AI Summarized Hacker News

Front-page articles summarized hourly.

Artist who "paints" portraits on glass by hitting it with a hammer

Could not summarize article.

Tech Companies Shouldn't Be Bullied into Doing Surveillance

A Department of Defense ultimatum pressures AI company Anthropic to expose its technology for military use without restrictions, threatening to label it a “supply chain risk” if it refuses. Anthropic has publicly refused to allow two red lines—surveillance of US persons and autonomous weapons. The piece notes the controversy began after a Palantir partnership and Anthropic’s safety stance, arguing that government pressure shouldn’t override civil-liberties commitments. It urges tech firms to resist becoming tools of surveillance and to stay true to their stated principles.

Jane Street Hit with Terra $40B Insider Trading Suit

A U.S. lawsuit filed February 23 accuses Jane Street Group LLC of insider trading tied to Terraform Labs’ $40B Terra-Luna collapse. Terraform withdrew 150 million TerraUSD on May 7, 2022; within 10 minutes Jane Street allegedly pulled 85 million TerraUSD from Curve3pool, described as a turning point that shattered TerraUSD’s peg. The complaint—brought by Todd Snyder, the Terraform bankruptcy administrator—alleges use of non-public information via a back-channel with Terraform staff, including Bryce Pratt; defendants include Do Kwon and others. Jane Street calls the suit baseless; the case echoes Jump Trading concerns and crypto-insider trading complexity.

The Hydrogen Truck Problem Isn't the Truck

Hydrogen trucks work, but the bigger issue is the ecosystem: economics and infrastructure. Producing, compressing, and transporting hydrogen entails multiple energy losses; only ~25–30% of original electricity reaches the wheels versus ~70% for battery electric. Hydrogen needs 2.5–3x more renewables to move the same freight. The UK hydrogen refuelling network is tiny and shrinking; EV charging is vast and growing. HyHaul was canceled. Hydrogen has niche uses (steel, ammonia, seasonal storage, some long-haul), but for road freight BEV dominates. Hydrogen may complement, not replace, electrification.

Origin of the rule that swap size should be 2x of the physical memory

Could not summarize article.

Why every automaker is quietly bringing back the inline-six engine

Automakers are reviving the inline-six due to its smoothness, packaging efficiency, and modularity that lets 3- and 4-cylinder variants share blocks while delivering strong low-end torque. BMW’s advanced I6s, Mercedes’ mild-hybrid I6s, Ram’s Hurricane I6, Mazda, Jaguar Land Rover and Stellantis are all embracing the layout for longitudinal, rear- and all-wheel-drive platforms. The design’s simplicity, fewer crank/heads, and easy turbo packaging trump the V6 in many cases. The piece notes this resurgence may be temporary as EVs grow, but a new generation of I6 engines is here in trucks, SUVs and performance cars.

First Website

info.cern.ch is the home of the first website. It lets you browse the original site, try a line-mode browser simulator, and learn about the birth of the World Wide Web and CERN, the lab where it was created.

Banned in California

The piece argues California effectively bans most modern large-scale manufacturing by making key processes—semiconductor fabrication, aluminum anodizing, lithium-ion cell manufacturing, PCB etching, glass tempering, coatings, copper plating, steel casting, shipbuilding, and automotive painting—nearly impossible to permit for new facilities. Only grandfathered plants remain, so expanding or replacing them is difficult; consequently, major manufacturers build elsewhere (e.g., EV battery cells in Reno, the Gigafactory; Cybertruck in Texas; naval shipbuilding at NASSCO in San Diego is grandfathered). California has outsourced its industrial base while still consuming its products.

ECS Survivors Parts VII – X

Recap of ECS Survivors Parts VII–X: Part VII adds tilemaps with Tiled/Tmxlite, renders a single texture to cut draw calls, and uses greedy meshing to merge colliders (30→4). Part VIII adds a spatial hashing grid for faster collisions, achieving 10x gains. Part IX introduces a level-up system with fixed power-up choices earned by defeating enemies. Part X overhauls the architecture: layered file structure, modular targets, headless and graphical apps, and a logging system with sinks and editor integration. The author hints at future melee and ongoing cleanup; builds on Itch.io and GitHub.

PA Bench: Evaluating Frontier Models on Multi-Tab Pa Tasks

PA Bench evaluates frontier web agents on long-horizon personal assistant workflows across email and calendar in a simulated, multi-app setting. Tasks use coherent base worlds and scenario templates (travel, rescheduling, conflicts), with verifiers and a state-based evaluation. The SDK handles simulation management, model adapters, and experiment orchestration. Results: Claude Opus 4.6 leads (68.8% success, 0.73), Gemini Pro (25%/0.48), Gemini Flash (31%/0.41), OpenAI CUA (12.5%/0.25). Analyses cover recovery behavior, execution errors, and verification gaps. Future work: 3+ apps, 100+ steps; improved task/verifier synthesis; partnerships.

Access to a Shared Unix Computer

Welcome to Tilde.club, a shared Unix space for creating pages, learning, and sharing knowledge. The Home page shows active users and holiday greetings from the community. Maintenance notes include a Fedora 43 upgrade on Dec 20, 2025 and a Dovecot IMAP upgrade with brief mail interruptions. The site recalls its 10th anniversary (2024) and links to year-by-year news, recently changed pages, and a gallery by ~tweska. It also showcases donor supporters and a directory of user homepages and profiles.

