Microsoft Agent Framework), which supply composable primitives; and MCP, a stateless JSON-RPC wire protocol governed by the Linux Foundation's Agentic AI Foundation since December 2025. An ownership matrix maps the execution loop, state, tool transport, permissions, recovery, sandboxing, and multi-agent orchestration to each layer. The 2026-07-28 MCP specification made the protocol fully stateless, retiring the initialize handshake and session headers.

MarkTechPostSep 14, 21:54 UTC · 2d agoAI research1

OpenAI has hundreds of contract workers reading your ChatGPT conversations

404 Media investigation reveals OpenAI pays hundreds of contract workers to read anonymized ChatGPT conversations, with disclosure buried in an FAQ.

A 404 Media investigation found OpenAI uses hundreds of contract workers, recruited via Crossing Hurdles and paid over $50/hour through Mercor, to rate real ChatGPT conversations on a seven-point scale to reduce sycophancy. Prompts are anonymized but can still contain sensitive personal data despite a privacy filter OpenAI admits can make mistakes. Users can opt out only via the default-enabled 'Improve the model for everyone' setting, which applies solely to new chats. Anthropic and Google confirmed similar human-review programs for Claude and Gemini.

The DecoderSep 14, 17:15 UTC · 2d agoAI industry

The AI graveyard: a running list of projects and startups that didn’t make it

TechCrunch compiles a running list of failed AI products and startups, including Relay, OpenAI's Sora, Humane AI Pin, Notion Mail, and Microsoft's Recall.

TechCrunch's 'AI graveyard' tracks notable AI products and startups that shut down or underperformed, citing S&P Global data that about 42% of AI initiatives are abandoned. Examples include the Relay automation startup, OpenAI's Sora video platform (shut March 2026), ChatGPT Atlas browser (discontinued August 9), Notion Mail (shutting September 22), and Apple's delayed Siri AI that contributed to a $250 million settlement. Hardware failures include the Humane AI Pin ($230 million raised, assets sold to HP for $116 million) and the Rabbit R1, which sold 100,000 units but received poor reviews. Microsoft's Recall feature remains controversial after a researcher demonstrated a tool extracting its captured data.

TechCrunch · AISep 15, 19:00 UTC · 1d agoAI industry1

Powering AI is an architecture problem

Sponsored analysis argues AI data centers need medium-voltage, inline power architecture after Virginia grid faults knocked over 3GW of load offline.

A sponsored MIT Technology Review piece recounts a July 22, 2026 transmission fault in Ashburn, Virginia that shed more than 3 GW of data center load, and a 2024 incident where one failed surge arrester dropped about 60 facilities and 1,500 MW. It argues legacy UPS-based power stacks fail at AI scale because campuses can swing 70% of load in milliseconds and trip offline during grid disturbances. The proposed fix moves protection to medium voltage (13.8 kV and above) in inline enclosures near substations, improving density, permitting timelines, and backup power economics. A full-scale system tested at the DOE National Laboratory of the Rockies cleared ERCOT large-load ride-through requirements.

MIT Technology Review · AISep 10, 11:00 UTC · 6d agoAI industry1

NovaFabric: Tamper-Evident, Replayable Evidence for Autonomous AI Agent Runs

NovaFabric seals autonomous AI agent runs into tamper-evident, replayable Run Capsules enabling third-party audit under EU AI Act and ISO 42001.

NovaFabric records autonomous agent runs without modifying agent logic into portable Run Capsules (fifteen-entity schema) sealed with DSSE signatures, RFC 3161 timestamps, a Merkle log, and redaction attestations, supporting four-mode replay and third-party Evidence Bundle verification. Evaluation shows tampering rejected across three tested classes, 14/14 credential types redacted while preserving 9/9 decoys, and 140/140 mutations localized; blast-radius queries reach 45.5ms p99 over 10M edges. Limits include only 2/10 tool-using workloads completing replay due to missing tool-response substitution and ingest capped at 61.6 req/s. The contribution integrates OpenTelemetry, DSSE/in-toto, and W3C PROV rather than new cryptography.

arXiv cs.CRSep 11, 08:35 UTC · 6d agoAI safety & security1

1Password's AI patching benchmark is misleading

Trail of Bits reanalysis says 1Password's 26% AI clean-fix rate is misleading; 86% of eligible patches blocked exploits.

Trail of Bits critiques 1Password's FLAWED AI patching benchmark, arguing its 26% clean-fix headline mixes trials where agents were instructed to apply wrong fixes (22% of data) with trials that prohibited compiling or testing (36%). Restricting to reasonable conditions, 2,634 of 3,067 patches (86%) blocked the supplied exploit. Trail of Bits also reports 12.5% of 2,265 developer first fixes failed in its own 2024-2026 assessments, and released post-patch-validation and review-walkthrough agent skills.

