Many respected neocortex researchers believe there is effectively one algorithm for all intelligence.
Mostly true True in substance, wrong in a detail.
Factual: Statements about the present or the past, checked against the record: did they hold up?
The second judge would not resolve this claim; the verdict shown is the first judge's.
What would count as true or false
Judged as of February 2015. True: the published literature shows several prominent, credentialed neuroscientists who study the neocortex (for example in the tradition of Mountcastle's common cortical algorithm hypothesis) holding that one common cortical algorithm underlies intelligence, and that this is a significant, recognised position. Mostly true: the hypothesis is held by a recognised group of researchers, but the claim slightly overstates how widely it is held or how strongly it is believed. Mixed: there are some proponents, but the field is sharply divided and the idea's standing is contested. Mostly false: only one or two figures, or mainly non-specialists, held the view, so 'many respected researchers' distorts a niche position. False: no respected neocortex researchers held the view.
Set before the research began.
Evidence (4)
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E1 1 Toward a Universal Cortical Algorithm arXiv (author: Michael R. Ferrier, Brown University)
“In review, there is compelling evidence that the various areas of cerebral cortex all implement a common algorithm.”
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E2 Sequence memory for prediction, inference and behaviour PubMed Central (Philosophical Transactions of the Royal Society B theme issue) · 12 May 2009
“Previously, we have proposed that the neocortex can be modelled as a hierarchy of memory regions, each of which learns and recalls sequences.”
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E3 Canonical circuits of the cerebral cortex as enablers of neuroprosthetics PubMed Central · 8 November 2013
“Otto Creutzfeld believed that these repetitive neocortical microcircuits processed information in similar manner with the resultant output depending on both the source of information and modulatory influences peculiar to each brain region”
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E4 The cortical column: a structure without a function PubMed Central (Philosophical Transactions of the Royal Society B) · 29 April 2005
“Although the column is an attractive concept, it has failed as a unifying principle for understanding cortical function.”
Reasoning
E1, an undated arXiv paper, finds "compelling evidence" that the various areas of cerebral cortex all implement a common algorithm. E3 records the neuroscientist Otto Creutzfeldt's view that repeated neocortical microcircuits process information in a similar way, and E2 sets out a model of the neocortex as a hierarchy of memory regions, each of which learns and recalls sequences. Together these show the common-algorithm idea was a recognised position before February 2015. However, E4 (2005) says the cortical column "has failed as a unifying principle" for understanding cortical function, which indicates that related ideas were questioned, and the evidence names only a few proponents. "Many respected researchers" therefore somewhat overstates how widely and how firmly the view was held.
Cite this claim
Sam Altman, “Many respected neocortex researchers believe there is effectively one algorithm for all intelligence.” (said February 2015). Verdict: mostly true. Reliability API, claim c_3afac2eca81a, method 0.1.0+c876030c, dataset release v1.1.2. https://epistacklabs.com/claims/c_3afac2eca81a
This claim is in dataset release v1.1.2, with the same verdict.
Reply to this claim
More factual claims by Sam Altman
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Mostly true
“TL;DR? A summary (from our instruction-following model) of the first part of our paper today on summarization:”
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“Human brains don’t look all that different from chimp brains, and yet somehow produce wildly different capabilities.”
Human brains do not look very different from chimp brains yet produce wildly different capabilities.
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“The very end of 2015, we announced it, and then the first day of work was like January of 2016.”
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“not until 2020 did we train GPT-3, which was the first model that I think actually was over some threshold of usability.”
OpenAI trained GPT-3 in 2020, which Altman considers the first model above a threshold of usability.
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Mostly true
“Absolutely. To go back to the analogy of electricity, there’s this amazing chart of what it cost to have an hour of light at night.”
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