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← Unsupervised learning trained on unfiltered, internet-scale image data now genuinely works.

17 connected korrents · 16 moments from 1 Jun 2009 to 18 Sept 2026.

Everything filed under neural networks neural networks Everything filed under computer vision computer vision Everything filed under LLMs LLMs Everything filed under pruning pruning Everything filed under robotics robotics Everything filed under physics physics Everything filed under transformers transformers Same subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subjectSame subject Read this korrent: Unsupervised learning trained on unfiltered, internet-scale image data now genuinely works. Unsupervised learning trained onunfiltered, internet-scale image data nowgenuinely works. Last stated 6 years ago 6 Apr 2021 GW Gwern — holds since 2021-04-06 — tap for who they are Same subject: ImageNet is much larger in scale and diversity and more accurate than existing image datasets. — tap to centre the map on it ImageNet is much larger in scale anddiversity and more accurate thanexisting image datasets. Last stated 17 years ago 1 Jun 2009 FL Fei-Fei Li — holds since 2009-06-01 — tap for who they are Same subject: Supervised pretraining on ImageNet is now obsolete for transfer learning, and ImageNet itself is just a contaminated validation set. — tap to centre the map on it Supervised pretraining on ImageNetis now obsolete for transferlearning, and ImageNet itself isjust a contaminated validation set. Last stated 6 years ago 6 Apr 2021 GW Gwern — holds since 2021-04-06 — 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: Growing evidence suggests the brain performs a form of backpropagation-like learning. — tap to centre the map on it Growing evidence suggests the brainperforms a form ofbackpropagation-like learning. Last stated 6 years ago 13 Mar 2021 GW Gwern — holds since 2021-03-13 — tap for who they are Same subject: Letting a robot imagine the next image helps, but it is not essential — the model was surprisingly good without it. — tap to centre the map on it Letting a robot imagine the nextimage helps, but it is not essential— the model was surprisingly goodwithout it. Last stated 2 months ago 12 Aug 2026 CF Chelsea Finn — holds since 2026-08-12 — tap for who they are Same subject: The internet is not a random pile of content but the largest capture of human behaviour ever made, which is the whole reason AI trained on it works. — tap to centre the map on it The internet is not a random pile ofcontent but the largest capture ofhuman behaviour ever made, which isthe whole reason AI trained on itworks. Last stated 2 months ago 10 Aug 2026 FL Fei-Fei Li — holds since 2026-08-10 — 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: Current AI struggles even to rediscover old laws of physics from data, and when it does, contamination from training is the first suspect. — tap to centre the map on it Current AI struggles even torediscover old laws of physics fromdata, and when it does,contamination from training is thefirst suspect. Last stated a year ago 14 Jun 2025 TT Terence Tao — holds since 2025-06-14 — tap for who they are Same subject: AlexNet's real breakthrough was not computer vision but the discovery of a universal function approximator that can learn any function. — tap to centre the map on it AlexNet's real breakthrough was notcomputer vision but the discovery ofa universal function approximatorthat can learn any function. Last stated 3 months ago 26 Jul 2026 JH Jensen Huang — holds since 2026-07-26 — tap for who they are Same subject: Atlas is the first model to unify pixel generation and pixel reconstruction, two tracks computer vision has kept apart for over half a century. — tap to centre the map on it Atlas is the first model to unifypixel generation and pixelreconstruction, two tracks computervision has kept apart for over halfa century. Last stated 2 months ago 4 Sept 2026 FL Fei-Fei Li — holds since 2026-09-04 — 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: Batteries will replace transmission as the cheapest way to keep the lights on, and the grid will shrink rather than grow. — tap to centre the map on it Batteries will replace transmissionas the cheapest way to keep thelights on, and the grid will shrinkrather than grow. Last stated 10 months ago 8 Dec 2025 CH Casey Handmer — holds since 2023-10-11 — tap for who they are CH Casey Handmer — holds since 2025-12-08 — tap for who they are Same subject: Most agent harnesses need some pruning during context compaction anyway for cost reasons, which Jev might help with. — tap to centre the map on it Most agent harnesses need somepruning during context compactionanyway for cost reasons, which Jevmight help with. Last stated a month ago 18 Sept 2026 AR Armin Ronacher — holds since 2026-09-18 — tap for who they are Same subject: Neuroplasticity is as much the removal of connections as the growth of new ones, so pruning is a form of learning rather than a form of decay. — tap to centre the map on it Neuroplasticity is as much theremoval of connections as the growthof new ones, so pruning is a form oflearning rather than a form ofdecay. Last stated 3 months ago 20 Jul 2026 TW Tommy Wood — holds since 2026-07-20 — tap for who they are Same subject: Sequence transduction can use a simple architecture based solely on attention, without recurrence or convolutions. — tap to centre the map on it Sequence transduction can use asimple architecture based solely onattention, without recurrence orconvolutions. 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 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: Looped/recurrent-depth transformer architectures can improve model quality at a fixed compute budget when the model is large enough. — tap to centre the map on it Looped/recurrent-depth transformerarchitectures can improve modelquality at a fixed compute budgetwhen the model is large enough. Last stated a month ago 9 Sept 2026 SR Sebastian Raschka — holds since 2026-09-09 — tap for who they are
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At the centre Unsupervised learning trained on unfiltered, internet-scale image data now genuinely works. Last stated 6 Apr 2021 · 6 years ago Holds Gwern Read this korrent →