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Senior engineers are spending their week cleaning up AI-generated code

New Relic study finds AI-generated code doubles critical runtime issues, with senior engineers losing a third of their week to fixes.

A New Relic survey of U.S. technology leaders reports AI now writes the majority of shipped code, with senior SRE and DevOps engineers spending up to a third of their week triaging and refactoring it. A large majority of organizations had at least one AI-related production failure in the past six months, and roughly three in ten saw newly introduced security vulnerabilities. AI-generated code showed nearly twice as many critical runtime issues as peer-reviewed human-authored code, with gaps concentrated in edge cases, concurrency, deprecated APIs, and complex state changes. Most teams now prompt AI tools to embed logs and traces directly into generated code.

Help Net Security · 24d agoAI industry1

[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

Three-quarters of Ransomware Attacks Target Mid-Market Firms

Black Kite research finds roughly 75% of ransomware attacks target mid-market firms, with manufacturers hit most often.

Attack-surface management vendor Black Kite published findings that about three-quarters of ransomware attacks target mid-market organizations. Manufacturing is the sector most likely to be attacked. The report frames mid-market companies as the sweet spot for ransomware operators.

Infosecurity Magazine · 29d agoRansomware in the wild

A brief history of AI executives calling for regulation

The Verge chronicles the history of AI executives, from Samuel Butler and Turing-era warnings to Altman and Musk, publicly calling for AI regulation.

The article traces recurring calls for AI regulation, from Samuel Butler's 1863 warnings and Alan Turing's 1951 lecture to Bill Joy's 2000 essay and Microsoft's 2018 facial recognition stance. Modern examples include Elon Musk's 2017 remarks to US governors, the 2023 Future of Life Institute pause letter, and Sam Altman's 2023 Senate testimony. It argues such appeals from industry leaders who profit from AI warrant skepticism.

The Verge · AI · 18h agoAI policy

What’s next for CISA’s CDM program that gives cybersecurity tools to federal agencies

CISA officials outline future plans for the CDM program, emphasizing speed, automation, unified data, and data-driven federal risk management.

Speaking at an Elastic Federal Cyber Defense Breakfast, CISA officials described next steps for the Continuous Diagnostics and Mitigation (CDM) program that supplies cybersecurity tools to federal agencies. Acting deputy program manager Richard Grabowski named velocity, unification, and data-driven risk management as core goals, including a three-year roadmap to expand SIEM-as-a-Service. Federal CISO Mike Duffy urged aggregating demand across agencies, buying outcomes rather than products, and designing acquisition for continuous improvement. CISA's Matt House tied the program's evolution to post-SolarWinds needs for a government-wide common operating picture.

CyberScoop · 1d agoPolicy & legal

From Megawatts to Tokens: How NVIDIA Maximizes AI Factory Production

NVIDIA detailed DSX power-management results: Lambda gained 24% token throughput at fixed power, and an AI factory auto-shed 1MW via Emerald AI's grid program.

NVIDIA says Lambda's first validation of DSX MaxLPS on HGX B200 servers ran 19 nodes within a 16-node power budget, lifting cluster token throughput 24% (roughly 4M to 5M tokens/second) and improving performance per watt by 23%. NVIDIA projects DSX MaxLPS can enable up to 40% more GPU capacity for Vera Rubin NVL72 factories within the same megawatt budget. Emerald AI's Conductor platform, running at NVIDIA's Eos factory with Silicon Valley Power, responded to over 200 utility demand signals, automatically dropping power from 4MW to 3MW without interrupting priority workloads. The first dedicated DSX Flex commercial deployment is planned at a 96-megawatt Manassas, Virginia facility.

NVIDIA Blog · 1d agoAI industry

What Zero-Day Response Should Be in the Post-Mythos Era

Picus Security outlines a zero-day response playbook where defenders simulate exploit technique chains before public PoCs exist.

