How Trust Cue rated them

• Subject depth Partly

  Claims like 'taste will be scarce' and the math-versus-genomics analogy are substantive starting points, but lack citations, worked examples, or data that would deepen them—though replies on validation pipelines and credit attribution show the capacity for deeper reasoning.

  Does the account move beyond surface takes on AI+science hype, engaging substantively with cost structures, validation pipelines, and the mechanics of how scien

  Quoted from public posts on X

  • AI is disruptive to knowledge work because it separates effort, quality, and taste.
  • Math may be a misleading test case because: - It's causally simple. Established rules always apply as long as pre-condit
• Original framing Partly

  The effort–quality–taste separation framework and computational biology comparison are genuinely novel framing for AI's impact on knowledge work, though they're often presented as aphorisms rather than developed arguments.

  Does the account add novel framing (e.g., 'effort/quality/taste separation,' industrial revolution analogy for math) rather than repeating consensus hot-takes a

  Quoted from public posts on X

  • But once we spend down the supply of preselected problems, taste for interesting problems will be the scarce resource.
  • Math is in a moment similar to biology shortly after the sequencing of the human genome where computational biology beca
• Sticks to the facts Partly

  The account updates publicly from skeptic to impressed (notably citing advancements without mechanism), and explicitly commits to tracking evidence. The update itself lacks specificity, but the stated commitment to evidence-tracking is genuine.

  Are claims about AI's limits proportionate to current evidence? Does the account update when data improves (as this one does) without flip-flopping on core reas

  Quoted from public posts on X

  • I've consistently argued that beliefs about AI should closely track the *current* evidence, which inherently implies I w
  • I've been a skeptic in the past but this is a genuinely amazing set of advancements. I'm officially very impressed.
• Upfront about their stake Strong

  No monetization, product shilling, or status-defense signals detected. Posts balance enthusiasm for AI capability with skepticism of hype, and engage substantively on validation pipelines and scientific integrity—ruling out shill or tribal-defensive patterns.

  Is the account motivated by understanding scientific truth and cost reduction, or by defending credentialist hierarchies and protecting academic status from per

  Quoted from public posts on X

  • I'm an AI *hype* skeptic. I think they're useful, and even revolutionary, just nowhere near end-of-the-human-race or eve
• Who engages with them Partly

  Engages with substantive repliers like Kevin Roose (NYT tech, 173k followers) and Judea Pearl, though most network engagement is with smaller accounts. References are specific (e.g., Terry Tao on coordination) but not always elaborated.

  Does the account engage respectfully with domain experts (Judea Pearl, Kevin Roose, Terry Tao references) and cite specific limitations rather than make univers

  Quoted from public posts on X

  • Good to see you, Judea.
  • I've been pissing off my fellow shape rotators for years saying math and physics have simple causal structure (compared