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Aschenbrenner's essay of 2024 argues against the view that deep learning is hitting a wall, holding that trends in compute, algorithmic efficiency and 'unhobbling' make AGI by 2027 'strikingly plausible', and treats the data wall as a source of variance rather than a limit. Copy claim link
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Supporting evidence: primary · 1 source
Date 2024 · publication Records dated 2024 → Role Contesting Register (kind of text) Nonfiction Engagement Engages a premise. It disputes the premises that scaling trends have stalled and that the shortage of internet data will stop progress short of AGI. Scope and limits The chapter states that without new methods the pretraining paradigm 'will (at least naively) run out' and that 'we’d plateau'; it argues that labs' research bets are likely to get around this. A forecast, not a demonstration.
The evidence 02 primary source Supports the claim
I. From GPT-4 to AGI: Counting the OOMs ↗ Situational Awareness: The Decade Ahead (situational-awareness.ai) · 2024
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Source excerpt “AGI by 2027 is strikingly plausible.” Location in source Chapter I, opening summary
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Leopold Aschenbrenner Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 9129049ea8fdc7c74585fad35e9c0b3a575affbf6651d066795b02f1500e3427). Current chapter page, retrieved 2026-10-29. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Leopold Aschenbrenner, “I. From GPT-4 to AGI: Counting the OOMs”, 2024. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (6 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. primary source Supports the claim
I. From GPT-4 to AGI: Counting the OOMs ↗ Situational Awareness: The Decade Ahead (situational-awareness.ai) · 2024
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Cite the original source Cite the original document, not Selekoa. Check these details against it.
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Source excerpt “leading some to proclaim stagnation and that deep learning is hitting a wall.1 But by counting the OOMs, we get a peek at what we should actually expect.” Location in source Chapter I, introduction
How it was read Retrieved directly from the publisher
Machine-checked · 2026-10-31
Source details and check notes Authors Leopold Aschenbrenner Version Retrieved for the candidate pack on 2026-10-29 (SHA-256 9129049ea8fdc7c74585fad35e9c0b3a575affbf6651d066795b02f1500e3427). Current chapter page, retrieved 2026-10-29. Canonical address Open the canonical source ↗ Accessed 2026-10-29 Language English (en) Attribution Leopold Aschenbrenner, “I. From GPT-4 to AGI: Counting the OOMs”, 2024. Reuse No open redistribution licence asserted. Bibliographic metadata, editorial paraphrases and short attributed quotations (at most 50 words each). Recheck terms before wider redistribution. Check notes Candidate pack passage, arguments about catastrophic risk from advanced AI (research/risk-debate). The quotation (28 words) matched the text retrieved for the candidate pack on 2026-10-29. Matching ignored differences of whitespace, case, quotation marks, dashes and Unicode compatibility forms, so the source’s typography can differ. No human editorial review. Status and meaning Editorial status. Not reviewed by an editor . An exploratory record that no editor has accepted. This status does not say whether a person has read any linked passage. Each evidence record above shows how it was checked.
Relation. A passage of the document disputes the proposition or a premise it depends on. The record documents the text’s position, not who is right.
Date. Date of publication, as the source gives it.
Record ID rd-r13-aschenbrenner-2024-situational-awareness