The article uses PaperCut NG/MF's August incident — exploitation in the wild before any patch, with the first emergency fix bypassed the same day and a third landing September 1 — as the template for AI-accelerated vulnerability response. It walks through a hypothetical CVE-2026-1001 (explicitly made up) to argue defenders should map CVEs to ATT&CK technique chains and simulate them against NGFW, WAF, EDR, endpoint hardening, and SIEM controls within minutes of disclosure. It notes disclosure-to-exploitation time has fallen from 21.5 days to hours.

BleepingComputer · 1d agoResearch in the wildCVE-2026-1001

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 · 2d agoAI research1

Claude Fable 5.1 Solves the Cyphral Distich, a 370-year-old cipher

Claude Fable 5.1 solved Sir Thomas Urquhart's 370-year-old Cyphral Distich cipher, recovering a hidden royalist prayer for Charles II.

Vals AI reports that Claude Fable 5.1 solved the Cyphral Distich, a 64-number cryptogram from Sir Thomas Urquhart's Logopandecteision unsolved since 1653, in 44 minutes using 176k tokens with no human hints. The key insight was that the cipher's key was the book itself: each number indexes a word in the corresponding Proquiritation, taking the first letter, yielding 'O GOD UPHOLD KING CHARLS THE SECOND AND MAKE HIM THE SUPREME RULER OF THIS LAND'. The model also deciphered the larger Cyphral Octastich (285 numbers) from The Jewel (1652) using page-based word indexing, recovering all but nine letters of a royalist prayer. The puzzle had been listed among Klaus Schmeh's Top 50 unsolved encrypted messages.

Hacker News · AI · 3d agoAI researchHN 63↑ · 6 comments1· 1 read

Can LLMs Engineer Their Own Agent Harness? ByteDance Seed’s HarnessDev Says Only 34 of 64 Changes Generalize

ByteDance Seed's HarnessDev benchmark finds LLM-built agent harnesses trail human engineering on code and search, with only 34 of 64 revisions generalizing.

Researchers from ByteDance Seed, SUTD, Georgia Tech, M-A-P, and TokenWave.AI introduce HarnessDev, a benchmark that evaluates the runnable agent harness an LLM writes rather than its answers, using Creation and Evolution stages across SWE-bench Pro, Terminal-Bench 2.1, MLE-bench, EQ-Bench3, and BrowseComp (2,207 instances). Six creator models including Opus 4.8, GPT-5.5, Gemini 3.1 Pro, DeepSeek V4 Pro, Qwen 3.7 Max, and Seed 2.0 Pro were tested; Opus 4.8 posted the best average of 67.8 versus an 86.2 human-engineered reference. Self-built harnesses beat references on writing and ML experimentation but lag badly on code and search, and quality proved executor-specific: Opus 4.8 fell from 69.3 to 33.0 on SWE-bench Pro when the executor was switched to Gemini. Evolution gains were small and noisy: of 64 adjacent changes, feedback and held-out scores agreed only 34 times (53.1%), and much generated state and memory code never executed.

MarkTechPostupdated · 12h agofirst · 5d agoAI research 19 sources

Why the current tech backlash feels different

The Verge's Decoder mailbag discusses the current tech backlash, arguing AI hype overstates verifiability outside software engineering.

Nilay Patel's Decoder mailbag episode addresses listener feedback on the widely discussed 'software brain' essay. He argues AI hype is concentrated on software because code is verifiable through compilation, while domains like drug discovery, math and science lack equivalent verifiability. The episode also touches on AI backlash, surveillance, data centers and upcoming midterm coverage.

The Verge · AI · 6d agoAI industry1

10 most critical LLM vulnerabilities

OWASP updated its Top 10 LLM application vulnerabilities, ranking prompt injection first and elevating excessive agency to third amid agentic adoption.

OWASP refreshed its Top 10 list of critical vulnerabilities in LLM applications, for the first time incorporating real-world incident data alongside expert voting. Prompt injection and sensitive information disclosure remain first and second, while excessive agency jumped from sixth to third as agentic systems that call APIs and execute code proliferate. Unbounded consumption of AI resources rose in prominence, while improper output handling dropped to the bottom as output sanitization becomes widespread. The list includes remediation guidance such as strict output schemas, human-in-the-loop approvals, and least-privilege credentials held in application code.

