Hacker News, Distilled

Declining Birth Rates & Modern Parenting

• Several argue that efilists “don’t need to do much” because everyday life is already making parenting unattractive.
• Drivers cited: helicopter parenting, criminalization of unsupervised play, disappearance of “third places” (malls, arcades), screen addiction, car culture, dual-income necessity, and dispersed families.
• Some parents push back, saying online narratives exaggerate how uniquely hard things are now and romanticize a past that was often materially harsher.

Individual vs Societal Incentives to Have Children

• Many note that in rich countries, individuals are often better off not having kids (money, freedom, career), while societies need children to avoid aging crises.
• There’s debate over who should pay to support parents, with tension between “we can’t afford it” and “we’re richer than ever; this excuse is nonsense.”
• Concerns about future old-age support: childfree people may face a thin, overburdened service base and political backlash from younger generations.

Antinatalism/Efilism: Arguments and Critiques

• Thread distinguishes “philosophical antinatalism” (“procreation is morally wrong”) from people who avoid kids for convenience or economics.
• Some claim the latter isn’t antinatalism at all; others say it is functionally similar.
• Critics see efilism as a reductio of utilitarianism, over‑weighting suffering and ignoring benefits of hardship, growth, and empathy.
• Others prefer nihilism: the universe is meaningless, but that doesn’t morally mandate ending life.

Religiosity, Fertility, and Future Demographics

• One line of argument: if “normies” don’t reproduce, high-fertility religious and ideological minorities will dominate over time.
• This is framed as memetic evolution: any “enlightened” movement discouraging reproduction self‑extinguishes.
• Some predict more religious or more extreme future societies; others expect reversion toward centrist norms.

Cosmism and Expansionist Alternatives

• In sharp contrast to efilism, a few espouse a “cosmist” or transhumanist view: intelligence should spread, extend lifespans, colonize space, maybe “awaken” the universe.
• Supporters find this inspiring and life‑affirming; detractors call it egoistic, imperialistic “sci‑fi villain” thinking.

Online Radicalization and Platforms

• The attacker is portrayed as “terminally online” and reportedly radicalized via Reddit.
• Commenters observe more calls for violence and negativity on large subreddits; question why Reddit escapes scrutiny compared to other platforms.
• There’s concern that modern social media structurally amplifies extreme, death‑obsessed subcultures compared to older, more ironic movements like Voluntary Human Extinction.

Mental Health, Young Men, and Violence

• Several link such acts to isolation, lack of community for young men, poor mental healthcare, and broken families, though others demand stronger evidence for demographic claims.
• The bombing is seen as both ideological (death cult logic about preventing suffering) and possibly a cry for help from someone deeply unwell.

Moral Philosophy, Suffering, and the Attack

• Some argue the bombing is incoherent: it causes suffering to prevent hypothetical future suffering. Others counter that, within efilist logic, large net suffering reduction could “justify” violence.
• Broader point: the internet reliably produces pathological extremes of many moral systems (utilitarianism, religious ethics, etc.); there may be no “internet-proof” philosophy.

Reception of Karton and motivation

• Many welcome Karton as a KDE-native alternative to virt-manager, especially for users already committed to Plasma and Qt applications.
• Some feel virt-manager is powerful but clunky, dated, and poorly maintained (e.g., HiDPI issues, lack of undo, awkward XML editing).
• GNOME Boxes is described as simpler but too limited and buggy; several people see a gap between “virt-manager complexity” and “Boxes minimalism” that Karton might fill.
• A few question whether “another GUI for KVM/QEMU” is needed, suggesting Cockpit or existing tools are enough, but others argue a traditional desktop UI (like VirtualBox/VMware) is better for non-experts.

UI technology and naming

• Mixed reactions to Kirigami/Qt Quick: some criticize perceived jank, inconsistencies, and preference for Qt Widgets; others argue it’s necessary for integration with modern Plasma and can be made to look good.
• Several comments attribute Plasma’s “janky” feel to QML rendering and even joke about commercial Qt licenses.
• The name “Karton” triggers linguistic digressions (German/Dutch/Spanish for “cardboard”), plus jokes about KDE’s “K-” naming tradition and VirtualBox/“boxes” associations.

Desired features and integration

• Users want better graphics support (e.g., Vulkan via libvirt), GPU passthrough, and robust audio.
• A recurring wish: running guest apps as if they were native windows (like Parallels “Coherence mode” or RDP’s single-app mode). People note partial analogues via X11 forwarding, WSL2, RDP, and VirtualBox workflows, but no clean, mainstream Linux solution.
• Some highlight SPICE/libvirt frontends as buggy and poorly maintained, particularly around audio and HiDPI.

KDE vs GNOME, design, and stability

• Long debate about KDE vs GNOME:
  • KDE praised for features, performance, and flexibility; critics say what it needs most is fewer bugs.
  • Several argue Plasma 5/6 are now very solid and that reputations from the KDE 4 transition are outdated.
  • GNOME is often described as pretty but overly minimal, opinionated, and reliant on fragile extensions. Some still prefer GNOME 3’s UX or tablet support.
• Aesthetic opinions diverge: some find KDE dated and “programmer-designed” (squares, padding, complex menus); others see KDE as the only “modern-looking” option and consider whitespace-heavy styles (GNOME/Windows) superficial.

Scope of KDE and ecosystem concerns

• Some argue KDE should focus on the DE/window management, not more apps like a VM manager, fearing developer effort is spread too thin.
• Others counter that building a broad application suite has always been part of KDE’s mission, and Karton (a small student project) likely won’t meaningfully drain resources.
• Theming and icon integration spark a side debate: one side claims cross-app theming routinely breaks apps; the other insists proper use of theme variables should make theming safe and is part of user freedom.

Scope of the UN Principles

• Commenters note the UN “open source principles” are high-level, intent-focused guidelines rather than binding policy or precise definitions.
• Some view them as mostly symbolic unless tied to procurement rules, interoperability requirements, or funding for maintenance.

France’s Open Source Reality: Progress vs. Cynicism

• Multiple posts describe strong French digital public services: unified login (FranceConnect), online taxes, fines, health, IDs, address changes, etc., often backed by free software and open data.
• Others counter with bad experiences (education portals, FranceConnect limitations, enterprise tax UI, digital ID app not open source, encryption export bureaucracy), and argue most money still flows to Microsoft/US cloud.
• Recent Microsoft “open bar” contracts for education and Office 365 moves are cited as evidence that practice lags rhetoric; defenders say backlash itself shows norms have shifted and that migrating huge estates takes many years.
• Examples of concrete projects: LibreOffice on hundreds of thousands of gov desktops, the open “Suite numérique,” Renater collaboration tools, open data like real-estate (DVF) and the Référentiel National des Bâtiments with wiki-style corrections.

UN / Government Role in Open Source

• Some ask why the UN should be involved at all; others answer: governance, standard-setting, and using its large IT budget to encourage open, interoperable systems.
• A parallel debate asks what counts as a “public utility” in the US and whether similar principles could realistically take hold there.

Office Suites and Usability

• There’s sharp disagreement on LibreOffice: some call it unusable with poor UI and contributor-hostile processes; others argue that mandated/default tools are often disliked but still workable, and that Office 365 is far from flawless.
• Collaboration features (cloud editing and sharing) are seen as the main reason MS Office remains entrenched.

AI, LLMs, and Definitions of “Open”

• Commenters wonder whether the UN principles extend to AI models and how “open source” will be defined there.
• Meta’s Llama licenses are criticized for usage restrictions; French comparison tools correctly avoid calling them open source but are accused of downplaying some limits.
• OSI’s AI definition and initiatives like Eleven Freedoms are discussed; some prefer stricter community standards (e.g., Debian’s ML policy) over OSI’s approach.

Regulation, Liability, and Institutional Capture

• A long subthread fears that state-defined “open source” plus regimes like the EU Cyber Resilience Act could overburden small commercial FOSS vendors while leaving only large corporations able to monetize open code.
• Others respond that voluntary developers are explicitly exempted, that product liability is normal in other sectors, and that engaging early with legislation can correct the worst proposals.
• Broader worry: “open source” as a label is being diluted and co‑opted by large foundations, corporations, and intergovernmental bodies, while underfunded grassroots efforts (e.g., alternative phone OSes) struggle.

