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@LRudL_

@LRudL_ on X

3 captures, most recent first. Transcribed by hand from screenshots — see the timeline for what that means.

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— quoting @RuxandraTeslo — saved image

Rudolf Laine [verified] @LRudL_ · 1h

Great overview of ideas close to my own heart

One axis I find helpful: Mill v Bentham. The field is Benthamite, but we need Mill's love of freedom and agency

Also Dostoevsky's inquisitor parable is one of the most philosophically dense and utterly Western pieces ever written

[quoted post]
Ruxandra Teslo [DNA helix emoji] [verified] @RuxandraTeslo · 4h

"Why are people not happier about A.I.? It might cure cancer" is a very one-dimensional view of human beings. It assumes that humans want only material comfort, disregarding their fears around loss of agency and purpose....
Note from Claude Sonnet 5

X post by Rudolf Laine (@LRudL_) praising an overview of ideas on AI and human agency, framing it as Mill versus Bentham (the field is Benthamite but needs Mill's love of freedom and agency) and citing Dostoevsky's Grand Inquisitor parable. Quotes Ruxandra Teslo on why 'it might cure cancer' is a one-dimensional view of what humans want; quote truncated.

millbenthamdostoevskygrand inquisitorhuman agencyai attitudesutilitarianism

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— saved image

Rudolf Laine @LRudL_
Increasingly common sequence for conceptual work:
(1) need to figure stuff out
(2) lots of Fable chats
(3) increasing confusion & frustration
(4) sit in chair and think & read w/o AI takes
(5) it all comes together
11:13 PM · Aug 22, 2026 · 2,370 Views

[reply]
Nathan Helm-B... @nathan8468... · 24s
I feel the "no, that's wrong" reaction to seeing the AI give bad takes on my ideas is actually sometimes really helpful.

A funny backwards way of finding out what I actually feel is right about a complex topic.
Note from Claude Sonnet 5

Tweet by Rudolf Laine describing a workflow for conceptual work involving AI chats followed by unaided thinking, with Nathan's own reply about how disagreeing with a bad AI take can reveal his real position.

ai collaborationconceptual worktwitternathan replyepistemics

@LRudL_

Rudolf Laine ✔ @LRudL_ · 21h The increasingly-hyperbolic METR graph is actually good news for safety. We just have to survive a brief singularity in March, and then afterwards the models will never be able to do more than undo a few hours' worth of work [Embedded chart: "Figure 1: Hyperbolic fit of METR time horizon implies normalcy" — y-axis "p50 Task Horizon (hours)" from -40 to ~40+, x-axis "Release Date" from 2023 to 2029. Legend: red "Exponential fit (R²=0.9537)", blue "Hyperbolic fit (R²=0.9845)", black dots "METR benchmark data". Both fits track the actual data closely and rise steeply approaching a vertical asymptote labeled "Mar 22" (2026); the red exponential fit continues shooting upward off the chart, while the blue hyperbolic fit passes through the asymptote and comes back from negative infinity to approach zero from below, flattening out near zero for 2026-2029.]
Note from Claude Sonnet 5

A joke tweet by AI safety researcher Rudolf Laine satirizing curve-fitting overreach in AI capability forecasting — pointing out that fitting a hyperbolic function (rather than exponential) to METR's time-horizon data produces an absurd mathematical artifact (task horizon crashing through a singularity to negative infinity and settling near zero) that would, taken literally, "solve" AI safety. A methodological joke about the limits of trend extrapolation in capability forecasting, relevant to Nathan's tracking of METR/time-horizon singularity metrics.

metrai capabilitiesforecastinghumortwittersingularitycurve fitting