#jevonsparadox — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #jevonsparadox, aggregated by home.social.
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Reverse Jevons Paradox
Comments: https://news.ycombinator.com/item?id=49162080
#HackerNews #ReverseJevonsParadox #JevonsParadox #Sustainability #EnergyEfficiency #Innovation
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Reverse Jevons Paradox
Comments: https://news.ycombinator.com/item?id=49162080
#HackerNews #ReverseJevonsParadox #JevonsParadox #Sustainability #EnergyEfficiency #Innovation
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William Jevons stated in 1865 that more efficient steam engines would not decrease the use of coal in British factories but would actually increase it. #nottheonion #jevonsparadox
theonion.com/technologica...
Technological Advancements All... -
William Jevons stated in 1865 that more efficient steam engines would not decrease the use of coal in British factories but would actually increase it. #nottheonion #jevonsparadox
theonion.com/technologica...
Technological Advancements All... -
https://youtu.be/a6sYYrLTOjQ Interesting take on making resource more efficient, made it more used than reducing usage. #jevonsparadox
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The cheaper AI tokens get, the more expensive memory becomes. Inference costs fell 280-fold in two years; enterprise AI spending tripled anyway, and DRAM contract prices just posted a record 90-95% quarterly jump. Jevons saw this pattern in 1865 with coal. A look at what actually rebalances the chip market...
https://www.buysellram.com/blog/cheaper-tokens-ai-chip-shortage/
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #BuySellRam #JevonsParadox #TechHardware -
The cheaper AI tokens get, the more expensive memory becomes. Inference costs fell 280-fold in two years; enterprise AI spending tripled anyway, and DRAM contract prices just posted a record 90-95% quarterly jump. Jevons saw this pattern in 1865 with coal. A look at what actually rebalances the chip market...
https://www.buysellram.com/blog/cheaper-tokens-ai-chip-shortage/
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #BuySellRam #JevonsParadox #TechHardware -
The cheaper AI tokens get, the more expensive memory becomes. Inference costs fell 280-fold in two years; enterprise AI spending tripled anyway, and DRAM contract prices just posted a record 90-95% quarterly jump. Jevons saw this pattern in 1865 with coal. A look at what actually rebalances the chip market...
https://www.buysellram.com/blog/cheaper-tokens-ai-chip-shortage/
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #BuySellRam #JevonsParadox #TechHardware -
The cheaper AI tokens get, the more expensive memory becomes. Inference costs fell 280-fold in two years; enterprise AI spending tripled anyway, and DRAM contract prices just posted a record 90-95% quarterly jump. Jevons saw this pattern in 1865 with coal. A look at what actually rebalances the chip market...
https://www.buysellram.com/blog/cheaper-tokens-ai-chip-shortage/
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #BuySellRam #JevonsParadox #TechHardware -
Claude Sonnet 5 launched at less than half the flagship's price with ninety percent of its benchmark performance. The natural conclusion: AI is getting cheaper, so chip demand should ease. Every data point says otherwise.
Inference costs fell 280-fold between 2022 and 2024 (Stanford AI Index). Enterprise AI spending tripled to $37B in 2025 anyway. DRAM contracts rose a record 90-95% in Q1 2026, NAND is projected up 70-75% in Q2, and SK Hynix has sold out its entire 2026 output. William Stanley Jevons described the mechanism in 1865: make a resource cheaper to use, and total consumption rises.
The article walks through what this means chip by chip — DRAM, NAND, GPUs, and why CPUs are the calm exception — plus the strongest counterarguments (ASICs, MoE, small models) and why they fall short. One practical takeaway: retired server memory is appreciating for the first time in years.
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #ITAssetManagement #JevonsParadox #TechHardware #technology
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Claude Sonnet 5 launched at less than half the flagship's price with ninety percent of its benchmark performance. The natural conclusion: AI is getting cheaper, so chip demand should ease. Every data point says otherwise.
Inference costs fell 280-fold between 2022 and 2024 (Stanford AI Index). Enterprise AI spending tripled to $37B in 2025 anyway. DRAM contracts rose a record 90-95% in Q1 2026, NAND is projected up 70-75% in Q2, and SK Hynix has sold out its entire 2026 output. William Stanley Jevons described the mechanism in 1865: make a resource cheaper to use, and total consumption rises.
