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← With suitable architecture, gradient-based learning can form decision…

17 connected korrents · 15 moments from 1 Jan 1998 to 18 Sept 2026.

Everything filed under neural networks neural networks Everything filed under pruning pruning Everything filed under scaling laws scaling laws Everything filed under LLMs LLMs Everything filed under optimizers optimizers 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: With suitable architecture, gradient-based learning can form decision surfaces that classify high-dimensional patterns such as handwritten characters with minimal preprocessing. With suitable architecture, gradient-basedlearning can form decision surfaces thatclassify high-dimensional patterns such ashandwritten characters with minimalpreprocessing. Last stated 29 years ago 1 Jan 1998 YB Yoshua Bengio — holds since 1998-01-01 — tap for who they are Same subject: Multilayer neural networks trained with backpropagation are the best example of successful gradient-based learning. — tap to centre the map on it Multilayer neural networks trainedwith backpropagation are the bestexample of successful gradient-basedlearning. Last stated 29 years ago 1 Jan 1998 YB Yoshua Bengio — holds since 1998-01-01 — tap for who they are Same subject: Pre-trained representations reduce the need for many heavily-engineered task-specific architectures. — tap to centre the map on it Pre-trained representations reducethe need for many heavily-engineeredtask-specific architectures. Last stated 8 years ago 11 Oct 2018 KT Kristina Toutanova — holds since 2018-10-11 — tap for who they are MC Ming-Wei Chang — holds since 2018-10-11 — tap for who they are KL Kenton Lee — holds since 2018-10-11 — tap for who they are JD Jacob Devlin — holds since 2018-10-11 — tap for who they are Same subject: Gradient descent finds a solution to the problems a model has seen; nothing in the algorithm makes it pick the one that generalises well. — tap to centre the map on it Gradient descent finds a solution tothe problems a model has seen;nothing in the algorithm makes itpick the one that generalises well. Last stated a year ago 26 Sept 2025 RS Richard Sutton — holds since 2025-09-26 — tap for who they are Same subject: Graph transformer networks allow multimodule document recognition systems to be trained globally with gradient methods to minimize overall performance. — tap to centre the map on it Graph transformer networks allowmultimodule document recognitionsystems to be trained globally withgradient methods to minimize overallperformance. Last stated 29 years ago 1 Jan 1998 YB Yoshua Bengio — holds since 1998-01-01 — tap for who they are Same subject: AI text detection through pattern recognition is prone to errors because LLM text may defy patterns or human text may mirror AI patterns. — tap to centre the map on it AI text detection through patternrecognition is prone to errorsbecause LLM text may defy patternsor human text may mirror AIpatterns. Last stated 3 months ago 9 Aug 2026 JW John Warner — holds since 2026-08-09 — tap for who they are Same subject: Pattern recognition and replication is fundamentally what machine-learning systems do best. — tap to centre the map on it Pattern recognition and replicationis fundamentally whatmachine-learning systems do best. Last stated 2 months ago 10 Aug 2026 AH Ann Handley — holds since 2026-08-10 — tap for who they are Same subject: An optimizer that is invariant to rescaling the gradients and cheap in memory is what makes very large models practical to train. — tap to centre the map on it An optimizer that is invariant torescaling the gradients and cheap inmemory is what makes very largemodels practical to train. Last stated 12 years ago 22 Dec 2014 JB Jimmy Ba — holds since 2014-12-22 — tap for who they are DK Diederik P. Kingma — holds since 2014-12-22 — tap for who they are Same subject: Convolutional neural networks are specifically designed to handle variability in two-dimensional shapes. — tap to centre the map on it Convolutional neural networks arespecifically designed to handlevariability in two-dimensionalshapes. Last stated 29 years ago 1 Jan 1998 YB Yoshua Bengio — holds since 1998-01-01 — 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 11 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 2 months ago 9 Sept 2026 SR Sebastian Raschka — holds since 2026-09-09 — tap for who they are Same subject: "Scaling" was powerful because it was one word: naming a research direction is what tells a whole field what to do next. — tap to centre the map on it "Scaling" was powerful because itwas one word: naming a researchdirection is what tells a wholefield what to do next. Last stated 11 months ago 25 Nov 2025 IS Ilya Sutskever — holds since 2025-11-25 — tap for who they are Same subject: A benchmark result should be reported under a stated budget, or as a curve against test-time compute — never as a single number. — tap to centre the map on it A benchmark result should bereported under a stated budget, oras a curve against test-time compute— never as a single number. Last stated 4 months ago 26 Jun 2026 NB Noam Brown — holds since 2026-06-26 — tap for who they are Same subject: A lab should spend most of its compute on research rather than on building the next model, because research is where the tenfold yearly efficiency gains come from. — tap to centre the map on it A lab should spend most of itscompute on research rather than onbuilding the next model, becauseresearch is where the tenfold yearlyefficiency gains come from. Last stated 7 months ago 13 Mar 2026 DP Dylan Patel — holds since 2026-03-13 — tap for who they are
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At the centre With suitable architecture, gradient-based learning can form decision surfaces that classify high-dimensional patterns such as handwritten characters with minimal preprocessing. Last stated 1 Jan 1998 · 29 years ago Holds Yoshua Bengio Read this korrent →