Transparency, Democracy, and Voting

• Several argue that open-source government software will increasingly distinguish democracies from authoritarian systems, given how much power runs on code.
• Others stress that even with open code, trust problems remain (compilers, hardware, deployment), and many advocate sticking with paper ballots plus human observers for elections.

Tools and Ecosystem Notes

• UN use of CryptPad Forms instead of Google is praised as a concrete privacy-respecting choice aligned with the principles.
• There is interest in more EU/federal-style funding bodies for “sovereign tech,” with debate over whether for‑profit vehicles (like German GmbH-based initiatives) are appropriate.

DIY vs. Installer Economics

• Many readers are struck by the large gap between DIY cost and installer quotes; DIY looks tempting if you can handle design, sourcing, and physical work.
• Others argue that professional quotes aren’t as outrageous if you factor in labor, permitting, warranties, and roof work; some think the author slightly overpaid on hardware at retail.
• A recurring “middle path” is: hire electricians/roofers for dangerous parts, DIY design and panel/battery choices, or buy from the same wholesalers installers use.
• Some note that subsidy structures and tax credits can distort quoted prices upward.

Permitting, Regulation, and Utilities

• Permitting and PG&E/PUC rules are seen as the biggest barriers: complex interconnect rules, inspections, placards, and in some cases bans on sizable off‑grid systems.
• Several posts frame the spread of home solar as a symptom of a “broken” or rent‑seeking utility regime, especially in California.
• Others counter that distributed solar does reduce transmission/distribution strain, which partly explains why utilities resist it.

Load Size, Homelabs, and Efficiency

• The author’s ~1 kW continuous rack triggers a long side discussion:
  • 1 kW 24/7 is ~8,760 kWh/year, more than total house usage for some people.
  • Detailed homelab breakdowns (drives, NICs, fans, PoE, RAM) show how easily racks hit 1–4 kW.
  • Several argue for “rightsizing”: newer CPUs, fewer spinning disks, more virtualization, and hot/cold storage tiers could cut power by ~10×.
• Others are relaxed: as long as solar/batteries cover it and the owner is happy, it’s just another lifestyle choice.

Batteries, Storage, and Grid-Level Issues

• Multiple DIYers report large LFP banks (10–160 kWh) and off‑grid systems with near‑zero ongoing costs once built.
• Cost of batteries per kWh is falling fast; some commenters claim lifetime costs of a few cents per kWh cycled.
• Grid-level storage ideas appear: molten salt/sand heat storage, gravity storage, neighborhood batteries, EVs as mobile storage, hot‑water‑tank buffering.
• Net metering changes (e.g., NEM3, Dutch feed‑in charges) push people toward local batteries and self‑consumption rather than exporting at poor rates.

Distributed Generation and Off‑Grid Microgrids

• Several describe sophisticated private microgrids (farms, coffee estates, rural compounds) with tens of kW of PV, multi‑house distribution, hydro/biogas backup, and automation.
• These systems often grew “organically” over years and now beat local grid economics, especially where grid power is expensive or unreliable (Caribbean, Nigeria, some US rural areas).
• Commenters working on policy see distributed generation as likely mainstream within 10–20 years, especially where transmission is saturated.

International Prices, Subsidies, and Policy Distortions

• Readers from Europe, Canada, Australia, and elsewhere report dramatically cheaper installs: 10–13 kW PV plus batteries often for €7–15k equivalent, post‑subsidy.
• This leads to speculation that US costs are inflated by soft costs (permitting, licensing, liability, sales overhead), tariffs, and subsidy‑driven price capture.
• Debate ensues over whether subsidies inherently raise prices versus whether insufficient competition and heavy regulation are the core problem.

Complexity, Safety, and Who Should DIY

• Several people say the article scared them off full DIY; electrical and regulatory complexity feel too high compared with plumbing/woodwork.
• Others insist it’s “more straightforward than people think” if you’re comfortable with heavy lifting, basic electrical knowledge, and slow, careful planning.
• Safety concerns arise around large battery banks in homes (fire, insurance), high‑voltage DC, and roof work; many advise at least contracting critical pieces to licensed pros.

Project goals and scope

• Vaev’s primary long‑term goal is high‑quality rendering of static documents, especially as the core of the “paper‑muncher” PDF engine intended to replace wkhtmltopdf in Odoo.
• General web browsing and JavaScript support are not excluded, but are presented as a possible later phase rather than the main objective.
• Vaev is part of a hobby OS ecosystem (Skift) but is intended to remain cross‑platform rather than spun out as a separate product.

PDF generation and existing tools

• Several commenters discuss moving away from wkhtmltopdf to setups based on PhantomJS, Puppeteer/Chromium, or newer tools like Typst and WeasyPrint.
• Experiences: browser-based PDF generation can be slow (tens of seconds), but careful reuse of a long‑lived headless page can achieve sub‑100ms renders.
• PrinceXML is praised for quality but criticized for not being FOSS; WeasyPrint and wkhtmltopdf are seen as either slow or unreliable.
• There is interest in Vaev as a non‑Chromium, open alternative for HTML→PDF.

Minimal, text‑only, and “smolweb” browsing

• Some want a GUI browser that renders only text and links (no images/media), beyond terminal tools like Lynx; Dillo with images disabled is mentioned as close.
• A broader idea: standardize a minimal subset of web standards so “smolweb” sites and alternative browsers can target a stable, small feature set.
• Proposed bases include HTML 4.01 + CSS 2.1, or email‑safe HTML; others argue for keeping modern layout (Grid/Flexbox) and semantic tables for accessibility.
• Skepticism: “living standards” are seen as weaponized churn; subsets risk drifting or inheriting too much legacy cruft.

Language choice, security, and complexity

• C++ choice triggers debate: some argue modern C++ with RAII and smart pointers can be reasonably safe; others emphasize that browsers are de‑facto RCE surfaces and C++ is historically bug‑prone.
• Rust/Servo is cited as an alternative; some claim C++ projects (e.g., Ladybird) outpace Servo due to a larger C++ developer pool.
• There is skepticism about marketing claims like “lightning‑fast, lightweight, and secure” given early feature‑incompleteness and lack of visible fuzzing.
• Several commenters stress that browser engines are extraordinarily complex, second only to OSes, yet still see high educational and exploratory value in building one from scratch.

Motor torque sensing: current vs direct measurement

• Several comments debate whether motor current is a good proxy for torque.
• One side: current sensing is “good enough” and widely used in industry; with motor constants, resistance, voltage, and gear ratio you can derive torque, at least relatively.
• Other side: with high gear ratios and cheap gearboxes, current–torque correlation becomes poor; friction, temperature, and mechanical slop dominate, so you only get a vague “effort” signal, not accurate torque.
• Series-elastic mechanisms and direct torque sensing are presented as more reliable but more complex/expensive.

Child and general safety with blinds

• Key risks called out: pulling the unit off the wall, strangulation on cords, fingers caught in mechanisms, and electrical hazards for powered systems.
• Standards such as UL 325 are mentioned as important; commenters stress that safety comes from process and adherence to standards, not intuition.
• One person describes an intentionally “overbuilt” but toddler-safe mechanical opener using a weight and solenoid, with all moving parts out of reach.

Value of automated blinds and home automation philosophy

• Many describe bedroom blinds automation as unusually high “quality of life” for the price: consistent wake times, no daily cognitive load, and strong effect on mood vs artificial light.
• Others note it’s not useful if they sleep with masks or pillows over their heads.
• Repeated advice: good automation should augment, not replace, manual controls. Smart switches that still work offline and automations that don’t break basic usability are praised.
• Some argue most “control-by-app” setups are regressions; real automation is schedules, occupancy, and state-based rules that usually require no interaction.

