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← How large-scale internet image data can be harnessed and organized remains a critical problem.

17 connected korrents · 17 moments from 1 Jun 2009 to 10 Aug 2026.

Everything filed under computer vision computer vision Everything filed under neural networks neural networks Everything filed under AI and jobs AI and jobs Everything filed under LLMs LLMs Everything filed under robotics robotics Everything filed under the cloud the cloud Same subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subject Read this korrent: How large-scale internet image data can be harnessed and organized remains a critical problem. How large-scale internet image data can beharnessed and organized remains a criticalproblem. Last stated 17 years ago 1 Jun 2009 FL Fei-Fei Li — holds since 2009-06-01 — tap for who they are Same subject: Growth of internet image data can enable more sophisticated models for indexing and interacting with multimedia. — tap to centre the map on it Growth of internet image data canenable more sophisticated models forindexing and interacting withmultimedia. Last stated 17 years ago 1 Jun 2009 FL Fei-Fei Li — holds since 2009-06-01 — tap for who they are Same subject: The internet is already past peak truth, and picking out training data worth learning from will only get harder. — tap to centre the map on it The internet is already past peaktruth, and picking out training dataworth learning from will only getharder. Last stated 5 months ago 13 May 2026 AH Anders Hejlsberg — holds since 2026-05-13 — tap for who they are Same subject: AI's bottleneck was never its algorithms but how little data they were fed, which is why the field needed ImageNet rather than another model. — tap to centre the map on it AI's bottleneck was never itsalgorithms but how little data theywere fed, which is why the fieldneeded ImageNet rather than anothermodel. Last stated 2 months ago 10 Aug 2026 FL Fei-Fei Li — holds since 2026-08-10 — tap for who they are Same subject: High-quality video data, especially paired with text, is harder to collect at scale than image or text data. — tap to centre the map on it High-quality video data, especiallypaired with text, is harder tocollect at scale than image or textdata. Last stated 3 years ago 12 Apr 2024 LW Lilian Weng — holds since 2024-04-12 — tap for who they are Same subject: AI is too critical to be delivered only as a centralized, hosted service. — tap to centre the map on it AI is too critical to be deliveredonly as a centralized, hostedservice. Last stated 5 months ago 14 May 2026 SS Salvatore Sanfilippo — holds since 2026-05-14 — tap for who they are Same subject: Models are enormous only because the internet is bad: most of that capacity does memory work, and a better dataset would need far less of it. — tap to centre the map on it Models are enormous only because theinternet is bad: most of thatcapacity does memory work, and abetter dataset would need far lessof it. Last stated a year ago 17 Oct 2025 AK Andrej Karpathy — holds since 2025-10-17 — tap for who they are Same subject: Unsupervised learning trained on unfiltered, internet-scale image data now genuinely works. — tap to centre the map on it Unsupervised learning trained onunfiltered, internet-scale imagedata now genuinely works. Last stated 6 years ago 6 Apr 2021 GW Gwern — holds since 2021-04-06 — tap for who they are Same subject: Alignment of today's models is going well enough to look solvable, while aligning models we can no longer understand remains unsolved. — tap to centre the map on it Alignment of today's models is goingwell enough to look solvable, whilealigning models we can no longerunderstand remains unsolved. Last stated 9 months ago 22 Jan 2026 JL Jan Leike — holds since 2026-01-22 — tap for who they are Same subject: A layer should learn a residual with reference to its own input rather than an unreferenced function, which is what makes great depth trainable. — tap to centre the map on it A layer should learn a residual withreference to its own input ratherthan an unreferenced function, whichis what makes great depth trainable. Last stated 11 years ago 10 Dec 2015 JS Jian Sun — holds since 2015-12-10 — tap for who they are KH Kaiming He — holds since 2015-12-10 — tap for who they are Same subject: A small enough winning ticket learns faster than the network it was cut out of, and ends up more accurate than it. — tap to centre the map on it A small enough winning ticket learnsfaster than the network it was cutout of, and ends up more accuratethan it. Last stated 9 years ago 9 Mar 2018 MC Michael Carbin — holds since 2018-03-09 — tap for who they are JF Jonathan Frankle — holds since 2018-03-09 — tap for who they are Same subject: A transduction model can rely entirely on self-attention for input and output representations without sequence-aligned RNNs or convolution. — tap to centre the map on it A transduction model can relyentirely on self-attention for inputand output representations withoutsequence-aligned RNNs orconvolution. Last stated 9 years ago 12 Jun 2017 IP Illia Polosukhin — holds since 2017-06-12 — tap for who they are JU Jakob Uszkoreit — holds since 2017-06-12 — tap for who they are NP Niki Parmar — holds since 2017-06-12 — tap for who they are AV Ashish Vaswani — holds since 2017-06-12 — tap for who they are NS Noam Shazeer — holds since 2017-06-12 — tap for who they are AG Aidan N. Gomez — holds since 2017-06-12 — tap for who they are +2 2 more Same subject: A company must cut half its engineers to pay for the other half's tokens, and that is what the layoffs are actually about. — tap to centre the map on it A company must cut half itsengineers to pay for the otherhalf's tokens, and that is what thelayoffs are actually about. Last stated 7 months ago 11 Mar 2026 SY Steve Yegge — holds since 2026-03-11 — tap for who they are Same subject: A home is an asset that is likely to perform poorly exactly when a person needs it most due to its correlation with local labor market shocks. — tap to centre the map on it A home is an asset that is likely toperform poorly exactly when a personneeds it most due to its correlationwith local labor market shocks. Last stated 3 months ago 30 Jul 2026 JD Jerusalem Demsas — holds since 2026-07-30 — tap for who they are Same subject: A labor market stuck in a low-hiring equilibrium will see employment decline outright unless hiring rates recover. — tap to centre the map on it A labor market stuck in a low-hiringequilibrium will see employmentdecline outright unless hiring ratesrecover. Last stated 9 months ago 11 Jan 2026 JP Joseph Politano — holds since 2026-01-11 — tap for who they are Same subject: A highly dynamic economy that cheaply mass-produces robots may increase rather than decrease the risk of Malthusian resource dilemmas. — tap to centre the map on it A highly dynamic economy thatcheaply mass-produces robots mayincrease rather than decrease therisk of Malthusian resourcedilemmas. Last stated 3 years ago 1 Oct 2023 TC Tyler Cowen — holds since 2023-10-01 — tap for who they are Same subject: A humanoid robot is the wrong tool on a factory floor, because a machine specialised in the task beats it. — tap to centre the map on it A humanoid robot is the wrong toolon a factory floor, because amachine specialised in the taskbeats it. Last stated 2 years ago 6 Apr 2025 MH Molson Hart — holds since 2025-04-06 — tap for who they are Same subject: A physical AI agent has to be safe on day one, because you cannot ship something merely good enough and let users find the edge cases. — tap to centre the map on it A physical AI agent has to be safeon day one, because you cannot shipsomething merely good enough and letusers find the edge cases. Last stated 3 months ago 3 Aug 2026 DD Dmitri Dolgov — holds since 2026-08-03 — tap for who they are
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At the centre How large-scale internet image data can be harnessed and organized remains a critical problem. Last stated 1 Jun 2009 · 17 years ago Holds Fei-Fei Li Read this korrent →