CSO Online · 6d agoAI safety & security

Anthropic built an economic model that frames its CEO's bleakest job forecasts as an outlier scenario

Anthropic published an economic model with three US economic scenarios through 2030, framing CEO Dario Amodei's bleakest job-loss forecasts as the outlier outcome.

Anthropic released an economic model outlining three scenarios for AI's impact on the US economy through 2030. The modest scenario resembles the internet's impact with stable wages, the middle scenario doubles growth while knowledge worker wages stagnate, and the extreme scenario projects 17.9% knowledge worker unemployment with labor's GDP share falling from 60% to 45%. CEO Dario Amodei's May 2025 warning of up to half of entry-level office jobs vanishing and 10-20% unemployment aligns with the extreme scenario, which the model treats as the least likely outcome.

The Decoder · 7d agoAI industry2

Sam Altman calls GPT-6 Astra rollout ‘messy’ as enterprise users wait for access

OpenAI's GPT-6 Astra launch hit access problems; Sam Altman apologized as availability gradually expanded from Daybreak partners to Pro, Enterprise, and API users.

GPT-6 Astra, launched September 4 as OpenAI's most advanced model, was initially accessible only to organizations enrolled in its Daybreak cybersecurity program, leaving Plus, Pro, Business, Enterprise, and API users waiting. Altman called the rollout 'messy'; by September 5 access had extended to Pro, Enterprise, and Business Premium users in ChatGPT's Work and Codex products plus the API. Analysts from Gartner and Greyhound Research said the staged rollout highlights the gap between announcement and production availability, urging enterprises to verify actual access levels and strengthen governance, security, and cost controls before adopting Astra's autonomous workflows.

CSO Online · 9d agoAI industry

WordPress Security Plugins: How to Choose the Right One

Sucuri's guide breaks WordPress security plugins into hardening, malware scanning, integrity monitoring, and filtering types, and explains how to evaluate and layer them.

The Sucuri guide explains that WordPress security plugins bundle five capabilities - hardening, malware detection, integrity monitoring, activity logging, and application-level filtering - and that plugins run only after WordPress loads, unlike server-level firewalls. It lists leading causes of compromise: outdated plugins and themes, weak or reused credentials, nulled premium software, insecure configuration, and shared-hosting cross-contamination. It concludes with evaluation criteria and a post-installation security checklist for owners without dedicated security teams.

Sucuri Blog · 12d agoIndustry

Adaptive Gated Deepfake Detection for Low-Resolution and Resource-Constrained Environments

AdaGate-DF routes deepfake detection by image quality through dual multi-exit gates, hitting 0.9370 AUC on Celeb-DF with low inference latency.

AdaGate-DF is an adaptive gated deepfake detection framework that uses image-quality cues to send high-quality images through earlier exits, saving compute in resource-constrained settings. On Celeb-DF it achieves an AUC of 0.9370, outperforming MaD-CoRN and DefakeHop++, and reaches 0.9708 at 384x384 resolution. On FaceForensics++ it remains effective under class imbalance while balancing uncertainty-aware prediction and computational efficiency.

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

Jackrong/Qwopus3.8-27B-Flash-GGUF — new model trending #26 on Hugging Face

Community fine-tune Qwopus3.8-27B-Flash, built on Qwen3.8-27B, cuts agent reasoning latency with 12.8% faster decoding and 80.7% MTP acceptance.

Jackrong released Qwopus3.8-27B-Flash, a fine-tune of Qwen3.8-27B optimized for long-running agent workloads, reporting 12.8% faster decoding and 80.7% multi-token-prediction acceptance. Training used roughly 1.5 million teacher-scored SFT examples filtered to the top 10%, followed by reinforcement training with NVIDIA NeMo-RL and GSPO. The author notes an explicit trade-off: MMLU-Pro mixed-set scores are lower than the base model, and a known bug can produce incorrect Python indentation. Author-provided benchmarks have not been independently verified.

Hugging Face trending models · 12d agoModel release2

The democratization of cyber warfare — and what it means for CISOs

CSO Online argues AI is democratizing cyber warfare, citing Taiwan's first largely autonomous AI-driven attack that hit 85 government accounts.