Blackout vs light management

• Strong interest in full blackout for kids or shift workers; basic vinyl blinds are considered inadequate.
• Suggested solutions: blackout curtains (often double-rod with “pretty” outer curtains), internal blackout roller/honeycomb shades with side channels, “blockout” or “blackout thermal” blinds, European rolling shutters, and sleep masks.
• Sleep masks receive detailed endorsements from people extremely sensitive to light; others prefer to wake with sunlight and see darkness + alarms as worse.
• Temporary hacks include aluminum foil and painter’s tape, especially for travel.

Home automation stacks and tooling

• Home Assistant (including the dedicated hardware box) is repeatedly recommended as the central platform.
• Common integrations: Zigbee/Z-Wave smart plugs and switches, Hue/ IKEA lighting, ESPHome DIY sensors, MQTT, and external tools like PyScript, AppDaemon, and Node-RED for more complex logic.
• Example automations: air-quality-triggered fans, porch lights on schedules, circadian lighting, low-level night lights, temperature-controlled window A/C, and alerts when appliances (e.g., humidifiers) stop drawing power.

Commercial and alternative blind/shutter solutions

• Multiple off-the-shelf retrofits are mentioned:
  • Clip-on blind tilters (e.g., SwitchBot Blind Tilt) with solar charging and optional hubs.
  • Motor units like Ryse SmartShade for roller shades, integrated with Home Assistant.
  • 3D-printed gearboxes that sit inline with the blind shaft, using servos and ESPHome.
• For European-style exterior rolling shutters, commenters reference motorized versions (“tapparella motorizzata”) plus in-wall Wi-Fi relays (e.g., Shelly) to integrate with automation.

Thermal control and building design

• Automated blinds are also valued for passive temperature control: closing during hot sunny periods, especially on south-facing windows.
• Some argue interior blinds only partly help; exterior shading (awnings, overhangs, external shades, climbing plants) can be much more effective.
• German-style rolladen and well-designed roof overhangs are cited as powerful combined solutions for seasonal sun management.

DIY mains work and safety concerns

• One commenter harshly criticizes the article’s mains-side design (relay doubling, resistor from mains to logic, questionable connectors), calling it dangerous and likely to cause fire or insurance problems.
• Others push back that DIY learning is important, but agree high-voltage work demands more than trial-and-error and should start from solid understanding of creepage/clearance, isolation, and code.
• There’s broad agreement that mistakes with mains pose risks not just to the builder but to others and future occupants, and that low-voltage experimentation is the safer entry path.

Obsidian, Longevity, and Data Lock‑In

• Many argue the author’s “20‑year longevity” concern is actually a point in favor of Obsidian: vaults are just Markdown in a normal folder, so other editors can replace Obsidian at any time.
• Counterpoint: heavy plugin use creates “Obsidian‑flavored” Markdown and hidden dependencies on JavaScript features that may not survive or port easily.
• Some report plugin breakage over the years (live preview changes, properties/frontmatter changes), seeing this as fragility vs. the long‑term stability of simpler tools (Emacs, plain text, org‑mode).

Syncing Notes and the $4–$8/month Debate

• A major criticism of the article: treating Obsidian Sync as mandatory and expensive, ignoring that:
  • Sync can be done via iCloud, Dropbox, Google Drive, Syncthing, WebDAV, CouchDB+LiveSync, git, etc.
  • Obsidian’s own sync now has a cheaper $4/month plan and is end‑to‑end encrypted.
• Many feel $4–$8/month is trivial compared to the value of a daily tool; others push back that recurring subscriptions accumulate and they prefer free/self‑hosted sync.
• Several users describe robust setups: git+Working Copy, Syncthing‑fork, Nextcloud/WebDAV, or couchdb‑based live sync, often combined with local backups.

Rolling Your Own vs Extending Existing Tools

• Some see building a full PKMS as overkill when the main pain point was sync; a plugin or external sync solution would have been far cheaper in time.
• Others defend “reinventing” as a valid learning project and a way to fully own the stack, even if it sacrifices Obsidian’s ecosystem.
• The choice of Directus (source‑available, BSL) is criticized as not fundamentally more future‑proof than Obsidian; it simply moves lock‑in from app to CMS.

Security, Self‑Hosting, and VPNs

• Strong thread recommending: don’t expose personal services directly; put them behind WireGuard/Tailscale/Zerotier, or similar, often with home servers plus DDNS.
• Debate around “perimeter security vs zero‑trust” in homelab contexts: some argue VPN‑only access is enough for personal threat models; others emphasize layered defenses and good auth even on LAN.

Alternative PKMS Tools and Workflows

• Widely mentioned alternatives: Emacs+org‑mode (plus org‑roam), Joplin, Trilium, Silverbullet, Logseq, Anytype, Tana, Apple Notes, simple git+Markdown, VimWiki, custom CLIs, and VS Code.
• Trilium and Silverbullet receive particular praise from self‑hosters for power and extensibility; Joplin for FOSS + sync; org‑mode for text‑centric “cognitive clay.”

Meta: PKMS Philosophy and Over‑Optimization

• Several commenters caution against spending more time tuning note systems than actually thinking, writing, and revisiting notes.
• Others highlight that the “right” PKMS is highly personal; some want minimal plaintext+git, others want rich graphs, templates, and LLM‑powered search.

Perceived structure vs randomness

• Commenters broadly agree the modeled clusters, transition matrix, and section-specific patterns make the text look highly structured, not like naive random glyphs.
• Some argue this level of internal consistency would be hard to destroy even if someone tried to write “randomly,” especially for a practiced scribe.
• Others note that non-cryptographic “visual” choices (making lines look nice, filling space, avoiding or forcing repeats) could still create patterns that appear linguistic.

Hoax/gibberish vs real or constructed language

• One camp thinks the manuscript is fundamentally gibberish or a hoax/“naive art”: intentional imitation of writing without underlying language.
• Counter-arguments: statistical analyses repeatedly find language-like structure; to achieve that, a hoaxer may effectively have invented a fairly elaborate system or conlang.
• Skeptics respond that humans are poor random generators; fake language will naturally mirror properties of the author’s native language and can follow Zipf-like distributions, so “language-like” statistics don’t prove real language.
• Some distinguish between: (1) a cipher or real language; (2) a constructed or stochastic fake language; (3) unconstrained gibberish—arguing (2) is the most plausible non-linguistic explanation.

Linguistic and historical constraints

• The manuscript materials and style are consistently dated to early 15th century, ruling out some later-attribution hoax theories.
• Palimpsest hypotheses are said to be contradicted by imaging studies.
• Voynichese reportedly deviates from known languages: very few distinct signs, unusual character distributions, heavy repetition, odd lack/behavior of high-frequency words, and evidence for at least two “languages” (A/B) and multiple scribes.

Comments on the NLP approach

• Several question using an older multilingual SBERT model trained on known languages: embeddings for an unknown script may be unreliable, and suffix-stripping might remove crucial information.
• SBERT’s sentence-level design clashes with the lack of clear sentence boundaries.
• Multiple people call for controls: run the same pipeline on real texts, ciphers, and synthetic Voynich-like gibberish (some provide generators) to see if similar clustering emerges.
• There is debate over dimensionality reduction: some like PCA’s interpretability; others suggest UMAP, t‑SNE (with caveats), PaCMAP/LocalMAP, or even TDA and sparse autoencoders to probe deeper structure; also suggestions to build cluster–cluster similarity maps.

Other hypotheses and directions

• Various proposed decipherments (Germanic, Uralic, Old Turkish, recent “solutions”) are mentioned but generally described as unconvincing or non-generalizable.
• Ideas raised include brute-force word mapping with scoring by language models, distributed “SETI@home”-style search, and comparison with biblical or other 15th‑century religious texts.
• Some suggest analyzing page-to-page stylistic evolution and line-end glyph behavior as further signals of intentional structure vs decorative filler.

What the Question Misses

• Many argue the prompt is misframed: there aren’t many “secret products” the ultra‑rich buy that others haven’t heard of.
• The real differences are in how money is used: time, freedom, access, staff, and insulation from hassle and consequences, not exotic gadgets.