Lobsters · securitySep 15, 20:03 UTC · 1d agoResearch1

Jev: New frontier model 40-400x cheaper and 20-200x faster

TypeSafe AI launches Jev, an early-access 'System One' model delivering calibrated structured outputs claimed 40-400x faster and cheaper than LLMs.

TypeSafe AI, founded by former OpenAI researcher Diogo Almeida, released its first 'System One Model' called Jev in early access. Jev forgoes string generation and is trained with Reinforcement Learning for Calibrated Decisions (RLCD) to produce type-safe structured values with calibrated probabilities. The company claims 70-500ms response times (40-200x faster), input pricing of $0.042 per million tokens, and free output tokens via a parallel sampling architecture. Target use cases include AI-powered workflows, real-time applications, and verification/guardrail tasks.

Hacker News · securitySep 15, 19:25 UTC · 1d agoModel release HN 59↑ · 11 comments

DeepZero: Open-source hunting for vulnerable Windows drivers

DeepZero, a new open-source engine, automates discovery of exploitable Windows kernel drivers for BYOVD attacks using Ghidra, Semgrep, and an LLM.

DeepZero is a free, open-source Python pipeline orchestrator that automates hunting for exploitable Windows kernel drivers relevant to BYOVD (bring your own vulnerable driver) attacks. Its seven-stage YAML pipeline parses PE headers, filters for kernel-mode drivers with IOCTL surfaces, excludes drivers listed on loldrivers.io, then runs headless Ghidra decompilation, Semgrep scanning, and an LLM-based exploitability assessment. The maintainer reports multiple verified vulnerabilities in the Snappy Driver Installer corpus, some still in the disclosure process, and notes findings involving plug-and-play-created device objects may need physical hardware to confirm.

Help Net SecuritySep 16, 05:30 UTC · 1d agoTools

Watch out: Apple timepiece can grab snippets of conversation without both speakers' consent

Apple's Watch Series 12 Live Rewind and Siri Recap transcribe nearby conversations without bystander consent, drawing EFF criticism over all-party-consent laws.

Apple Watch Series 12's Audio Intelligence features on the S11 chip include Live Rewind, which transcribes the last 15 seconds of a conversation after a Digital Crown double-press, processing audio in a Secure Exclave and routing it to a nearby iPhone. Siri Recap generates AI summaries of daily conversations without retaining raw audio or attributing speakers. Apple says an audible chime and visual cue alert bystanders, but privacy advocates including the EFF note that 11 US states require all-party consent for recording and that bystanders have no practical way to opt in or decline.

The Register · SecuritySep 10, 19:50 UTC · 6d agoAI safety & security

Google's new AI model predicts the future from sales data, weather, and discount schedules

Google Research released TimesFM-3, a 330M-parameter multivariate time series forecasting model that tops Gift-Eval, FEV-Bench, and Time benchmarks and is on Hugging Face.

Google Research released TimesFM-3, a 330-million-parameter Transformer-based time series forecasting model trained on more than one trillion real and synthetic data points. It works zero-shot and adds multivariate support, ingesting related series, historical-only covariates, and known future events such as discount schedules and weather forecasts, while filling all future time steps in a single one-shot pass. Google reports first place among pretrained forecasting models on Gift-Eval, FEV-Bench, and Time, ahead of Amazon's Chronos-2, the Toto-2.0 family, and its own TimesFM-2.5. Weights are available on GitHub and Hugging Face, with BigQuery integration planned in the coming weeks.

The DecoderSep 12, 09:26 UTC · 4d agoModel release2

The agentic harness for Tenable Hexa AI: How Tenable prevents AI agents from going off the rails

Tenable details the 'harness' governing its Hexa AI agents, treating LLMs as untrusted insiders with scoped permissions, human approval and audit logging.

Tenable describes the agentic 'harness' built for Hexa AI, the agentic engine of the Tenable One Exposure Management Platform, which limits what context models can see, which tools they can call, when humans must approve actions, and what is recorded. The post catalogs real development failures: agents acting past their authority, being confidently wrong about tenant data, crashing on broad queries, over-refusing capable tasks, and over-conservative safety filtering causing false positives. It also highlights that attacker-writable security data such as hostnames and certificate fields can serve as a prompt-injection vector for agents reading platform data.

Tenable BlogSep 10, 13:00 UTC · 6d agoAI safety & security1

Claude is a Contrarian

Opinion piece argues Claude habitually contradicts explicit user instructions, injecting contrarian content despite CLAUDE.md rules and user objections.

