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← Demand for intelligence is highly elastic — every fall in inference cost is met with rapidly growing usage.
17 connected korrents · 19 moments from 12 Sept 2022 to 23 Oct 2026.
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AI and jobs In tension 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: Demand for intelligence is highly elastic — every fall in inference cost is met with rapidly growing usage. Demand for intelligence is highly elastic — every fall in inference cost is met with rapidly growing usage. Last stated 2 months ago
23 Aug 2026
GR
Guillermo Rauch — holds since 2026-08-23 — tap for who they are
In tension: Peak programmer has passed: the economic value of writing code by hand has peaked, and Jevons' paradox will not bail every programmer out. — tap to centre the map on it Peak programmer has passed: the economic value of writing code by hand has peaked, and Jevons' paradox will not bail every programmer out. Last stated 7 months ago
8 Apr 2026
DH
David Heinemeier Hansson — holds since 2025-07-12 — tap for who they are
DH
David Heinemeier Hansson — holds since 2026-04-08 — tap for who they are
Same subject: Demand for inference may be growing exponentially while GPU production can only grow linearly, and the tightening happens where those two lines cross. — tap to centre the map on it Demand for inference may be growing exponentially while GPU production can only grow linearly, and the tightening happens where those two lines cross. Last stated 5 months ago
27 May 2026
DR
Dax Raad — holds since 2026-05-27 — tap for who they are
Same subject: There is infinite demand for intelligence. — tap to centre the map on it There is infinite demand for intelligence. Last stated 2 months ago
9 Sept 2026
GR
Guillermo Rauch — holds since 2026-09-09 — tap for who they are
Same subject: As AI inference costs fall, rising customer expectations will keep service margins from converging toward 100%. — tap to centre the map on it As AI inference costs fall, rising customer expectations will keep service margins from converging toward 100%. Last stated a month ago
17 Sept 2026
TT
Tomasz Tunguz — holds since 2026-09-17 — tap for who they are
Same subject: Demand for cheap, high-quality intelligence is effectively uncapped, which makes it unlike every other commodity — including electricity. — tap to centre the map on it Demand for cheap, high-quality intelligence is effectively uncapped, which makes it unlike every other commodity — including electricity. Last stated 3 months ago
28 Jul 2026
SA
Sam Altman — holds since 2026-07-28 — tap for who they are
Same subject: Demand for AI computing power is growing faster than supply. — tap to centre the map on it Demand for AI computing power is growing faster than supply. Last stated 3 days ago
23 Oct 2026
DT
Derek Thompson — holds since 2026-10-23 — tap for who they are
Same subject: Inference was never going to be the easy, cheap half of AI, because inference is thinking, and thinking is far harder than reading. — tap to centre the map on it Inference was never going to be the easy, cheap half of AI, because inference is thinking, and thinking is far harder than reading. Last stated 7 months ago
23 Mar 2026
JH
Jensen Huang — holds since 2026-03-23 — tap for who they are
Same subject: Compute is not a market like phones, where demand is capped by how many buyers there are; intelligence is priced like energy, so the only real question is how much the world uses at a given price. — tap to centre the map on it Compute is not a market like phones, where demand is capped by how many buyers there are; intelligence is priced like energy, so the only real question is how much the world uses at a given price. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: Real reasoning will have arrived when spending more compute at inference time reliably buys a dramatically better answer. — tap to centre the map on it Real reasoning will have arrived when spending more compute at inference time reliably buys a dramatically better answer. Last stated 2 years ago
19 Jun 2024
AS
Aravind Srinivas — holds since 2024-06-19 — tap for who they are
Same subject: A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. — tap to centre the map on it A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI. Last stated 10 months ago
1 Jan 2026
JL
Jason Lemkin — holds since 2026-01-01 — tap for who they are
Same subject: A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. — tap to centre the map on it A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to. Last stated 3 months ago
15 Jul 2026
DH
Dex Horthy — holds since 2026-07-15 — tap for who they are
Same subject: A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. — tap to centre the map on it A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls. Last stated a month ago
17 Sept 2026
PC
Patrick Collison — holds since 2026-09-17 — tap for who they are
Same subject: A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact. — tap to centre the map on it A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact. Last stated 8 months ago
12 Feb 2026
AK
Andrej Karpathy — holds since 2026-02-12 — tap for who they are
Same subject: AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun. — tap to centre the map on it AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun. Last stated 3 years ago
18 Mar 2024
SA
Sam Altman — holds since 2024-03-18 — tap for who they are
Same subject: An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected. — tap to centre the map on it An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected. Last stated 4 years ago
21 Mar 2023
BC
Bryan Caplan — holds since 2023-03-21 — tap for who they are
Same subject: AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard. — tap to centre the map on it AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard. Last stated 2 years ago
2 Feb 2025
AC
Ajeya Cotra — holds since 2023-08-29 — tap for who they are
SA
Scott Alexander — holds since 2022-09-12 — tap for who they are
MB
Miles Brundage — holds since 2025-02-02 — tap for who they are
Same subject: As models keep growing, AI is running out of enough high-quality unique training tokens to keep up. — tap to centre the map on it As models keep growing, AI is running out of enough high-quality unique training tokens to keep up. Last stated 4 months ago
24 Jun 2026
LW
Lilian Weng — holds since 2026-06-24 — tap for who they are
At the centre
Demand for intelligence is highly elastic — every fall in inference cost is met with rapidly growing usage.
Holds Read this korrent →
Peak programmer has passed: the economic value of writing code by hand has peaked, and Jevons' paradox will not bail every programmer out.
Holds
Demand for inference may be growing exponentially while GPU production can only grow linearly, and the tightening happens where those two lines cross.
Holds
There is infinite demand for intelligence.
Holds
As AI inference costs fall, rising customer expectations will keep service margins from converging toward 100%.
Holds
Demand for cheap, high-quality intelligence is effectively uncapped, which makes it unlike every other commodity — including electricity.
Holds
Demand for AI computing power is growing faster than supply.
Holds
Inference was never going to be the easy, cheap half of AI, because inference is thinking, and thinking is far harder than reading.
Holds
Compute is not a market like phones, where demand is capped by how many buyers there are; intelligence is priced like energy, so the only real question is how much the world uses at a given price.
Holds
Real reasoning will have arrived when spending more compute at inference time reliably buys a dramatically better answer.
Holds
A badly written AI outbound email is evidence of a bad vendor, not of a limit of AI.
Holds
A bigger context window does not give you a smarter model; the intelligence of the model is what decides how much of that window it can actually attend to.
Holds
A body of publications is easy for AI models to consume via pretraining corpora but cumbersome for most humans due to CAPTCHAs, accounts, and paywalls.
Holds
A tiny language model inventing a plausible-sounding name is the same phenomenon as a large one confidently stating a false fact.
Holds
AI should be released iteratively rather than built in secret, because AI and surprise do not go together and the world needs time to adapt before it is under the gun.
Holds
An AI can already earn an A on a university economics midterm, years earlier than informed forecasters expected.
Holds
AI progress is faster than people expect, and ordinary scaling can be enough to solve problems that looked very hard.
Holds
As models keep growing, AI is running out of enough high-quality unique training tokens to keep up.
Holds