Spectrum of Wealthy Lifestyles

• Commenters describe a range: some billionaires live modestly and avoid attention; others (or their heirs) are entitled, ostentatious, and destructive.
• “Old money” culture often downplays visible wealth (old Volvos, plain clothes), while still quietly spending on elite schools, legacy vacation homes, and private travel.
• Several mention the “third‑generation curse”: founders are frugal, their children mixed, grandchildren often spoiled.

Access, Staff, and Problem‑Solving

• Key differentiator: access. Calls get returned, doors open, politicians and CEOs take meetings.
• At higher tiers, “family offices” and concierge services pay bills, manage investments, book travel, and smooth logistics; some see this as “Being Rich as a Service.”
• Wealth buys people more than things: housekeepers, nannies/governesses, drivers, chefs, lawyers, “fixers.” Problems are delegated instead of personally handled.
• In some countries, even middle‑class households employ multiple domestic workers; there’s debate whether this is necessary support or status‑driven exploitation.

Goods, Experiences, and Status

• Ultra‑rich do buy jets, yachts, art, multiple vacation homes, private concerts, day‑and‑date home cinema, VIP Disney tours, private museum and theme‑park access.
• High‑end hotels (Four Seasons, St. Regis, etc.) are seen less as better rooms and more as “say it once and it happens” service.
• Yet many point out rich and upper‑middle class share the same consumer tech; smartphones are a great leveller.
• Expensive goods often shift quickly from “better” to mostly positional: paying for brand, exclusivity, and social signaling.

Time, Work, and Financial Freedom

• For some, real wealth starts when you no longer need to sell time for money and can walk away from bad jobs or situations.
• A few describe modest net worth (low 7–8 figures) as enough to stop working, live comfortably, and “not care what others think.”
• Others note many billionaires never stop working, have messy personal lives, and feel trapped managing money and businesses.

Love, Happiness, and Limits of Money

• Several argue money can’t buy love, youth, or health; others counter that wealth can heavily improve odds via therapy, coaching, healthcare, and flexible time.
• There’s sharp disagreement over “money doesn’t buy happiness”: some call it cope for the poor; others say money buys comfort and options, not guaranteed joy.

Status Signaling and Privacy

• Status goods (luxury hotels, fashion, cars) are criticized as zero‑sum, but others note signaling helps form and maintain groups.
• Some claim truly powerful people under‑signal (plain clothes, no obvious luxury), using status quietly; others see lavish consumption as deliberate “peacocking.”
• Several say the best part of being rich is privacy and the ability to ignore status games while still knowing you could win them.

Inequality, Tax, and Philanthropy

• Strong debate on wealth caps and high marginal tax rates vs. property rights and incentives.
• Some want caps at the point where private wealth can distort democracy; others say past attempts failed and prefer progressive taxes and modest wealth taxes.
• Philanthropy by billionaires is contested: some highlight huge health gains; others see it as tax‑optimization and unaccountable political influence.
• There’s concern that public cynicism about billionaire charity may actually discourage doing good.

Power, Law, and Politics

• Several argue the biggest thing extreme wealth buys is de facto immunity: ability to shape law, buy influence, move to corrupt jurisdictions, and avoid consequences ordinary people face.
• Others push back with counterexamples of rich people jailed, but acknowledge that legal and political “tilt” toward the wealthy is real.

Knowledge Gaps and Moving Up

• A subthread notes many who grow up poor never learn basics of investing, 401(k)s, or using services (cleaners, lawn care, travel), even after higher earnings.
• Some see this as “unknown unknowns” transmitted via family and class: middle‑class kids get informal training in how to use money to buy time and quality, not just stuff.

Incident recap (known from the thread)

• iPhone trade‑in + Apple Card financing failed when the bank account for autopay changed.
• Trade‑in apparently didn’t complete, payment became overdue, and within ~15 days Apple disabled App Store, iCloud, Apple Music, and Apple ID–linked services, though iMessage/phone still worked.
• It took roughly nine days and multiple escalations to reach someone who could resolve it.

Who is at fault?

• One camp views this as a non‑story: the user missed serious emails, didn’t return a trade‑in, failed to pay, and then complained.
• Others argue even if it’s 100% the user’s fault, the consequences are disproportionate and the resolution path far too opaque and slow.
• Some doubt specific details (e.g., “never got a trade‑in kit” or “no Apple reply”), others say there’s no clear reason to assume lying vs. simple mistakes.

Overreach and linkage between debts and services

• Major concern: unpaid hardware leading to broad lockout of unrelated, previously paid services and purchases.
• Critics liken this to a store repossessing or disabling older, fully paid goods because you’re late on a new purchase.
• Defenders argue Apple is within its rights to withhold cloud services if a device on that account is effectively unpaid; opponents counter that disabling all linked services is unreasonable.

Risks of tightly coupled ecosystems

• Many see this as a cautionary tale about going “all‑in” with one vendor (Apple, Google, etc.).
• Losing one account can cascade into loss of phone services, photos, app access, email, and third‑party logins (“Sign in with X”).
• Several recommend: avoid “login with BigTech” for critical accounts, own your email domain, and keep financial products separate from identity/accounts.

Customer support and comparatives

• Some report Apple support as responsive and excellent, especially vs. Google’s near‑nonexistent human support for account lockouts.
• Others emphasize that the key failure here was that first‑line Apple support lacked visibility into billing/lockout status and escalation took days.

Broader policy and regulation themes

• Thread touches on the lack of “due process” for account bans and lockouts at large platforms.
• Suggestions include legal requirements for large tech companies to provide competent, reachable support and clearer separation of powers between financial products and core identity/services.

Mechanical properties & “stronger than steel”

• Commenters dig into the cited Nature paper: densified wood reaches ~550–600 MPa tensile strength along the grain, with density ~1.3 g/cc and ~10× higher specific strength than mild structural steel.
• It is highly anisotropic and relatively brittle: strong in tension along fibers, weaker in compression and especially across fibers; unlike steel it doesn’t yield ductilely before failure.
• Several note that “stronger than steel” is marketing shorthand: it can beat low‑end steels in specific tensile strength, but not high-strength steels, and only in one direction.

Process, energy use & chemistry

• The process: boil wood in NaOH + Na₂SO₃ for hours to partially remove lignin/hemicellulose, then hot-press at ~5 MPa for many hours to densify.
• People question energy intensity (boiling + long pressing vs arc furnaces) and whether the pulping chemicals can be effectively recovered like in Kraft mills. Environmental impact of sulfite pulping is flagged as a concern.
• There is some confusion over whether resins are added; in the cited research and demos, the product is essentially pure wood with modified structure, not resin-infused composite.

Form factor, joining & workability

• Likely limited to relatively simple, pressed shapes (beams, panels). Complex automotive/airframe geometries would be expensive because you can’t quickly stamp and form it like sheet steel.
• Joining is more like wood (fasteners, adhesives) than steel (welding). That changes joint design and may be a structural limitation.
• Expect drilling/cutting to resemble very dense hardwoods or panzerholz: workable with good tooling but harder on bits, not magical “unmachinable” material.

Applications, cost & markets

• Construction is seen as the natural first market: beams, façade panels, maybe mass-timber‑like systems. Some compare it to CLT, glulam, panzerholz, Lignostone, Masonite.
• Industry voices anticipate it will be much more expensive than existing engineered wood and probably more expensive than steel for structural capacity, making niche, high‑value uses (facades, specialty beams, possibly flooring) more realistic initially.
• Automotive/aviation/space ideas (cars, planes, ships, satellites, machine tools) are floated but most doubt economics and manufacturability there.

Fire, durability, insulation

• Mass timber behavior in fire (charring, retained integrity) is cited as a plus; others point to catastrophic failures of some lightweight engineered wood beams in house fires.
• Long‑term resistance to moisture, swelling, rot, and fungal attack is unclear; the original work required coatings to prevent humidity swelling.
• Densification removes air, probably reducing thermal insulation of members; could increase thermal bridging unless wall systems adapt.

