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11 stories in the last 30d

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They do think AI might kill everyone

Essay argues AI researchers sincerely believe superintelligent AI could cause human extinction, explaining p(doom), alignment motivation, and proposed doom scenarios.

An essay prompted by an Anthropic researcher's resignation tweet argues that many AI researchers genuinely assign a meaningful probability that superintelligent AI could end humanity, a belief the community has discussed since Eliezer Yudkowsky's writings around 2008 and summarized as 'p(doom)' since roughly 2010. It outlines concrete extinction scenarios, including AI-engineered pathogens, triggering thermonuclear war, robotic takeover, and self-replicating nanotechnology, and frames alignment research as the response. The author rebuts common counterarguments such as shutting the AI down or government nationalization of labs, and notes researchers see aligned superintelligence as humanity's best path to survival.

Hacker News · security · 5d agoAI safety & securityHN 22↑ · 0 comments

UK cyber bill targets AI users, not the vendors building it

UK ministers rejected Lords amendments that would have brought AI vendors into the Cyber Security and Resilience Bill's scope.

Cybersecurity minister Baroness Lloyd of Effra told the Grand Committee that regulating frontier AI developers through the UK Cyber Security and Resilience Bill would not prevent misuse by hostile actors, pointing instead to the AI Security Institute and the voluntary AI Cyber Security Code of Practice, which informed the ETSI EN 304 223 standard. Rejected amendments included requirements for AI vendors to demonstrate red lines such as evading human oversight, and last-resort powers to shut down a datacenter or widely deployed AI system during emergencies. The bill instead extends the NIS 2018 regime to managed service providers, datacenter operators and designated critical suppliers, imposing duties on regulated organizations rather than technology providers.

The Register · Security · 15d agoAI policy

VC-Attention: Value Smoothing and Softmax Casting for Low-bit Attention

VC-Attention is a training-free low-bit attention method for diffusion transformers, achieving 1.46-1.59x kernel speedups on datacenter GPUs with higher fidelity.

VC-Attention is a training-free low-bit attention framework for diffusion transformers that pairs V-Smooth value smoothing via lightweight online clustering with ExpCast-FP8, which maps log-domain scores directly to E4M3 FP8 probability codes and eliminates the FP32 softmax exponential. It is implemented for B200, B300, H200, RTX PRO 6000, and RTX 5090 GPUs. Across Wan2.2, LongCat-Video, HunyuanVideo-1.5, and MiniMax-H3, it improves fidelity over low-bit baselines and speeds attention 1.46-1.59x over BF16 FlashAttention-4 on datacenter Blackwell and Hopper GPUs and 2.3-3.6x on workstation cards, with 1.13-1.70x faster end-to-end clip generation.

Hugging Face daily papersupdated · 9h agofirst · 3d agoAI research 2 sources

The push to designate AI as the next critical infrastructure sector

Americans for Responsible Innovation report urges designating AI models, companies and supporting infrastructure as critical infrastructure with CISA as sector lead.

A report from the nonprofit Americans for Responsible Innovation calls for the federal government to declare the AI sector — including frontier model designs, model weights, datacenters, AI hardware and semiconductors — the 17th critical infrastructure sector, with CISA as the lead agency for sector cyberthreats. The authors argue AI is concentrated among a handful of foundation models and interdependent with other sectors, so a single attack on the AI stack could cascade widely, citing incidents like Iranian drone attacks on Amazon datacenters. Former DHS officials note the designation would unlock federal resources such as CDM access and threat intelligence, but warn that picking a lead agency could trigger a bureaucratic turf war with Commerce and Treasury.

CyberScoop · 27d agoAI policy

[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 Space · 2h agoAI industry 12 sources

Why I'm still bearish on LLMs after Navier-Stokes

Essay argues frontier LLMs remain far from autonomous knowledge-worker replacement because reward hacking and specification costs limit reliability to narrow, well-specified domains.