The article walks through what this means chip by chip — DRAM, NAND, GPUs, and why CPUs are the calm exception — plus the strongest counterarguments (ASICs, MoE, small models) and why they fall short. One practical takeaway: retired server memory is appreciating for the first time in years.
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #ITAssetManagement #JevonsParadox #TechHardware #technology
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The cheaper AI tokens get, the more expensive memory becomes. Inference costs fell 280-fold in two years; enterprise AI spending tripled anyway, and DRAM contract prices just posted a record 90-95% quarterly jump. Jevons saw this pattern in 1865 with coal. A look at what actually rebalances the chip market...
https://www.buysellram.com/blog/cheaper-tokens-ai-chip-shortage/
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #ITAssetManagement #JevonsParadox #TechHardware -
The cheaper AI tokens get, the more expensive memory becomes. Inference costs fell 280-fold in two years; enterprise AI spending tripled anyway, and DRAM contract prices just posted a record 90-95% quarterly jump. Jevons saw this pattern in 1865 with coal. A look at what actually rebalances the chip market...
https://www.buysellram.com/blog/cheaper-tokens-ai-chip-shortage/
#AI #Semiconductors #DRAM #MemoryShortage #DataCenters #HBM #GPU #SSD #ITAD #BuySellRam #JevonsParadox #TechHardware #tech -
@hu_ai
"less AI" is still AI.
"less meat" is still meat.if your AI slop generator is "more effective," that still does not mean less AI. see #JevonsParadox:
https://en.wikipedia.org/wiki/Jevons_paradoxstop trying to sell us your " #vegan " AI by pretending it's "less AI."
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@hu_ai
"less AI" is still AI.
"less meat" is still meat.if your AI slop generator is "more effective," that still does not mean less AI. see #JevonsParadox:
https://en.wikipedia.org/wiki/Jevons_paradoxstop trying to sell us your " #vegan " AI by pretending it's "less AI."
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@infrastory
Hate to break it to you, but (a) the #JevonsParadox has been a thing for about two centuries, and (b) the atmosphere and oceans neither know nor care how many people are on the plane. -
The problem of too many cars isn’t just about the tailpipes. And although EVs seemingly address that issue (or “move” much of it, depending on the electricity source), their increased weight, and the potential increase in size and distance driven (due to #JevonsParadox) make EVs “complicated.”
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The problem of too many cars isn’t just about the tailpipes. And although EVs seemingly address that issue (or “move” much of it, depending on the electricity source), their increased weight, and the potential increase in size and distance driven (due to #JevonsParadox) make EVs “complicated.”
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I’ll make this VERY clear — if you don’t understand very well critical truths like #InducedDemand (aka the Irrefutable Law of Congestion) and its twin truth #JevonsParadox, you are not qualified to make transportation-related decisions affecting cities. And your profession will make cities worse.
RE: https://bsky.app/profile/did:plc:pchnq7klmm3ejqduuqaqrsd6/post/3mjp36vjox22g -
I’ll make this VERY clear — if you don’t understand very well critical truths like #InducedDemand (aka the Irrefutable Law of Congestion) and its twin truth #JevonsParadox, you are not qualified to make transportation-related decisions affecting cities. And your profession will make cities worse.
RE: https://bsky.app/profile/did:plc:pchnq7klmm3ejqduuqaqrsd6/post/3mjp36vjox22g -
Jevons Paradox vs the DC bubble narrative.
DeepSeek cut AI training cost by 95%. Bears said demand would fall.
What happened: Meta raised capex to $65B. Amazon to $200B. Microsoft held at $80B.
Per-unit cost drops 90%, total volume rises 1,000%. Every efficiency gain bears cite AGAINST DC demand is evidence FOR it.