Environment, forestry & skepticism

• Strong interest in carbon benefits vs steel/concrete, but also questions about forestry limits, plantation wood quality, and whether this is truly “green” given chemicals and energy.
• Some highlight extensive prior art in densified wood and similar products that never displaced metals, suggesting cost, anisotropy, and code/regulatory barriers are likely constraints.
• Use of obviously AI/CG imagery on the company site and lack of real‑world structural demos in the article raise suspicions about maturity and over‑hype.

FSRS vs Earlier Algorithms (SM-2 / SuperMemo)

• Many commenters welcome FSRS as a major upgrade over Anki’s old SM‑2: less punishing on lapses, fewer “bursts” of reviews, and better calibration to actual forgetting.
• Some compare FSRS against newer proprietary SuperMemo versions (SM‑17/18); early benchmarks suggest FSRS 6 is at least competitive with SM‑17, but data on SM‑18 is unclear.
• FSRS’s ability to handle off‑schedule reviews and to optimize parameters from a user’s own history is seen as a big practical gain.
• A few people still prefer manual or very simple interval control, arguing the complexity isn’t worth it for them.

Spaced Repetition: Power and Limits

• Strong consensus that SRS is extremely effective for memorization (languages, medicine, stats, APIs, shortcuts, trivia), and can be “transformative” for some.
• Others stress it is not a “silver bullet”: many users burn out, drop off, or misuse it (treating flashcards as primary learning rather than reinforcement).
• Several distinguish memorization from real skill or understanding; SRS is scaffolding, not full learning, especially in math, programming, and language production.
• Motivation and autonomy come up repeatedly: systems optimized for time can be demotivating; people often prefer slower but more enjoyable methods.

Anki: Strengths, Frictions, and UX Complaints

• Anki is praised as the de facto standard: powerful model (notes → templates → cards), extensible add‑ons, solid data portability, and cross‑platform sync.
• Equally strong criticism of its UI and onboarding: confusing concepts (notes vs cards vs decks), rough editor, hard-to-understand scheduling, and punishing backlogs after missed days.
• Power users highlight existing solutions (FSRS presets, daily review caps, “Easy Days,” tags instead of decks, AnkiConnect, CSV import, image occlusion), but many still find the learning curve unreasonably high.

Language Learning and Japanese Focus

• Large subthread on Japanese (WaniKani, Bunpro, kanji SRS, anime/manga motivation). FSRS is suggested as a better scheduler than WaniKani’s bucket system, though integrating it with WaniKani’s gamified unlock model is non‑trivial.
• Experience reports: tens of thousands of vocab items/kanji learned with Anki over years, but also accounts of burnout, huge daily queues, and the gulf between word recognition and real comprehension or speaking.
• Strategies discussed: sentence cards vs single words, “vocabulary mining” from real content, combining SRS with extensive reading/listening, and using SRS only for early vocab or specific subskills (e.g., writing, pitch accent).

Beyond Vocab: Use Cases and Data Models

• Users apply SRS to: exam prep (law, medicine, ham radio), stats and algorithms, shell and editor shortcuts, geography, trivia, people’s names and preferences, metro maps, driving theory, etc.
• Some criticize Anki’s collection/deck model as monolithic and awkward for classroom or multi‑user scenarios; others defend it as flexible when combined with tags, suspension, and CSV‑based updates.

Tooling, Integration, and Card Creation Friction

• Many say card creation and re‑engagement are bigger bottlenecks than the algorithm itself.
• Desired: OS‑level “pipes” from browsers/PDFs/notes into SRS with minimal friction, inbox-style workflows, and better handling of holidays and irregular usage.
• Various tools and workflows are mentioned: browser extensions (Yomitan, asbplayer, subs2srs‑style tools), AnkiConnect, custom scripts that enrich cards with LLM‑generated context or new example sentences.

Next‑Gen Directions: LLMs, Semantics, and Free Recall

• Ideas floated:
  • Use embeddings/semantic similarity to space related cards and avoid overtraining on identical prompts.
  • LLMs to auto-generate or critique cards, grade typed answers, produce varied contexts, or even integrate conversational practice with SRS.
  • Free‑recall modes and interleaving of higher‑level tasks, not just fact recall.
  • Incremental reading–style systems that schedule not only cards but also source texts.
• Concerns include LLM question quality, loss of user autonomy in grading, and risk of training only narrow recall rather than generalization.

Perceived (Il)Legitimate Use Cases

• Many commenters see crypto as overwhelmingly used for crime: drugs, fraud, money laundering, bribery, sanctions evasion, ransomware, child abuse material, murder-for-hire, cartel funds, and terrorist financing.
• Others argue there are “legit” uses: bypassing capital controls (Argentina, Lebanon, Turkey), sending money to relatives or refugees (notably Ukrainian), paying for hosting/VPNs or games from sanctioned countries, porn/kink sites excluded by card networks, and supporting debanked or censored entities (e.g., publishers, activists).
• Disagreement centers on whether “bypassing bad laws” is morally legitimate or simply lawbreaking; some equate it to money laundering in principle.

Sanctions, Capital Controls & Authoritarian Regimes

• Crypto is described as a tool to sidestep punitive FX regimes and dual exchange rates, avoiding official conversion at bad rates and bans on outbound hard currency.
• Critics counter that the same rails empower kleptocrats and sanctioned states, making oppressive regimes more resilient and facilitating theft at scale.

Regulation, Enforcement & Consumer Protection

• Consensus that the protocol layer is hard to regulate; debate focuses on regulating exchanges and fiat on/off-ramps via KYC/AML and sanctions.
• Irreversible, pseudonymous transfers are seen as structurally favorable to scams and kidnapping/ransom, compared to bank-based systems with in-person checks and chargebacks.
• Some insist that safeguards like banks and refunds are hard-won consumer protections; crypto discards them to society’s detriment.

Speculation, Returns & Social Harm

• Speculation is defended by some as a legitimate use or entertainment (akin to casinos, horse racing).
• Others argue current crypto gains are mostly from “fleecing rubes,” enabled by hype and weak regulation.
• Debate over whether crypto’s price increases represent inflation hedge, speculative bubble, or “inflation” via proliferation of new coins.

Centralization vs Censorship-Resistance

• Pro-crypto voices emphasize escaping centralized gatekeepers (banks, card networks, Stripe) that can deplatform lawful but disfavored speech or commerce.
• Critics note practical centralization: most activity is off-chain inside exchanges; stablecoins like USDT can freeze accounts; big platforms can and do block users.

Energy & Technical Debates

• Concern over combining energy-intensive AI with crypto; critics see much AI/crypto usage as waste.
• Defenders stress that many newer chains use proof-of-stake, arguing that energy critiques aimed at all crypto are outdated, though Bitcoin remains a major PoW user.

Ideological Evolution & Culture

• Several see a shift from early cypherpunk/techno-anarchist ideals (freedom from banks and states) to today’s landscape of hedge funds, “finance bros,” and billionaires seeking to escape regulation and taxes.
• Some argue this trajectory was inherent in the technology’s goal of being “unstoppable”: once you remove legal constraints, fraudsters and criminals logically dominate.
• Others frame it as a broader pattern: builders create tools, then redistributors/financial interests capture the narrative and extract value.

AI, Agents & New Use-Case Proposals

• One thread proposes using crypto (e.g., USDC on fast PoS chains) as a universal, transferable payment layer between AI agents and services, with dynamic pricing based on demand.
• Pushback: such systems don’t require blockchains; centralized credits are simpler, give users recourse, and align with platform incentives. Many see no compelling reason for platforms to adopt open, token-based payments.

Macro-Political & Systemic Risks

• Some speculate about crypto’s role under a Trump administration: wealth extraction from the US economy, possible “crypto-equivalence” for US debt, and eventual opaque bailouts if losses become systemic.
• Others doubt there will be bailouts; they see the system designed to push losses onto the masses while insiders rotate into new tokens.
• Concerns raised about civil unrest as inequality, scams, and climate impacts (e.g., Florida real estate in a warming world) intersect with crypto-driven wealth shifts.

