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arvind narayanan

1 capture, most recent first.

Eli Lifland @eli_lifland

quoting Helen Toner (@hlntnr) substack

Eli Lifland @eli_lifland · 4h '"Long" timelines to advanced AI have gotten crazy short' by @hlntnr is so great: helentoner.substack.com/p/long-timelin... LeCun and Marcus have 10-20 year timelines! Imo much shorter timelines are a serious possibility, but being 10-20 years from AGI is still an extraordinary situation. [Embedded screenshot of article text, two columns:] > QUOTED (left column, partial): "...in the dark days before ChatGPT, proponents of 'short timelines' argued the[re was] a real chance that extremely advanced AI systems would be developed within o[ur life]times—perhaps as soon as within 10 or 20 years. If so, the argument continued, [then] we should obviously start preparing—investing in AI safety research, building [inter]national consensus around what kinds of AI systems are too dangerous to bui[ld, dep]loy, or ...[ensuring] adversaries couldn't steal them, and so on. These preparations could take years o[r deca]des, the argument went, so we should get to work right away. Opponents with 'long timelines' would counter that, in fact, there was no evidence [that] AI was going to get very advanced any time soon (say, any time in the next 30 [year]s). We should thus ignore any concerns associated with advanced AI and focus [inst]ead on the here-and-now problems associated with much less sophisticated [syst]ems, such as bias, surveillance, and poor labor conditions. Depending on the [disp]osition of the speaker, problems from AGI might be banished forever as 'scien[ce ficti]on' or simply relegated to the later bucket. [Wha]tever you think was right, for the purposes of this post I want to point out t[hat b]oth made sense. 'This enormously consequential technology might be built with[in a c]ouple of decades, we'd better prepare,' vs. 'No it won't, so that would be a waste o[f time]' is a perfectly sensible set of opposing positions. [Toda]y, in this era of scaling laws, reasoning models, and agents, the debates look [differ]ent." > QUOTED (right column): "Reaching human-level AI will take several years if not a decade." (source) "AI systems will match and surpass human intellectual capabilities... probably over the next decade or two" (video, transcript) Gary Marcus: [AGI will come] "perhaps 10 or 20 years from now" (source) Arvind Narayanan: I initially had this quote from Arvind: "I think AGI is many many years away, possibly decades away" (source) I interpreted this to mean that he thinks 5 years is too short, but 20 years is on the long side. When I ran this interpretation by Arvind, he added some interesting context: he chose his phrasing in that interview in light of what he sees as a watering down of the definition of AGI, so his real timeline is longer. But to clarify what that meant, he said: "I think actual transformative effects (e.g. most cognitive tasks being done by AI) is decades away (80% likely that it is more than 20 years away)." (source: private correspondence) ...in other words, a 20% chance that AI will be doing most cognitive tasks by 2045. These "long" timelines sure look a lot like what we used to call "short"! In other words: Yes, it's still the case that some AI experts think we'll build human-level AI soon, and others think we have more time. But recent advances in AI have pulled the meanings of "soon" and "more time" much closer to the present—so close [that]"
Note from Claude Sonnet 5

A tweet sharing Helen Toner's substack post on how AI timeline discourse has shifted — self-described "long timeline" skeptics (LeCun, Marcus, Narayanan) now hold positions (10-20 years, 20% chance of transformative AI by 2045) that would have counted as "short timelines" pre-ChatGPT. Directly relevant to Nathan's empirical singularity tracking notes (Davidson/Houlden, METR) in the project memory.

twitterai timelinesagi forecastinghelen tonergary marcusarvind narayananyann lecun