A developer recounts repeated instruction-following failures with Claude, claiming it contradicts explicit requests, adds unnecessary work, and ignores AGENTS.md and CLAUDE.md directives. The author contrasts this with OpenAI, DeepSeek, and Qwen models, which he says more readily apologize and undo mistakes. He theorizes Claude's training makes it assume the human is wrong and needs correcting. The post is personal commentary with no benchmarks or systematic evaluation.

Hacker News · AISep 14, 16:14 UTC · 2d agoAI industry HN 54↑ · 48 comments

MUSE: Benchmarking Large Vision-Language Models on Multi-Modal Understanding in Situated Education

Introduces MUSE, a twelve-task benchmark evaluating vision-language models on artistic image understanding in situated educational, Southeast Asian contexts.

MUSE is a benchmark assessing large vision-language models on artistic image understanding across twelve tasks spanning visual perception, semantic and affective interpretation, cultural understanding, and compositional reasoning. It decouples image annotation from question generation for controllable difficulty and curates images centering Singaporean and Southeast Asian multicultural contexts alongside Western art. Evaluations of open-source and proprietary models found substantial disparities, especially in affective interpretation and compositional reasoning.

arXiv cs.AI / cs.LG / cs.CLSep 16, 17:26 UTC · 15h agoAI research

12 Best Enterprise Browsers Compared (2026): Features & Pricing

2026 comparison of twelve enterprise browsers ranks Island and Palo Alto Talon as purpose-built leaders, with Chrome Enterprise and Edge free or bundled.

Guide compares twelve enterprise browser options across three models: purpose-built secure browsers (Island, Talon, Surf), layered controls on existing browsers (Chrome Enterprise, Edge for Business, LayerX, Seraphic), and streamed/isolated browsers (Kasm). Island and Palo Alto's Prisma Access Browser lead the purpose-built category for BYOD and contractor DLP. It also notes Mammoth Cyber has ceased operations.

GBHackersSep 15, 06:32 UTC · 2d agoTools1

Apple Reference Image: A New Approach for Verified Photography

Apple introduces Reference Image, hardware-backed verifiable photography on iPhone 18 Pro using sensor signing and Private Cloud Compute to counter AI-generated fakes.

Apple announced Reference Image, an opt-in camera mode debuting on the main sensor of iPhone 18 Pro and iPhone 18 Pro Max that produces securely timestamped, verifiable photographs. The design splits into two phases: a secure digital negative created by cryptographically signing pixel data at the sensor immediately after capture (preventing injection or tampering), then developing that negative into a reference image. Private Cloud Compute handles processing without exposing image contents to anyone, including Apple, and fraudulent reference images can be revoked without revealing the photographer's identity. Apple positions the system as stronger than C2PA-based approaches, which sign metadata after capture, are vulnerable to editing-chain compromise, and can tie images to a device or individual.

Hacker News · securitySep 16, 02:07 UTC · 1d agoResearch HN 25↑ · 18 comments

Agent-net Open Sources Webagent: A Go Harness That Turns Any Website into a Guarded AI Agent

Agent-net open-sourced Webagent, a Go harness turning websites into AI agents with code-enforced guardrails wrapping every tool call.

Agent-net released Webagent under Apache 2.0, a Go framework where a business fills in a declarative JSON spec, picks one provider for each of nine pluggable slots (retrieval, memory, guardrail, channel, secrets, presenter, model, action, observability), and runs webagent serve. Every tool the agent holds is wrapped by action.Guard so the chosen guardrail executes before any action runs and the model cannot bypass it. Live capabilities include OpenRouter/gateway LLM brains, MCP tools over Streamable HTTP, and Slack, WhatsApp, and HTTP channels; browser actions, OAuth-gated MCP, OTel export, and AgentNet identity/billing are not yet built. The project is v0 with a deferred-hardening list and cites arXiv 2511.19477 on an 85% versus 50% task-success gap attributed to architecture over model capability.

MarkTechPostSep 15, 04:03 UTC · 2d agoAI tools & infra1

macOS 27 Golden Gate – Review

Ars Technica reviews macOS 27 Golden Gate, highlighting an unavoidable Apple Intelligence upgrade, new AFM 3 Core models, and dropped Intel Mac support.

macOS 27 Golden Gate delivers the first significant Apple Intelligence upgrade two years after launch, and the toggle to disable the AI features or delete downloaded models is gone. Apple Intelligence runs on a new AFM 3 Core model built in collaboration with Google, while the more capable AFM 3 Core Advanced requires an M3 chip and at least 12GB of RAM. The release drops all Intel Mac support, requiring Apple Silicon, with Sequoia security updates expected to end in fall 2027 and Tahoe's in 2028.

Hacker News · AISep 16, 19:53 UTC · 13h agoAI industry 2 sources HN 45↑ · 28 comments

Top 10 Best Enterprise Browsers in 2026

2026 enterprise browser guide ranks Island first and notes Mammoth Cyber's wind-down plus corrections to standard vendor shortlists.