Overall Reaction to the Tool

• Many commenters find the HN chat interface technically impressive, fun to play with, and surprisingly insightful about users, topics, and trends.
• People enjoyed examples like: “best database according to HN”, “best time to post Show HN”, language popularity stats, retirement-number analysis, and user-behavior summaries.
• Some hit the free usage limit quickly and wanted more to explore, such as pre-generated/browsable analyses or blog-style writeups of interesting queries.

UX, Access, and Pricing

• Several complaints about friction: mandatory email/login, confusing redirects, wrong URL in the submission, and difficulty seeing the HN dataset at first.
• Multiple users say they won’t give their email “just to try it”; suggestions include captchas instead of logins and showing value before signup.
• Common request: let users plug in their own OpenAI/Claude keys or some “Login with ChatGPT”–style billing to avoid another subscription.
• The creator notes that LLM costs and the need to avoid abuse drive the login wall and pricing, and that the app is roughly break-even.

Use of HN Data, Copyright, and Rights

• Ongoing debate about whether it’s appropriate to monetize analyses of HN comments:
  • One side: HN is public; the data is in a public BigQuery dataset and via API; anything public can be analyzed.
  • Other side: commenters retain copyright; HN only has a license; third parties don’t automatically gain commercial rights just because there’s an API or dataset.
• The BigQuery listing that appears “official” is clarified (via linked prior discussion) as a third-party project, not something HN/Y Combinator publishes directly.
• Some find it especially distasteful that their own contributions are turned into a paid product “sold back” to them.

Privacy, Anonymity, and Doxing Concerns

• Strong unease about prompts like “What do you think about user X?” and how easily the tool (or other LLMs) can:
  • Aggregate a user’s entire history,
  • Infer real-world identity or other accounts,
  • “Dox” people or link throwaways via writing style.
• Several say this makes them reconsider posting at all; others argue that the damage is already done because of past scraping and datasets.
• Distinction is made between public records and impersonation: commenters broadly see AI (or humans) role-playing as real individuals as ethically unacceptable.
• Some propose a convention like “NoAI/NoIndex” in profiles as a soft opt-out signal, while acknowledging it wouldn’t be enforceable.

Technical Aspects and Safety

• People praise the multi-tool setup (SQL runner, Python transform, charting, search) and how well it orchestrates queries and visualizations.
• There’s curiosity about safeguards that prevent destructive SQL (e.g., DELETE), with speculation that the database is read-only plus prompt- or tool-level restrictions.

Language Popularity & HN Bias

• The tool’s outputs suggest Rust and Go dominate by story count and karma, while Lua/Erlang have high per-story scores.
• Follow-up queries on Show HN titles show Python, JavaScript, Go, and Rust leading by project count.
• Commenters note:
  • Title-bias (Rust/Go often mentioned in titles),
  • Possible undercounting (e.g., TypeScript, Lisp) due to regex-based detection,
  • That HN “attention” doesn’t necessarily reflect real-world usage.
• Some perceive a systemic Rust bias on HN and speculate that YC/startup culture amplifies it.

Ethical Discomfort with AI Over Social Data

• Multiple users express a general “gross” or “icky” feeling about:
  • AI systems mining social conversations for fine-grained judgment of individuals,
  • Normalizing surveillance-like analysis of casual, in-the-moment discussion.
• Others counter that public forums are inherently public, but even they acknowledge the emotional shock of seeing an LLM instantly surface and summarize one’s entire online persona.

Mentoring, Juniors, and Mutual Learning

• Many commenters describe deep enjoyment in mentoring juniors: asking “what are you working on?” often reveals dead ends, which become rich teaching moments.
• Mentorship is framed as symbiotic: juniors gain confidence to question decisions; seniors are forced to articulate and re‑examine their own habits.
• Several argue this applies to seniors too: experienced people also wander down bad paths and benefit from peer conversations.
• There’s frustration about industry reluctance to invest in juniors (“they might leave”), which some see as backward: preferring low‑skill, low‑mobility staff.

Informal vs Structured Knowledge Transfer

• Strong disagreement on the article’s swipe at “water-cooler” learning:
  • One camp: relying on chance hallway chats is irresponsible; written, reusable answers (pre‑pivot Stack Overflow style, documentation, blogs) scale expert time far better.
  • Another camp: informal, unguided interaction conveys mindset, culture, tacit patterns, and “links between concepts” that formal material never captures.
• Consensus trend: it’s not either/or. Formal processes raise the floor; informal contact raises the ceiling.

Remote Work, Pairing, and Tools

• Some claim remote work weakens novice learning by removing spontaneous “what are you working on?” moments; screen sharing is useful but a strict subset of in‑person interaction.
• Others counter that in open offices most communication was already via chat; pings are actually easier and less intrusive than walking over.
• Pair programming emerges as a concrete practice that matches the article’s advice: novice drives, expert advises; works well even remotely.

Exploration, Debugging, and Niche Work

• Examples from mechanics and programming highlight how subtle tricks and shortcuts aren’t obvious from manuals or APIs; they’re discovered or observed.
• Several celebrate debugging and untangling legacy or niche systems as a joyful, puzzle‑like path to rapid expertise—though some warn it can turn into career‑long drudgery if you become the only person willing to touch painful systems.
• Learning by live exploration (good debuggers, REPLs, Smalltalk/Lisp environments) is contrasted with modern ecosystems that feel more opaque.

Nature of Expertise and Career Strategy

• Debate over domain specificity: some see expertise as tightly bound to a domain; others argue that meta‑skills and patterns transfer well, and domain knowledge is comparatively easy to acquire.
• Commenters note tacit/“ineffable” knowledge that isn’t in official documents and is hard for current AI or rule‑based systems to capture.
• A few criticize the binary “expert vs novice” framing, preferring a continuum and distinguishing practitioner skill from educator skill; being great at both is seen as extremely rare.
• Career advice appears: specialize in new or neglected niches (e.g., emerging fields, unglamorous systems) to advance quickly, since everyone starts as a novice there.

Climate Change, Fatalism, and Global EV Momentum

• Some see climate catastrophe as effectively locked in and view legacy automakers’ resistance as expected but tragic.
• Others counter with cautious optimism that large-scale EV and renewables adoption (especially driven by China) can still meaningfully reduce harm, even if not “solve” climate change.

China’s EV Dominance and Trade Barriers

• Multiple comments argue Chinese EVs and batteries are already cheaper and better, and that blocking them mostly protects high US prices and incumbent behavior.
• Others warn offshoring and reliance on China undermine US manufacturing capacity and national security; they see “cheap imports” as having devastated many US communities.
• There is tension between wanting low-cost Chinese EVs and fearing strategic dependence on a geopolitical rival.

US Manufacturing, Labor, and Immigration

• Debate over whether manufacturing jobs can or should “come back”:
  • One side: automation and worker preferences mean we should focus on living wages, unions, and universal benefits rather than nostalgic factory jobs.
  • Other side: dismissing manufacturing harms rural and non-metro areas, contributing to social crises (e.g., opioids).
• Repeated point: many hard physical jobs (construction, agriculture, meat-packing) are filled by immigrants; Americans generally avoid them at current wages.

Consumer Preferences and Car Prices

• Some say typical buyers want simple, affordable ICE vehicles (2010s-style sedans/SUVs) with familiar engines.
• Others say mainstream buyers care more about comfort tech (CarPlay, heated seats, safety) than about engine type.
• Wide frustration with rising new and used car prices; several people explicitly want cheap Chinese EVs to apply price pressure.

California’s Mandate, Federalism, and GM’s Position

• GM’s push for a single national standard is seen by many as an attempt to override California’s stricter rules for corporate convenience.
• Disagreement over whether state-by-state environmental regulation is “silly” in a single national market or a core feature of US federalism.
• Some expect court and congressional efforts (backed by automakers and swing-state politics) to weaken or reverse California’s authority.

Mandates vs Taxes and Road Funding

• Strong thread arguing mandates are clumsy; better tools would be:
  • Increasing fuel or carbon taxes (on fuel or ICE vehicles) to shift demand.
  • Designing excise/registration schemes that heavily penalize new ICE sales while avoiding retroactive punishment of existing owners.
• Others note gas taxes finance roads; as EVs grow, both tax-based and mandate-based transitions must confront how to fund infrastructure.
• Cap-and-trade and EV-specific fees are mentioned, but there’s no consensus on the “right” mechanism.

