It's the “hardware”, stupid

AI hardware needs real user problems to solve

  • Many commenters argue current “AI devices” don’t do anything a smartphone can’t already do more easily.
  • These gadgets are seen as solutions in search of a problem, primarily motivated by new revenue streams and data collection rather than user needs.
  • Devices that are just thin clients calling cloud APIs are compared to generic SBCs; nothing fundamentally new or compelling.

Online vs offline AI and the “doomsday oracle”

  • Cloud‑dependent AI hardware is seen as uninteresting; truly novel devices would run useful models offline.
  • A niche, imaginative idea: a solar‑powered, fully offline AI box that preserves the knowledge to rebuild civilization.
  • Others counter this fails the “toothbrush test” (not used daily) and is only realistically for hobbyists or doomsday preppers.

Platform and OS constraints (Android, etc.)

  • Some find it noteworthy that an OpenAI device would likely depend on Android while competing with Google. Others see this as normal, like many vendors using Android today.
  • A suggestion to “feed Android into an LLM and redesign it” is mocked as unrealistic at current scales.
  • Brief side note: question why not use something like Fuchsia + Android compatibility instead.

Hardware vs software culture

  • Several posts stress that good hardware is meaningless without excellent software and UX.
  • Traditional hardware companies are accused of treating software as a BOM line item instead of a value‑creating ecosystem.
  • Nvidia and Apple are cited as counterexamples where strong software stacks make hardware far more valuable.

Why the iPhone succeeded (and what AI devices are missing)

  • Disagreement with the article’s claim that iPhone success was “not about design.”
  • One camp: iPhone won by bundling core daily functions (phone, internet, music, maps) into one device that actually worked well.
  • Another camp: many phones already did that; what set iPhone apart was polish—fluid touch UI, a real browser, big screen, and coherent design/branding.
  • The pivotal insight: it was a general‑purpose pocket computer that happened to make calls, not a “phone with extras.”

AR glasses, Vision Pro, and form factors

  • Some see glasses as the most plausible future AI form factor: socially familiar, always‑on display, directional sensing.
  • Others recall Google Glass backlash (privacy, “creep‑shotting”) and worry about normalized “panopticon glasses.”
  • Vision Pro is viewed as technically impressive but misaligned with real problems: high cost, comfort issues, walled garden, and limited standalone computing.

Design leadership, Jobs/Ive, and OpenAI hardware hopes

  • There’s debate over how much of the iPhone’s magic was Jony Ive’s design vs. Steve Jobs’ product “taste.”
  • Several argue success was highly contextual—a unique combination of people, timing, and ecosystem; replicating that with an AI device is unlikely.
  • Some are cautiously optimistic about the Ive–OpenAI collaboration but others are skeptical, especially given moves toward advertising in AI products.

Is the smartphone the “endgame”?

  • One side echoes the article’s line that “reinventing AI = reinventing the smartphone,” implying AI hardware must replace phones to matter.
  • Others push back: people routinely carry tablets, books, cameras, notebooks in addition to phones; new AI devices can coexist rather than replace.
  • AI is already succeeding via existing devices, and Apple is seen as struggling to tie AI meaningfully to hardware because most value is cloud‑based.

Miscellaneous tangents

  • Debate over whether Raspberry Pis are “boring” overkill versus uniquely useful small Linux + GPIO machines.
  • Idea of an audio‑only, server‑driven AI “terminal” (just mic + speaker) is criticized as deeply limiting for work, reading, media, and privacy.
  • Some complain that tightly locked‑down hardware prevents third parties from building the novel experiences that might actually make new AI devices worthwhile.