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DeepSeek matched top US AI models at a fraction of the cost. If efficiency makes AI cheaper, do we use the same amount more efficiently or way more? This is the heart of Jevon's paradox. https://www.poppastring.com/blog/what-about-jevons-paradox #AI #JevonsParadox
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DeepSeek matched top US AI models at a fraction of the cost. If efficiency makes AI cheaper, do we use the same amount more efficiently or way more? This is the heart of Jevon's paradox. https://www.poppastring.com/blog/what-about-jevons-paradox #AI #JevonsParadox
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This obscure Civil War-era figure gave us a paradoxical warning. Do we have time to heed it today?
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Is #AI / #ML / #LLMs going to make your engineering job obsolete? Michelle Brush argues the exact opposite: The job is about to get much, much harder.
Discover how the #JevonsParadox will create massive software demand, while the #IroniesOfAutomation will make the remaining engineering jobs harder.
To thrive & lead in this new tech landscape, engineers MUST master these skills:
🔹 Systems Thinking
🔹 Non-Abstract System Design
🔹 Reliability Engineering
🔹 Complexity TheoryWatch the #InfoQ video for more insights: https://bit.ly/4rxnHAT
#Leadership #Agile #transcript included
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Is #AI / #ML / #LLMs going to make your engineering job obsolete? Michelle Brush argues the exact opposite: The job is about to get much, much harder.
Discover how the #JevonsParadox will create massive software demand, while the #IroniesOfAutomation will make the remaining engineering jobs harder.
To thrive & lead in this new tech landscape, engineers MUST master these skills:
🔹 Systems Thinking
🔹 Non-Abstract System Design
🔹 Reliability Engineering
🔹 Complexity TheoryWatch the #InfoQ video for more insights: https://bit.ly/4rxnHAT
#Leadership #Agile #transcript included
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The Baumol Effect and Jevons paradox are related
https://www.a16z.news/p/why-ac-is-cheap-but-ac-repair-is
#HackerNews #BaumolEffect #JevonsParadox #Economics #Analysis #A16Z #Insights
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The Baumol Effect and Jevons paradox are related
https://www.a16z.news/p/why-ac-is-cheap-but-ac-repair-is
#HackerNews #BaumolEffect #JevonsParadox #Economics #Analysis #A16Z #Insights
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Aus Gründen: "Das bedeutet, dass Sie jetzt eine Menge Geld für sehr kurzfristigen Nutzen ausgeben."
#JevonsParadox: keine Death-Metal-Band, sondern #InducedDemand
Quelle: "abctv" (jetzt ABC Australia) leicht satirisch 11. Oktober 2019 bei Twitter #OneMoreLaneWillFixIt #A100 https://x.com/ABCTV/status/1182468049011535872
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Aus Gründen: "Das bedeutet, dass Sie jetzt eine Menge Geld für sehr kurzfristigen Nutzen ausgeben."
#JevonsParadox: keine Death-Metal-Band, sondern #InducedDemand
Quelle: "abctv" (jetzt ABC Australia) leicht satirisch 11. Oktober 2019 bei Twitter #OneMoreLaneWillFixIt #A100 https://x.com/ABCTV/status/1182468049011535872
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This happens again and again. Efficiency improvements promise a green sustainable future, but end up delivering just more economic growth, equating more ecological destruction.
The more efficient something is, the cheaper it becomes, the more it will be used, with less care and consideration.
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This happens again and again. Efficiency improvements promise a green sustainable future, but end up delivering just more economic growth, equating more ecological destruction.
The more efficient something is, the cheaper it becomes, the more it will be used, with less care and consideration.
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The more we can deliver, the more resources we consume.
Animals "use efficiency to catalyze sprawl. […] The road to degrowth will require drastic social change."@blair_fix wrote: https://economicsfromthetopdown.com/2024/05/18/a-tour-of-the-jevons-paradox-how-energy-efficiency-backfires/ 🧵
#constraints #socialEngineering #tech #sprawl #efficiency #rebound #ReboundEffect #industry #electricity #data #dataViz #sustainability #engines #statistics #GHG #emissions #co2 #co2emissions #JevonsParadox #renewables #renewableEnergy #degrowth #electricVehicles #infrastructure
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The more we can deliver, the more resources we consume.