EV Infrastructure and Practical Barriers

• Apartment dwellers and small-town residents are highlighted as edge cases: lack of home charging, limited building electrical capacity, and slow public charging make EV-only mandates feel premature.
• Some argue 120V/Level 1 charging would cover most daily needs; others point out the cost and complexity of retrofitting older buildings and upgrading grid connections.

Unions, Jobs, and Political Constraints

• EVs and PHEVs use fewer parts and more automation, threatening unionized assembly jobs.
• Several commenters argue national politicians (both parties) will prioritize UAW/Teamsters and Midwestern jobs over aggressive EV policies, regardless of climate goals.
• One commenter frames a stark tradeoff in the US context: if forced to choose, many will back unions and legacy jobs over rapid EV disruption.

Automaker Strategy and Historical Parallels

• Multiple comments compare current US EV resistance to 1970s US automakers’ slow response to emissions and fuel-efficiency rules, which opened the door to Japanese competition.
• China’s EV surge (and, in other markets, the rise of Chinese brands) is seen as a potential repeat: US firms lobbying instead of innovating may get “crushed” when protection weakens.
• Some expect GM and peers to be bailed out again rather than allowed to fail, reinforcing their incentive to fight mandates instead of building compelling, affordable EVs.

Model access, safety & format

• Commenters initially struggled to find “open source” materials; others linked the Hugging Face repo with weights.
• One checkpoint file is flagged as unsafe by scanners, triggering concern about malware via .pth / pickle-based checkpoints.
• Several argue this is likely a false positive but advise caution and advocate for safetensors and diffusers formats as industry standards.
• A diffusers conversion is already available, and at least one web UI (SD.Next dev branch) supports the model.

Quality, artifacts & capabilities

• Testers report visually impressive results, but with clear temporal artifacts: hair flicker, disappearing details, clothing glitches, and limited actual motion beyond simple pans and limb movements.
• Some examples are criticized for obvious glitches even in showcase clips.
• The underlying Wan2.1-14B base leads to questions about frame rate (e.g., whether it’s locked to 16 fps).
• Paper notes training on 2–8 second clips at 720p; one user wants head‑to‑head comparisons against FramePack for longer 2D sequences.
• Unclear whether the model can maintain a consistent character across multiple scenes and angles, a known weak spot of current gen.

Naming, branding & web infrastructure

• The “AniSora” name is widely assumed to be playing off OpenAI’s Sora; others point out “sora” is a common Japanese word/name.
• Some note OpenAI’s sora.com now redirects to a subdomain, leading to side-discussion about cookies, cross‑domain auth, and ad‑tech.

Copyright, training data & legality

• Many assume the model is trained on copyrighted anime, manga, webtoons, and Pixiv-style art.
• Debate centers on whether Bilibili’s distribution licenses imply any right to train models; some say it’s analogous to Crunchyroll releasing a model and being pressured by licensors; others argue “China doesn’t care about licenses.”
• Broader point: almost all major models (including Western ones) are suspected of using copyrighted material; precedents (e.g., Meta’s book data) are cited.
• Several note that the legal “right to train” is unresolved; enforcement is seen as effectively “pay to play” favoring large firms.

Impact on artists, copyright theory & “what is art?”

• Long, nuanced debate compares visual artists to translators: both transform prior works/inputs, but artist outputs are clearly copyrighted; translators’ status and creativity are contested.
• One side argues:
  • AI training consumes huge corpora of protected work and directly undermines illustrators, especially commercial ones (gacha art, light novel covers, etc.).
  • Mass AI use risks collapsing markets, reducing incentives for new styles, and flooding the web with low-quality “AI slop.”
• Others respond:
  • All creativity is derivative; humans are also trained on massive “datasets” of lived experience and prior art.
  • Copyright is already messy and overextended; some advocate reducing or even abandoning it, or redefining derivative use for models.
  • The real harm is not exposure to copyrighted work, but models that can reproduce specific works or identifiable individual styles at scale; technical solutions to avoid memorization are proposed.
• There’s disagreement on whether AI outputs can be “art”:
  • Some insist art requires human intent, expression, and a personal creative journey.
  • Others say if AI-generated work successfully evokes complex impressions and is shaped by human direction, it functionally is art; tools don’t negate artistry.
• A common prediction: AI devastates the “bottom half” of commercial work (cheap illustration, junior roles, penny‑dreadful novels), while high‑end or deeply personal art remains but becomes more niche and/or luxury‑like.

Anime industry & content ecosystem

• Several see this as enabling “infinite anime” (fan continuations, AMVs, fan seasons for series like Haruhi or Solo Leveling), and empowering small teams/indies.
• Others fear an overwhelming influx of low‑effort AI anime, worsening already‑perceived quality decline and making high‑effort shows harder to find.
• People note that animation has always been cost‑driven: past shifts (xerox vs inking, Flash-era TV, 3D shortcuts) already traded style for efficiency.
• A Toei Animation report is cited: they plan AI for storyboards, color specification/correction, in‑betweening, and backgrounds—suggesting mainstream studios will adopt AI as a production aid rather than full replacement, at least initially.
• Some argue audiences already tolerate “sloppy” visuals when writing is strong (e.g., low‑frame shows, simple-looking series), so they may accept mild artifacts for more content; others say jarring AI in‑betweens in a beloved show would be infuriating.

Artist livelihoods, future of work & culture

• Multiple posts express sympathy for illustrators whose work is being scraped to train models that then undercut their commissions and studio jobs.
• Comparisons are drawn to translators and musicians: machine assistance and streaming have driven down rates and made full‑time creative careers rarer, even as overall output volume rose.
• One prominent theme: we risk a world of abundant personalized media but fewer shared cultural touchstones (everyone watching unique AI‑tailored “Frozen‑like” content instead of the same show), weakening art’s social role.
• Others counter with economic analogies (furniture, custom cars): mass‑produced media and a smaller “hand‑made” sector can coexist, with human‑made work becoming a premium status good, potentially authenticated by cryptographic “100% human” labels.

Legal status of outputs

• A US Copyright Office bulletin is referenced: generative AI outputs are only copyrightable where a human “determined sufficient expressive elements.”
• This raises concern that AI‑generated shows might be weakly protected: if courts see them as primarily machine‑authored, anyone could freely copy or remix them, undermining monetization.

Motivations & demand

• Some ask “who needs this?” and view it as pointless or creepy compared to human animation.
• Counterarguments:
  • Huge unmet global demand for anime‑style content; East Asian studios can’t meet it at current price points.
  • AI anime could break what’s seen as an “East Asian monopoly” on the style and respond to skewed supply‑demand dynamics (e.g., doujinshi scarcity, scalping).
  • Faster production cycles for sequels and adaptations are seen as a major draw for fans.

User experience & access

• Several users report the web demo or associated tools:
  • Some say it’s free and works well.
  • Others encounter build failures, errors while consuming credits, or are annoyed by Google login and hidden account requirements for uploads.
  • One alternative site (anisora.ai) is recommended as working smoothly.
• There’s also curiosity (and expectation) that the model can/will be used for hentai or explicit content, given perceived weaker guardrails in some Chinese AI services; no definitive answer is shared.

Alleged antisemitism vs criticism of Israel

• Some commenters ask what specific “unsafe antisemitic actions” justify federal defunding, suggesting the real issue is Harvard not crushing Gaza-related protests.
• A lawsuit by Jewish students is cited, alleging a hostile environment, administrative inaction, double standards, and faculty rhetoric; others stress that allegations are not evidence and note the complaint’s charged political tone.
• Major disagreement over whether campus protests are primarily anti-Israel or antisemitic:
  • One side says anti-Zionism is inherently eliminationist and bigoted, since it targets the existence of the only Jewish state and often includes calls for violence.
  • The other side argues anti-Zionism can be purely political, focused on Israeli government actions; conflating it with antisemitism risks chilling legitimate criticism of Israel.
• Several comments highlight that any explicit threats or hate should be punished, but that feeling threatened by criticism of Israel is not itself proof of antisemitism.

