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← The adult brain's stock of neurons is essentially fixed, and that is…
17 connected korrents · 19 moments from 1 Jun 2009 to 18 Sept 2026.
Everything filed under LLMs
LLMs
Everything filed under pruning
pruning
Everything filed under neural networks
neural networks
Everything filed under computer vision
computer vision
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education
Everything filed under AI and science
AI and science
Everything filed under Psychotherapy
Psychotherapy Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Same subject Read this korrent: The adult brain's stock of neurons is essentially fixed, and that is no limit on learning, because plasticity is the changing of connections between the cells you already have. The adult brain's stock of neurons is essentially fixed, and that is no limit on learning, because plasticity is the changing of connections between the cells you already have. Last stated 3 months ago
20 Jul 2026
TW
Tommy Wood — holds since 2026-07-20 — 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 the removal of connections as the growth of new ones, so pruning is a form of learning rather than a form of decay. Last stated 3 months ago
20 Jul 2026
TW
Tommy Wood — holds since 2026-07-20 — tap for who they are
Same subject: Learning takes time, effort and sometimes pain, and no tool changes that, because that is how the brain is built. — tap to centre the map on it Learning takes time, effort and sometimes pain, and no tool changes that, because that is how the brain is built. Last stated 2 months ago
10 Aug 2026
FL
Fei-Fei Li — holds since 2026-08-10 — tap for who they are
Same subject: Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind. — tap to centre the map on it Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind. Last stated a year ago
23 Jul 2025
DH
Demis Hassabis — holds since 2025-07-23 — tap for who they are
Same subject: The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. — tap to centre the map on it The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out. Last stated a year ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
Same subject: The most fertile way to study neuroscience today is to work on AI models rather than on brains. — tap to centre the map on it The most fertile way to study neuroscience today is to work on AI models rather than on brains. Last stated 2 months ago
20 Aug 2026
KK
Kevin Kelly — holds since 2026-08-17 — tap for who they are
MH
Max Hodak — holds since 2026-08-20 — tap for who they are
Same subject: Neural networks do not have a one-to-one mapping between individual neurons and concepts. — tap to centre the map on it Neural networks do not have a one-to-one mapping between individual neurons and concepts. Last stated a month ago
8 Sept 2026
SA
Scott Alexander — holds since 2026-09-08 — tap for who they are
Same subject: Opening a fixed relational pattern takes two things: the implicit made explicit, and the person's own recoil from what they see. — tap to centre the map on it Opening a fixed relational pattern takes two things: the implicit made explicit, and the person's own recoil from what they see. Last stated 3 years ago
11 Aug 2023
TR
Terry Real — holds since 2023-08-11 — 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 brain performs a form of backpropagation-like learning. Last stated 6 years ago
13 Mar 2021
GW
Gwern — holds since 2021-03-13 — 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 transmission as the cheapest way to keep the lights on, and the grid will shrink rather 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 some pruning during context compaction anyway for cost reasons, which Jev might 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: The point of a good memory is not to remember more but to remember better, because forgetting most of what you experience is what human brains are built to do. — tap to centre the map on it The point of a good memory is not to remember more but to remember better, because forgetting most of what you experience is what human brains are built to do. Last stated 2 years ago
25 May 2024
CR
Charan Ranganath — holds since 2024-05-25 — tap for who they are
Same subject: As reasoning models and agents retain more tokens for longer, KV-cache size and attention cost become the main constraint on scaling context. — tap to centre the map on it As reasoning models and agents retain more tokens for longer, KV-cache size and attention cost become the main constraint on scaling context. Last stated 5 months ago
16 May 2026
SR
Sebastian Raschka — holds since 2026-05-16 — tap for who they are
Same subject: Context engineering has stayed relevant for a year because it is grounded in how transformer attention works, and it will matter to anyone building on AI until post-transformer models arrive. — tap to centre the map on it Context engineering has stayed relevant for a year because it is grounded in how transformer attention works, and it will matter to anyone building on AI until post-transformer models arrive. Last stated 3 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: Directly optimizing prompt embeddings (prefix-tuning) yields better performance than even a single optimized text prompt. — tap to centre the map on it Directly optimizing prompt embeddings (prefix-tuning) yields better performance than even a single optimized text prompt. Last stated 6 years ago
4 Feb 2021
GW
Gwern — holds since 2021-02-04 — 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 not computer vision but the discovery of a universal function approximator that 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 unify pixel generation and pixel reconstruction, two tracks computer vision has kept apart for over half a 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 can enable more sophisticated models for indexing and interacting with multimedia. Last stated 17 years ago
1 Jun 2009
FL
Fei-Fei Li — holds since 2009-06-01 — tap for who they are
At the centre
The adult brain's stock of neurons is essentially fixed, and that is no limit on learning, because plasticity is the changing of connections between the cells you already have.
Holds Read this korrent →
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.
Holds
Learning takes time, effort and sometimes pain, and no tool changes that, because that is how the brain is built.
Holds
Anything nature shaped can be learned efficiently by a classical neural network, because evolutionary processes leave structure behind.
Holds
The knowledge a model soaks up in pre-training is holding it back; what we actually want is the intelligence with the knowledge stripped out.
Holds
The most fertile way to study neuroscience today is to work on AI models rather than on brains.
Holds
Neural networks do not have a one-to-one mapping between individual neurons and concepts.
Holds
Opening a fixed relational pattern takes two things: the implicit made explicit, and the person's own recoil from what they see.
Holds
Growing evidence suggests the brain performs a form of backpropagation-like learning.
Holds
Batteries will replace transmission as the cheapest way to keep the lights on, and the grid will shrink rather than grow.
Holds
Most agent harnesses need some pruning during context compaction anyway for cost reasons, which Jev might help with.
Holds
The point of a good memory is not to remember more but to remember better, because forgetting most of what you experience is what human brains are built to do.
Holds
As reasoning models and agents retain more tokens for longer, KV-cache size and attention cost become the main constraint on scaling context.
Holds
Context engineering has stayed relevant for a year because it is grounded in how transformer attention works, and it will matter to anyone building on AI until post-transformer models arrive.
Holds
Directly optimizing prompt embeddings (prefix-tuning) yields better performance than even a single optimized text prompt.
Holds
AlexNet's real breakthrough was not computer vision but the discovery of a universal function approximator that can learn any function.
Holds
Atlas is the first model to unify pixel generation and pixel reconstruction, two tracks computer vision has kept apart for over half a century.
Holds
Growth of internet image data can enable more sophisticated models for indexing and interacting with multimedia.
Holds