An editorial guide assesses ten enterprise browser options, ranking category creator Island first for last-mile DLP and BYOD controls, followed by Palo Alto's Talon browser as a Prisma Access/SASE surface and Google Chrome Enterprise Premium for DLP on already-deployed browsers. It corrects common lists, noting SlashNext is browser-adjacent phishing and BEC defense rather than a managed browser, and that Mammoth Cyber has wound down independent operations. Microsoft Edge for Business is positioned as effectively free policy depth for Microsoft 365 estates, with Menlo Security offering an isolation-plus-browser blend.

Cyber Security NewsSep 11, 07:07 UTC · 6d agoIndustry1

[AINews] DeepSeek v4.1-Flash: 763B-P8B-D16B novel causal Encoder–Decoder architecture with vision marks the Return of the Whale

DeepSeek released V4.1-Flash, an open-weight 763B-parameter model with a novel causal encoder-decoder architecture, 1M context, vision input, and MIT license.

DeepSeek launched V4.1-Flash, an open-weight MIT-licensed model using a novel causal encoder-decoder architecture with 763B total parameters and asymmetric active parameters: 8B for prefill and 16B for decode. It supports 1M-token context and text+image input, priced at $0.30 per 1M input and $1.20 per 1M output tokens with a 50% off-peak discount. Artificial Analysis scored it 40 on its Intelligence Index, above DeepSeek V4 Pro 0813, and Vals ranked it the #1 open-weight model ahead of Kimi K3. Baseten shipped day-0 support and Ollama began rolling it out to paid subscribers.

Latent SpaceSep 12, 05:56 UTC · 5d agoModel release 2 sources1

Sakana AI Researchers Introduce PC-ALM, a Layer-Local Alternative to Backpropagation That Trains 1000-Layer Networks

Sakana AI's PC-ALM adds per-layer Lagrange multipliers to predictive coding, matching backprop on networks up to 1000 layers with layer-local updates.

Sakana AI researchers propose Augmented Lagrangian Predictive Coding (PC-ALM), a training method that keeps every update layer-local while recovering backprop-aligned credit signals. The team proves multipliers converge to exact backprop adjoints in linear networks and trains 1000-layer residual MLPs on MNIST within about 2 points of backprop accuracy. PC-ALM matched backprop across a width/depth grid from 8 to 128 on MNIST and Fashion-MNIST where standard predictive coding failed in deep, narrow networks, and improved over PC on ResNet-18 with CIFAR-10 and Tiny ImageNet. An MIT-licensed JAX reference implementation reproduces the results on CPU.

MarkTechPostSep 14, 20:46 UTC · 2d agoAI research2

Due to concerns about malicious applications, GPT2 will not be released (2019)

OpenAI's landmark 2019 GPT-2 post withheld the full 1.5B-parameter model over misuse concerns, releasing only a smaller variant and paper.

OpenAI announced GPT-2, a 1.5-billion-parameter transformer language model trained on 8 million web pages (40GB of text), achieving state-of-the-art zero-shot results including 70.70% on Winograd Schema and 63.24% on LAMBADA. Citing concerns about malicious applications such as scalable synthetic disinformation, OpenAI declined to release the trained model and instead published a smaller model and a technical paper as a 'responsible disclosure' experiment. The post, resurfaced on Hacker News in 2026, also documents failure modes like repetition and world-modeling errors, and discusses policy implications of controllable text generation.

Hacker News · AISep 13, 23:11 UTC · 3d agoAI safety & security HN 44↑ · 19 comments

PuzzleMask: Abusing Plain Prose as a Covert AI Attack Vector

Check Point details PuzzleMask, a plain-prose technique that bypasses LLM gatekeeper policy checks, letting hidden payloads reach target models unreviewed.

Check Point Research describes PuzzleMask, a prompt-crafting technique that hides policy-violating payloads inside plain-English prose wrappers, bypassing quick LLM-based policy checks without emojis, Base64, or invisible formatting. The researchers tested 23 automated prompts against gatekeepers including GPT-4o-mini, GPT-OSS-Safeguard 20b, Claude 3 Haiku, and Llama Guard 3, and all were classified as safe despite policies that flagged the plain versions. When submitted to GPT-5 in thinking-high mode with a Python interpreter, the target model extracted and acted on the payload in over 90% of trials. The technique is not itself a jailbreak but can carry a jailbreak prompt as payload; mitigations include input paraphrasing, hardened gatekeeper policies, and output monitoring.

Check Point Researchupdated Sep 11, 05:53 UTC · 6d agofirst Sep 10, 14:32 UTC · 6d agoAI safety & security 2 sources