CSO Online argues AI is accelerating the democratization of cyber warfare by collapsing cost and skill barriers, with effects already reaching the private sector. It cites the August disclosure of the first largely autonomous AI-enabled attack on Taiwan government infrastructure, where up to eight agents operating simultaneously compromised at least 85 government accounts and exfiltrated more than 2,500 personnel records before expanding to the nuclear safety agency and energy companies. The piece places this in a historical arc from crossbows to cheap drones and cites Kane Gamble's 2015 solo social-engineering compromise of senior US intelligence officials as evidence that low-resource attackers were already viable.

CSO Online · 12d agoIndustry

1-15 August 2026 Cyber Attacks Timeline

Hackmageddon logged 108 confirmed cyber incidents for August 1-15, 2026, led by malware and public-facing application exploits.

Hackmageddon recorded 108 confirmed incidents between August 1-15, 2026, with cybercrime accounting for 90 of them (83.3%). Malware was the dominant vector with 26 incidents (24.1%), and exploitation of public-facing applications (MITRE ATT&CK T1190) was the leading initial access vector in 36 classified incidents. Cyber espionage motivated 15 incidents, and Public Administration was the most-targeted sector with 25 of 139 sector mentions.

Hackmageddon · 14d agoResearch 2 sources

DavidAU/Qwen3.8-27B-TURBO-Fable-Cold-Fusion-735-882-Heretic-Uncensored-NEO-CODER-MAX-MTP-GGUF — new model trending #8 on Hugging Face

A new Qwen3.8-27B GGUF fine-tune claims ARC-C 735 at 8-bit with thinking tokens cut 2x-10x versus the base model.

Independent creator DavidAU released a GGUF fine-tune of Qwen3.8-27B built with Unsloth, claiming ARC-C of 735 at 8-bit and 719 at 4-bit, trending #8 on Hugging Face. The 'TURBO' variant cuts thinking tokens by one half to as much as one tenth while retaining output quality and detail. The repo ships both regular and MTP quants and claims gains over the base model across seven benchmarks, using 'Cold Fusion (GAIN + Unsloth)' and 'Fable Fusion 711' training methods.

Hugging Face trending models · 15d agoModel release

Week in review: Compromised Zimbra servers, previously patched Citrix NetScaler flaw exploited

Help Net Security's weekly digest highlights 274 compromised Zimbra servers, Gitea and Citrix NetScaler KEV additions, a PaperCut zero-day, and a suspected Iran-linked power plant attack.

The roundup reports at least 274 internet-facing Zimbra instances compromised via CVE-2026-73570, critical Gitea CVE-2026-60004 added to CISA's KEV catalog after exploitation began, and previously patched Citrix NetScaler flaw CVE-2026-8452 exploited in the wild. It also covers PaperCut NG/MF zero-day attacks, a suspected Iran-linked shutdown of a UK power plant, an FBI seizure of domains tied to a China-linked group that hit NASA, DOJ and the Senate, a cyberattack disrupting Boston Scientific, and the Manchester Airports Group breach. Additional items include Chameleon SEO poisoning phishing, Android car head unit proxy botnet malware, ReliaQuest social engineering by ShinyHunters, fake OpenAI Codex macOS malware, and AI-related workforce and supply chain interviews.

Help Net Security · 18d agoIndustry in the wildCVE-2026-73570CVE-2026-60004CVE-2026-8452

AWS’s new sign-up gives accounts spend caps, email invites, and agent-set permissions

AWS's new sign-up flow gives fresh accounts agent-configured permissions, email-based team access, and per-project monthly spend caps starting at $20.

New AWS customers can sign up with Google, GitHub, or Apple identities, start with $100 in Free Tier credits, and build inside a project where AWS and coding agents automatically configure permissions and install tools like the AWS CLI and Agent Toolkit. In a demo, an agent deployed a Lambda function, DynamoDB table, and API Gateway endpoint without any manually written IAM policies. Paid projects get monthly spend limits starting at $20 that pause the project when reached, and the gradual rollout applies to new customers only.

Help Net Security · 1h agoAI tools & infra