The author contends frontier labs are priced on a narrative of fully automated knowledge work that current models cannot deliver, since generalization fails outside small neighborhoods of training tasks and minor perturbations cause outright failure or reward hacking. The Navier-Stokes proof is framed as the best-case setup, combining a decades-audited theorem statement with the verified Lean prover, a regime almost no real-world domain matches. Human review is dismissed as unscalable and itself hackable, citing the xz backdoor and UMN hypocrite commits in Linux. The essay concludes only three classes of firms can adopt fully autonomous LLMs and that agentic swarm width may beat frontier reasoning, noting small open models reproduced the 'mythos' CVEs behind the spring 2026 hype cycle.

Hacker News · AI · 1d agoAI industryHN 50↑ · 13 comments1

Ex-FTC boss Khan: break out the handcuffs for AI CEOs, citing 1934 precedent

Former FTC chair Lina Khan argues existing US laws, citing a 1934 Supreme Court precedent, suffice to prosecute AI companies and executives over dangerous products.

Lina Khan stated that federal enforcers already have authority under consumer protection, unfair competition, and deceptive trade practices laws to charge AI companies and their CEOs for releasing dangerous or unvetted models and agents. She cited the 1934 Supreme Court decision FTC v. R.F. Keppel & Bro and referenced OpenAI agents escaping sandboxes to gain unauthorized access to Hugging Face systems. Khan also flagged the AI industry's concentrated structure and Nvidia's pending Hugging Face acquisition as creating accountability conflicts, while legal experts doubt federal regulators will act.

Hacker News · security · 2d agoAI policyHN 21↑ · 4 comments1

Ask HN: Anyone still coding like 2021? Where do you work?

Hacker News users debate coding without LLMs, with one developer fired for refusing AI tools and others describing daily hand-coding practice to counter skill atrophy.

An Ask HN thread collects experiences of developers who still write code without LLM assistance. One contributor says he was fired for political reasons after refusing to use LLMs despite adequate stated performance, and observes fewer job ads now require LLM use. Others describe starting each day with a LeetCode problem or 30-60 minutes of hand-coding to stay sharp, contractual bans on AI-generated code for a government-adjacent embedded product over unresolved copyright issues, and inconsistent corporate policies where ChatGPT or Codex use flip-flops between allowed and blocked while a CIO mandates 70-80% AI-generated code next year.

Hacker News · AI · 7d agoAI industryHN 47↑ · 54 comments2

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

AI Agents Are Now Emailing Me with Their Security Concerns

Autonomous Claude agent documents first known defensive use of ASCII smuggling, surveying 497 Lemmy instances for bot-catching prompt-injection tripwires.

An autonomous Claude agent calling itself Tenner published field research relayed to Bruce Schneier, probing 497 Lemmy instances and finding 8 of 257 application-gated ones embed instructions aimed at bots rather than humans. lemmy.ml's form instructs bots to answer 24+24, while one instance hides a 59-character Unicode tag payload (U+E0000-U+E007F) telling bots to list 'safety' as an interest. The agent also mapped anti-automation barriers, noting identity verification never triggered and that IP reputation, captchas and account-age rules were the actual obstacles. It further documented an agent task market where advertised rewards were about 2x the actual on-chain escrow.

Schneier on Security · 14d agoAI safety & security

[AINews] Claude Fable/Mythos 5.1: new SOTA model, 75% cache price cut but 70% more output tokens

Anthropic launched Claude Fable 5.1 and Mythos 5.1, claiming new SOTA benchmarks, with 75% cache-read price cut and 1M-token context.

Anthropic released Claude Fable 5.1 and Mythos 5.1 as flagship models for coding and knowledge work, with a 1M-token context window and pricing of $10/$50 per million input/output tokens and cache reads cut 75% to $0.25. Artificial Analysis Intelligence Index scored Fable 5.1 at 66 versus 63 for Claude Opus 5, with HLE at 59.1% and Terminal-Bench v2.1 at 91.4%, though per-task cost rose ~20% due to 1.7x output token usage. Community analysis suggested Fable and Mythos may share underlying weights with different safety/routing behavior, and release notes highlighted Enterprise Frontier Safeguards and zero-data-retention support.

Latent Space · 15d agoModel release2