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← General-purpose computing has largely run its course; domain-specific…
17 connected korrents · 16 moments on record from 18 Apr 2024 to 4 Sept 2026.
Everything filed under data centers
data centers
Everything filed under energy
energy
Everything filed under reinforcement learning
reinforcement learning
Everything filed under scaling laws
scaling laws
Everything filed under semiconductors
semiconductors
Everything filed under AGI
AGI 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: General-purpose computing has largely run its course; domain-specific acceleration is the way computing keeps scaling. General-purpose computing has largely run its course; domain-specific acceleration is the way computing keeps scaling. Last stated 5 months ago
15 Apr 2026
JH
Jensen Huang — holds since 2026-04-15 — tap for who they are
Same subject: The business is not building a great chip; it is accelerating an algorithm domain. — tap to centre the map on it The business is not building a great chip; it is accelerating an algorithm domain. Last stated a month ago
26 Jul 2026
JH
Jensen Huang — holds since 2026-07-26 — tap for who they are
Same subject: Compute platforms are converging toward one unified, globally distributed system limited only by physics. — tap to centre the map on it Compute platforms are converging toward one unified, globally distributed system limited only by physics. Last stated 6 days ago
1 Sept 2026
GR
Guillermo Rauch — holds since 2026-09-01 — tap for who they are
Same subject: Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve. — tap to centre the map on it Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve. Last stated a year ago
5 Jun 2025
SP
Sundar Pichai — holds since 2025-06-05 — tap for who they are
Same subject: Intelligence is going to scale by exactly one thing, and that thing is compute. — tap to centre the map on it Intelligence is going to scale by exactly one thing, and that thing is compute. Last stated 6 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own. — tap to centre the map on it Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own. Last stated 2 years ago
3 Feb 2025
NL
Nathan Lambert — holds since 2025-02-03 — tap for who they are
Same subject: By the end of this decade the ceiling on AI compute is set by ASML, the lowest rung of the supply chain, and not by anything above it. — tap to centre the map on it By the end of this decade the ceiling on AI compute is set by ASML, the lowest rung of the supply chain, and not by anything above it. Last stated 6 months ago
13 Mar 2026
DP
Dylan Patel — holds since 2026-03-13 — tap for who they are
Same subject: The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. — tap to centre the map on it The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture. Last stated 3 days ago
4 Sept 2026
FL
Fei-Fei Li — holds since 2026-09-04 — tap for who they are
Same subject: AI capabilities are jagged rather than smooth, so the different definitions of human-level AI will be met years apart rather than together. — tap to centre the map on it AI capabilities are jagged rather than smooth, so the different definitions of human-level AI will be met years apart rather than together. Last stated 5 months ago
6 Apr 2026
HT
Helen Toner — holds since 2026-04-06 — tap for who they are
Same subject: A data centre earns its county far more tax revenue per gallon of water than a golf course does. — tap to centre the map on it A data centre earns its county far more tax revenue per gallon of water than a golf course does. Last stated 11 months ago
11 Oct 2025
AM
Andy Masley — holds since 2025-10-11 — tap for who they are
Same subject: A data centre powered by solar and batteries alone needs an array so oversized that the design is not worth building. — tap to centre the map on it A data centre powered by solar and batteries alone needs an array so oversized that the design is not worth building. Last stated 2 years ago
18 Apr 2024
AV
Austin Vernon — holds since 2024-04-18 — tap for who they are
Same subject: A data centre should be split into independent power blocks fed directly at 1500 volts DC, rather than run through one central distribution system. — tap to centre the map on it A data centre should be split into independent power blocks fed directly at 1500 volts DC, rather than run through one central distribution system. Last stated 2 years ago
18 Apr 2024
AV
Austin Vernon — holds since 2024-04-18 — tap for who they are
Same subject: "Food from thin air" is not from thin air: it runs on water, minerals, ammonia and industrial plant. — tap to centre the map on it "Food from thin air" is not from thin air: it runs on water, minerals, ammonia and industrial plant. Last stated 2 months ago
30 Jun 2026
CS
Chris Smaje — holds since 2026-06-30 — tap for who they are
Same subject: A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. — tap to centre the map on it A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated. Last stated 3 months ago
4 Jun 2026
AI
Alex Imas — holds since 2026-06-04 — tap for who they are
Same subject: A future of constrained energy will need more people working the land, and that is not the same as going back to the past. — tap to centre the map on it A future of constrained energy will need more people working the land, and that is not the same as going back to the past. Last stated 2 months ago
30 Jun 2026
CS
Chris Smaje — holds since 2026-06-30 — tap for who they are
Same subject: A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. — tap to centre the map on it A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well. Last stated 10 months ago
17 Nov 2025
AK
Andrej Karpathy — holds since 2025-11-17 — tap for who they are
Same subject: Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. — tap to centre the map on it Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago. Last stated 6 months ago
20 Mar 2026
AK
Andrej Karpathy — holds since 2026-03-20 — tap for who they are
Same subject: Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. — tap to centre the map on it Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving. Last stated 11 months ago
17 Oct 2025
AK
Andrej Karpathy — holds since 2025-10-17 — tap for who they are
At the centre
General-purpose computing has largely run its course; domain-specific acceleration is the way computing keeps scaling.
Holds JH Jensen HuangRead this korrent →
The business is not building a great chip; it is accelerating an algorithm domain.
Holds JH Jensen Huang
Compute platforms are converging toward one unified, globally distributed system limited only by physics.
Holds
Scaling laws are still working, but the models people actually use run a few months behind the maximum capability Google can deliver, because the biggest model is too slow and expensive to serve.
Holds
Intelligence is going to scale by exactly one thing, and that thing is compute.
Holds JH Jensen Huang
Reasoning will generalize the way instruction tuning did: add enough verifiable domains and, at some point nobody can yet locate, the rest start working on their own.
Holds NL Nathan Lambert
By the end of this decade the ceiling on AI compute is set by ASML, the lowest rung of the supply chain, and not by anything above it.
Holds DP Dylan Patel
The scaling law for world models was a conviction held in advance, not a discovery; the devils were always in the architecture choices and the data mixture.
Holds FL Fei-Fei Li
AI capabilities are jagged rather than smooth, so the different definitions of human-level AI will be met years apart rather than together.
Holds HT Helen Toner
A data centre earns its county far more tax revenue per gallon of water than a golf course does.
Holds AM Andy Masley
A data centre powered by solar and batteries alone needs an array so oversized that the design is not worth building.
Holds AV Austin Vernon
A data centre should be split into independent power blocks fed directly at 1500 volts DC, rather than run through one central distribution system.
Holds AV Austin Vernon
"Food from thin air" is not from thin air: it runs on water, minerals, ammonia and industrial plant.
Holds CS Chris Smaje
A country outside the AI supply chain should just buy the index — which works only in the world where AI ends up commoditised rather than concentrated.
Holds AI Alex Imas
A future of constrained energy will need more people working the land, and that is not the same as going back to the past.
Holds CS Chris Smaje
A verifiable task can be optimised by reinforcement learning until a neural network performs it extremely well.
Holds
Capability does not generalise for free: a model that will move mountains on an agentic task still tells the same bad joke it told five years ago.
Holds
Humans barely use reinforcement learning for intelligence — what RL they do use goes into motor tasks, not problem solving.
Holds