Animals "use efficiency to catalyze sprawl. […] The road to degrowth will require drastic social change."@blair_fix wrote: https://economicsfromthetopdown.com/2024/05/18/a-tour-of-the-jevons-paradox-how-energy-efficiency-backfires/ 🧵
#constraints #socialEngineering #tech #sprawl #efficiency #rebound #ReboundEffect #industry #electricity #data #dataViz #sustainability #engines #statistics #GHG #emissions #co2 #co2emissions #JevonsParadox #renewables #renewableEnergy #degrowth #electricVehicles #infrastructure
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If I had a band, I’d probably call it “Jevons Paradox.” (Check out the hashtag #JevonsParadox if you’re not sure what that is.) What would YOUR band name be?
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If I had a band, I’d probably call it “Jevons Paradox.” (Check out the hashtag #JevonsParadox if you’re not sure what that is.) What would YOUR band name be?
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Why “better vehicles” will never solve our congestion and pollution problems, and are (at most) part of the solution (remembering that they actually lead to more driving via #JevonsParadox). The more important part will always be fewer cars and less driving, fueled by better cities and more choices.
US drivers log 3.28 trillion m... -
Why “better vehicles” will never solve our congestion and pollution problems, and are (at most) part of the solution (remembering that they actually lead to more driving via #JevonsParadox). The more important part will always be fewer cars and less driving, fueled by better cities and more choices.
US drivers log 3.28 trillion m... -
“As self-driving companies pour billions of dollars into advancing their technology, it’s impossible to know how safe and energy-efficient their products could eventually become. But the #JevonsParadox… how much more driving will AVs induce — and will those added miles swamp any possible upside?”
What a 160-year-old theory abo... -
"As the climate crisis deepens, artificial intelligence (AI) has emerged as a contested force: some champion its potential to advance renewable energy, materials discovery, and large-scale emissions monitoring, while others underscore its growing carbon footprint, water consumption, and material resource demands. Much of this debate has concentrated on direct impact -- energy and water usage in data centers, e-waste from frequent hardware upgrades -- without addressing the significant indirect effects. This paper examines how the problem of Jevons' Paradox applies to AI, whereby efficiency gains may paradoxically spur increased consumption. We argue that understanding these second-order impacts requires an interdisciplinary approach, combining lifecycle assessments with socio-economic analyses. Rebound effects undermine the assumption that improved technical efficiency alone will ensure net reductions in environmental harm. Instead, the trajectory of AI's impact also hinges on business incentives and market logics, governance and policymaking, and broader social and cultural norms. We contend that a narrow focus on direct emissions misrepresents AI's true climate footprint, limiting the scope for meaningful interventions. We conclude with recommendations that address rebound effects and challenge the market-driven imperatives fueling uncontrolled AI growth. By broadening the analysis to include both direct and indirect consequences, we aim to inform a more comprehensive, evidence-based dialogue on AI's role in the climate crisis."
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"As the climate crisis deepens, artificial intelligence (AI) has emerged as a contested force: some champion its potential to advance renewable energy, materials discovery, and large-scale emissions monitoring, while others underscore its growing carbon footprint, water consumption, and material resource demands. Much of this debate has concentrated on direct impact -- energy and water usage in data centers, e-waste from frequent hardware upgrades -- without addressing the significant indirect effects. This paper examines how the problem of Jevons' Paradox applies to AI, whereby efficiency gains may paradoxically spur increased consumption. We argue that understanding these second-order impacts requires an interdisciplinary approach, combining lifecycle assessments with socio-economic analyses. Rebound effects undermine the assumption that improved technical efficiency alone will ensure net reductions in environmental harm. Instead, the trajectory of AI's impact also hinges on business incentives and market logics, governance and policymaking, and broader social and cultural norms. We contend that a narrow focus on direct emissions misrepresents AI's true climate footprint, limiting the scope for meaningful interventions. We conclude with recommendations that address rebound effects and challenge the market-driven imperatives fueling uncontrolled AI growth. By broadening the analysis to include both direct and indirect consequences, we aim to inform a more comprehensive, evidence-based dialogue on AI's role in the climate crisis."
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@nic221 @benlockwood Don’t forget Jevon’s Paradox.
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@nic221 @benlockwood Don’t forget Jevon’s Paradox.