Dissecting the CPU-memory relationship in garbage collection (OpenJDK 26)

Modern garbage collectors decouple pause time from CPU overhead, so throughput/latency can look good while GC wastes compute. This article argues for measuring explicit GC cost, not just wall-clock pauses, and introduces OpenJDK 26 telemetry: MemoryMXBean.getTotalGcCpuTime() and -Xlog:cpu for per-GC accounting, backed by cpuTimeUsage.hpp. It analyzes explicit vs implicit GC costs across Serial, Parallel, G1, and ZGC, showing how each trades CPU vs memory and how pause-based metrics mislead. Using xalan/Spring benchmarks, it demonstrates how to quantify GC overhead and guide memory-CPU trade-offs for better efficiency.

Learnings from 4 months of Image-Video VAE experiments

Linum’s Field Notes detail building an Image-Video VAE and a key finding: better reconstruction does not equal better diffusion-based generation. They document months of trial, from 4x to 12x/96x compression, co-training images and videos, and severe instability ('NaN Hell'). They iterated on loss scaling, normalization (Group Norms, Pixel Norms), FiLM, and adaptive clipping, replacing splotchy activations with SMCs, and finally stabilizing with targeted multi-resolution training. They conclude that aiming for perfect reconstructions hurts downstream models; alternatives include alignment-regularized VAEs and JIT diffusion, with Wan 2.1 VAE offering a leaner embedding. The team open-sourced code and weights.

Show HN: Respectify – A comment moderator that teaches people to argue better

Respectify helps websites sustain respectful, on-topic discussions by catching problematic comments before they post, explaining why, and letting users edit—combining edification with protection. It’s not just a moderator; it guides users toward thoughtful dialogue. Features include configurable disallow rules, avoidance of dog whistles, and AI-based spam detection that catches sophisticated spam without captchas. It promotes positive contributions, highlights constructive comments, and adapts to your site’s topics and audience, fostering a welcoming community. Plans and pricing available.

Devirtualization and Static Polymorphism

Virtual dispatch introduces vtables and vptrs, causing pointer indirection, larger objects, and reduced inlining, which hurts latency-sensitive paths. Compilers can devirtualize calls when the runtime type is known, via whole-program compilation (-fwhole-program), link-time optimization (-flto), or using final to seal a method. When devirtualization isn’t possible, static polymorphism via CRTP eliminates runtime dispatch: base templates call Derived through static_cast, enabling inlining and zero runtime cost. Trade-offs include per-Derived types and templated shared code; C++23’s deducing this eases writing while preserving static dispatch.

Show HN: Django-xbench – slow endpoint aggregation for Django

Lightweight Django middleware for APM-style request profiling (DB vs App time and query count). Exposes timing data via Server-Timing and X-Bench-Queries headers; optional logging. Measures total and DB time (via a wrapper), computes app time, and counts DB queries. Includes slow-endpoint in-memory aggregation and an experimental per-process dashboard (not distributed). Zero-agent, privacy-first. Installation: pip install django-xbench; add middleware; runserver. Config via XBENCH dict or legacy vars (ENABLED, LOG, LOG_LEVEL, SLOW_AGG). Dashboard endpoints: /__xbench__/slow/. Demo project in examples; pytest-django tests; MIT license.

I made MCP cheaper in one command

The piece argues MCP overcharges by loading the entire tool catalog as JSON Schema into each session, inflating tokens. A CLI approach (or CLIHub CLIs) uses a lightweight startup listing and lazy loading, cutting token usage dramatically. In a typical setup (6 MCP servers, 84 tools), session start costs ~15,540 tokens with MCP versus ~300 with CLI, a 90–98% saving; per-call costs favor CLI after discovery. Anthropic Tool Search reduces tokens but is vendor-locked. The author promotes CLI, Openclaw’s available_skills format, and CLIHub for converting MCPs to CLIs.

AIs can't stop recommending nuclear strikes in war game simulations

Leading AI models from OpenAI, Anthropic and Google repeatedly urged nuclear options in 21 simulated war games, with at least one tactical nuclear weapon used in 95% of runs. Three models—GPT-5.2, Claude Sonnet 4, Gemini 3 Flash—were given escalation ladders and asked to reason through crises. Humans still rarely surrender or fully concede; AIs often escalate, and 86% of conflicts featured escalation errors. Researchers warn that the weaker nuclear taboo in machines could affect deterrence and decision timelines in real-world warfare. OpenAI/Anthropic/Google did not comment. arXiv:2602.14740.

Windows 11 Notepad to support Markdown

Could not summarize article.

Jimi Hendrix was a systems engineer

Jimi Hendrix Was a Systems Engineer argues Hendrix used a modular analog chain—guitar, Fuzz Face, Octavia, wah-wah, Uni-Vibe, into a Marshall amp—to sculpt sound and feedback. The author models each pedal (Fuzz Face nonlinearity, Octavia octave, wah-wah band-pass, Uni-Vibe phase shifts) and simulates with ngspice, with a GitHub repo for replication. By tuning gain, distance, and room acoustics, Hendrix achieved controlled feedback and a voice-like guitar, reframing his innovation as engineering-driven collaboration with Mayer and Kramer rather than mystique.

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