yann lecun

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]"

norvid_studies @norvid_studies I didn't know the historical version but oddly this *exact* objection was made to LLMs, iirc by lecun(?). the LLM has some chance of an error at every token. the error chance blows up as length increases. if it makes any error, the entire computation fails... "[Historians of computing might remember when von Neumann came on the scene in the 1940s, there was an objection to classical computers that goes like "Computers are made of gates. Gates have errors. As soon as you get an error, the rest of the computation is bunk. The probability of *not* making an error is exponentially decaying. Therefore, upper bound to how much can be computed reliably is very small -- logarithmically small!" Von Neumann said no with his threshold theorem. If the individual gates are reliable enough, then you can build composite gates of arbitrarily high reliability.]" > QUOTED: Yuxi on the Wired @layer07_yuxi · Oct 6 > Replying to @Algon_33 > Your objection is difficult to understand. Do you mean that mathematician's intuition is more reliable than proofchecker? This is an incredible statement. We[?] is false. How many times have mathematician's in... > Show more

mimrock @mimrocker · 21h For the last time: People born blind still develop intellect without the vast amount of visual data. It is not necessary for cognition. Do you know what input is crucial for cognition? Language. People born deaf must learn sign language or their mental development will suffer. > QUOTED: hampton — e... ✓ @hampt... · Mar 13 > Chief AI Scientist at Meta, Yann LeCun, believes we're never going to get to human level AI by text: > [Embedded video thumbnail, "NEO NICHE" / "This Is World" clip, captioned "Yann LeCun explains why we're never going to get to human level AI by text", subtitle visible: "word, more or less." Duration 0:54, dated 03.07.25]