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The Impossibility of Supersized Machines (2017)

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The Impossibility of Supersized Machines (2017)
TL;DR · WeSearch summary

The paper 'On the Impossibility of Supersized Machines' argues that machines cannot exceed human size, despite speculation by some experts in computer science, philosophy, and physics. The authors present seven distinct arguments to demonstrate that such growth is not merely unlikely but fundamentally impossible. The work was published as a nine-page academic paper with two figures in the arXiv repository in March 2017.

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arXiv.org
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Record

Original publisherarXiv.org
Canonical URLhttps://arxiv.org/abs/1703.10987
Publication timeSat, 16 May 2026 20:28:56 +0000
Retrieval time2026-05-16T20:40:19.047Z
Last seen2026-05-16T20:40:19.047Z
Headline sourcePublisher (no WeSearch rewrite)
Excerpt sourcepublisher body
Excerpt methodFirst ~120 words (~800 chars) of extracted publisher body, fair-use limited.
SummaryWeSearch · cerebras-chat (WeSearch summarizer)
Summary source textcontentText
Citation coverageSummary is a WeSearch-generated derivative; primary citation is the original publisher URL.
ClusterV0prdshIzbSX
Cluster logicGrouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison.
Ranking reasonStory pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking.
Publisher visitYes — open original
Substitutes article?No — link-out required for full text

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WeSearch declared handling (basis: Derived from the published RSS/Atom feed). This is WeSearch policy, not a legal grant on the publisher's behalf.
Unknown
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Snippet May a short excerpt of the publisher's text be shown? Allowed
AI summary May WeSearch generate its own short summary of the article? Limited
Retrieval / RAG May the content be exposed for third-party retrieval-augmented generation? Not asserted
Model training May the content be used to train AI models? Not asserted
Commercial reuse May the content be reused commercially? Not permitted

Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.

Opening excerpt (first ~120 words) tap to expand

Computer Science > Computers and Society arXiv:1703.10987 (cs) [Submitted on 31 Mar 2017] Title:On the Impossibility of Supersized Machines Authors:Ben Garfinkel, Miles Brundage, Daniel Filan, Carrick Flynn, Jelena Luketina, Michael Page, Anders Sandberg, Andrew Snyder-Beattie, Max Tegmark View a PDF of the paper titled On the Impossibility of Supersized Machines, by Ben Garfinkel and 8 other authors View PDF Abstract:In recent years, a number of prominent computer scientists, along with academics in fields such as philosophy and physics, have lent credence to the notion that machines may one day become as large as humans. Many have further argued that machines could even come to exceed human size by a significant margin.

Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv.org.

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