Legality and motive of federal defunding

• Multiple participants see the funding cutoff as political retaliation by the administration, using federal agencies to coerce Harvard’s speech and policies.
• Linked analysis characterizes the move as likely illegal and dangerous for rule of law, even for those who dislike Harvard.

Impact on research and alternative funding

• Concern that vital programs (e.g., Undiagnosed Diseases Network) may collapse, harming patients with rare diseases; some call this “abject evil” over a campus culture war.
• One view: universities long knew federal funds come with strings; if research is truly valuable, private donors, state governments, or foreign governments can replace the money.
• Others counter that much basic research has no direct ROI and exists largely because of federal funding; alternatives are hand-waved rather than concrete.

Harvard’s endowment and tax status

• The $52B tax-exempt endowment sparks debate:
  • Critics call it a “tax dodge,” questioning high executive pay and whether “student aid” mostly offsets Harvard’s own high tuition.
  • Defenders emphasize nonprofit rules, education as a public good, restricted vs unrestricted funds, and note that this structure is standard for universities globally.
• Some argue Harvard should use its endowment to buffer defunding; others stress most funds are restricted, though Harvard still has large unrestricted assets.

Broader political and cultural context

• Several comments frame this as part of a wider right-wing campaign against universities, minority rights, and dissent, with progressives juggling many urgent issues.
• A final thread notes that conservatives often tolerate ideological differences to gain power, while liberals fracture over them—seen as contributing to current institutional vulnerabilities.

Why LLMs May Outperform Humans at Persuasion

• LLMs can recall and recombine huge amounts of “factual-sounding” content, making their answers seem researched and authoritative compared to short, bare human replies.
• They don’t get tired, will respond to every point in a gish-gallop, and can mirror the interlocutor’s tone and style, which helps with rapport.
• They’re trained on vast corpora full of persuasive language (marketing, scams, bullying, debate material), giving them a rich library of tactics.
• Their strength is “shallow but extremely wide” search: rapidly exploring wording and framing that satisfy many small constraints.

Hallucination, Lying, and RLHF

• Commenters stress that LLMs smoothly fabricate details to make arguments look stronger; bad math proofs and fake “facts” can look airtight until inspected closely.
• Some models hallucinate less than others, but benchmarks show trade-offs between capability and hallucination rates.
• A key criticism: RLHF / “human preference” tuning rewards outputs people like, not truth. A lie that isn’t recognized as a lie is often preferred, effectively optimizing for undetectable deception.
• This makes LLMs “bad tools” in an engineering sense: they fail silently and confidently, instead of flagging uncertainty.

Human vs LLM Communication Styles

• Examples (like defining a stack) show humans arguing over minutiae, misreading, or hair-splitting logic structures. Some see this as necessary precision; others say it’s why people prefer LLMs’ smoother answers.
• Several anecdotes compare LLMs to skilled human bullshitters who care only about being convincing, not about truth.

Debate Culture, Gish Gallop, and Datasets

• High-school/college debate practices (spreading: ultra-fast delivery of many arguments, gish-gallop tactics) are cited as analogous to LLM persuasion.
• Debate incentives reward volume of arguments and penalize ignoring even absurd claims, distorting debate away from clarity or audience understanding.
• A large open debate-argument dataset derived from this culture is being used to train/evaluate LLMs, arguably reinforcing these tactics.

Experimental Design and Word Count

• One close reading of the paper notes LLM advice messages were over twice as long as human ones. Word count may explain much of the persuasive gap.
• Some suggest rerunning the experiment with controlled lengths or instructing humans to write longer, to see if LLMs still win.
• Others note that longer outputs also reduce hallucinations, and that humans underestimate how much sheer length biases perceived rigor.

Social, Political, and Commercial Implications

• Many are worried about mass persuasion: targeted political messaging, subtle advertising, and manipulation on social platforms.
• Fears include young users over-trusting “magic oracles” and the prospect of chatbots that quietly embed product pushes into otherwise helpful advice.
• Some propose personal “loyal” models to critique incoming persuasive content—leading to the image of LLMs arguing with other LLMs on our behalf.
• Commenters expect political campaigns and advertisers to adopt such systems aggressively; some joke that salespeople, not programmers, should be most worried about replacement.

Broader AI Trajectory and Labor

• One camp anticipates rapid upheaval: any value delivered via digital interfaces (especially knowledge work and persuasion-heavy roles) is vulnerable, with robotics following later.
• Another camp is skeptical: hallucinations and legal liability limit real deployment; current productivity gains feel closer to autocomplete than revolution.
• There’s debate over whether we’re heading toward a “weak singularity” (recursive improvement, end of scarcity) or just another overhyped tech wave.

Archiving and meta-discussion

• Some question linking via archive.is when the blog has no paywall; others argue archiving protects against link rot, traffic spikes, geo-blocking, and preserves the article’s state during discussion.
• Several note HN had an early, technically sound comment debunking the original “universe decays in 10⁷⁸ years” result that was initially downvoted, used as evidence that audiences prefer sensational “breakthroughs” over skeptics.

Knowledge silos, expertise, and accessibility

• One view: the episode shows damaging knowledge silos and failures of adjacent-field communication.
• Counterview: relevant knowledge (timelike Killing fields, QFT in curved spacetime) is standard and on arXiv; the scientific process did work—other physicists quickly published a rebuttal.
• A recurring theme is that cutting-edge QFT/GR is accessible only to a tiny fraction of people; explanations pitched too technically for HN are hard to evaluate, yet oversimplification breeds misunderstandings.

Hawking radiation, Unruh effect, and the criticized claim

• Multiple comments stress that the popular “virtual particle pair, one falls in” story is a heuristic; the real Hawking effect comes from mode-mixing of quantum fields in curved spacetime near horizons.
• Unruh effect (accelerated observers seeing thermal radiation) is raised as an intuitive bridge, with clarifications about proper acceleration and different types of horizons.
• Baez’s core point, echoed by others: for static, globally hyperbolic spacetimes with a global timelike Killing field (like an isolated “dead” star), standard results say no Hawking radiation; claiming otherwise is extraordinary and should have triggered expert consultation.

Baryon number and theoretical stakes

• Some argue Baez overstates how “shocking” baryon-number violation would be, citing existing expectations that black hole evaporation can violate baryon number.
• Others reply: the paper under fire implies baryon violation for ordinary collapsed stars (without black holes), which is qualitatively more extreme.
• Experimental limits on proton decay and nonperturbative SM processes are mentioned to show that baryon violation is tightly constrained and context-dependent.

Black holes, horizons, and information

• Long subthread debates whether infalling observers “really” cross the horizon versus asymptotically approach it, the role of coordinate choices, and how to reconcile outside vs infalling viewpoints.
• Standard GR picture (using Kruskal–Szekeres, Eddington–Finkelstein) is defended: locally, nothing special at the horizon for large black holes; tidal forces and the singularity are the real killers.
• Others propose more speculative ideas (horizons as dimensional reduction surfaces, maybe no interior/singularity at all), which are met with skepticism and requests for consistency with mainstream GR/QFT.

Journalism, peer review, and misinformation

• Many see the real institutional failure not in “academia in general” but specifically in the journal (Phys. Rev. Lett.) publishing a paper outside reviewers’ expertise.
• Several argue science journalists should have emailed multiple experts before amplifying such an outlier claim; others caution that “ask the experts” must be framed as context-seeking, not blind deference.
• Broader concern: science now visibly suffers from hype cycles and misreporting; to non-experts, genuine disputes and corrections can look like politics, undermining trust.

Title and communication style

• Physicists and astronomers note the blog title “Dead Stars Don’t Radiate” is technically misleading: white dwarfs and neutron stars certainly radiate thermally; the intended meaning is “no Hawking-like radiation from non–black holes.”
• Some call this mild clickbait; others see it as deliberate provocation aimed at a technically literate audience, redeemed by the detailed, well-argued content.