#rationing — Public Fediverse posts

How will universities ration internal access to LLMs?

I’m increasingly preoccupied by the question of how universities will cope with the impending reality of inference rationing. These firms are facing what Mills and Whittle describe as the AI pricing problem: “the prices generative AI companies must charge are higher than the prices consumers are likely willing to pay, given the value consumers receive from these products”. I’m increasingly convinced that inference is effectively being offered at a loss in ways that need to be at the centre of how we see LLMs within organisations: our access to AI is being subsidised and that subsidy is likely to end soon. Mills and Whittle break down the cost structure of labs providing access to their models:

• The cost of developing the models: the cost of building the infrastructure to train the models, the compute used in training and the labour costs of the developers
• The costs of making the models available: the development and labour costs of making the models available as software, building the infrastructure required for inference and the inference costs of how users utilise the models

When I’ve tried to raise this problem (in my own possibly less authoritative sociological register) I’ve inevitably met the belief that ‘technology will make it cheaper’. The most frequent example is DeepSeek but my understanding is that the aggressive use of synthetic data from frontier models was a huge part of reducing their training costs. They effectively skipped one of the costliest bits of the process by relying on other firms who had already done it. While there are undoubtedly technological developments which can reduce costs of training and inference, the parallel imperative towards pushing the frontier means bigger and more expensive models over time, at least for the large AI labs. That is the closest thing they have to a ‘moat’. So while technology will plausible reduce fixed costs in some dimensions, there are countervailing trends pushing up fixed costs in other dimensions. In other words it just seems obviously implausible to me that we see a significant reduction across the entire cost structure. It will remain extremely expensive to build, train and operate these models. Even if cost-per-token falls the labs will still have to claw back huge capital investments through inference pricing.

These aren’t reflected in huge subsidies at the moment to institutional users across public sector organisations, including the American government:

The GSA (2025b) has struck agreements with OpenAI and Anthropic to access their technologies for only $1 per agency, while Google will provide its Gemini for Government product at a cost of only $0.47 per agency, with xAI’s technologies costing only $0.42 per agency (GSA, 2025c). Microsoft is providing its Copilot product for free (GSA, 2025d).

If they are correct that profitable firms would have to charge more than consumers are willing to pay, that is a huge problem for the labs. It also means we’re likely to see a period of intense volatility when all manner of explicit and opaque strategies are used in order to experiment with different ways of fiddling with the overall cost structure. The nearest term one is going to be a shift from pricing by seat to pricing by inference at least once current contracts come to an end. But there will be other modes as well because AI labs are currently selling an extremely expensive service to organisations at a significant loss.

What does this mean for universities who have subscribed to enterprise AI? I can see three potential pathways here:

1. They exit from the space entirely leaving LLM-access a matter of staff and student individual preference. The information governance problem remains and the potential to work on culture and integrity is lost, but a huge cost is removed.
2. They pivot towards adapting open-weights models for sector-specific purposes. This would likely need to be consortium based due to the costs involved in getting it right, but it could be the best of both words in a sense.
3. They develop internal processes to distinguish between better or worse uses of LLMs which would ultimately entail a form of internal inference rationing. I suspect this would be just guidance initially but if normative prompting isn’t sufficient to reduce costs then at some point someone is going to start mapping inference onto cost centres within the university. An awful lot could flow from that, none of it good.

The easiest way out of this dilemma would be if staff and students simply don’t engage with the platform in the first place. There’s enough evidence of polarisation around enterprise AI and reluctance to trust in house provision of AI that enterprise platforms might just not take off in the first place. But if they do then I struggle to see any options other than the other three but this is a first speculative attempt to map out the issues here.

I’m thinking of organising a workshop about this. If you’re interested please get in touch!

How will universities ration internal access to LLMs?

I’m increasingly preoccupied by the question of how universities will cope with the impending reality of inference rationing. These firms are facing what Mills and Whittle describe as the AI pricing problem: “the prices generative AI companies must charge are higher than the prices consumers are likely willing to pay, given the value consumers receive from these products”. I’m increasingly convinced that inference is effectively being offered at a loss in ways that need to be at the centre of how we see LLMs within organisations: our access to AI is being subsidised and that subsidy is likely to end soon. Mills and Whittle break down the cost structure of labs providing access to their models:

• The cost of developing the models: the cost of building the infrastructure to train the models, the compute used in training and the labour costs of the developers
• The costs of making the models available: the development and labour costs of making the models available as software, building the infrastructure required for inference and the inference costs of how users utilise the models

When I’ve tried to raise this problem (in my own possibly less authoritative sociological register) I’ve inevitably met the belief that ‘technology will make it cheaper’. The most frequent example is DeepSeek but my understanding is that the aggressive use of synthetic data from frontier models was a huge part of reducing their training costs. They effectively skipped one of the costliest bits of the process by relying on other firms who had already done it. While there are undoubtedly technological developments which can reduce costs of training and inference, the parallel imperative towards pushing the frontier means bigger and more expensive models over time, at least for the large AI labs. That is the closest thing they have to a ‘moat’. So while technology will plausible reduce fixed costs in some dimensions, there are countervailing trends pushing up fixed costs in other dimensions. In other words it just seems obviously implausible to me that we see a significant reduction across the entire cost structure. It will remain extremely expensive to build, train and operate these models. Even if cost-per-token falls the labs will still have to claw back huge capital investments through inference pricing.

These aren’t reflected in huge subsidies at the moment to institutional users across public sector organisations, including the American government:

The GSA (2025b) has struck agreements with OpenAI and Anthropic to access their technologies for only $1 per agency, while Google will provide its Gemini for Government product at a cost of only $0.47 per agency, with xAI’s technologies costing only $0.42 per agency (GSA, 2025c). Microsoft is providing its Copilot product for free (GSA, 2025d).

If they are correct that profitable firms would have to charge more than consumers are willing to pay, that is a huge problem for the labs. It also means we’re likely to see a period of intense volatility when all manner of explicit and opaque strategies are used in order to experiment with different ways of fiddling with the overall cost structure. The nearest term one is going to be a shift from pricing by seat to pricing by inference at least once current contracts come to an end. But there will be other modes as well because AI labs are currently selling an extremely expensive service to organisations at a significant loss.

What does this mean for universities who have subscribed to enterprise AI? I can see three potential pathways here:

1. They exit from the space entirely leaving LLM-access a matter of staff and student individual preference. The information governance problem remains and the potential to work on culture and integrity is lost, but a huge cost is removed.
2. They pivot towards adapting open-weights models for sector-specific purposes. This would likely need to be consortium based due to the costs involved in getting it right, but it could be the best of both words in a sense.
3. They develop internal processes to distinguish between better or worse uses of LLMs which would ultimately entail a form of internal inference rationing. I suspect this would be just guidance initially but if normative prompting isn’t sufficient to reduce costs then at some point someone is going to start mapping inference onto cost centres within the university. An awful lot could flow from that, none of it good.

The easiest way out of this dilemma would be if staff and students simply don’t engage with the platform in the first place. There’s enough evidence of polarisation around enterprise AI and reluctance to trust in house provision of AI that enterprise platforms might just not take off in the first place. But if they do then I struggle to see any options other than the other three but this is a first speculative attempt to map out the issues here.

I’m thinking of organising a workshop about this. If you’re interested please get in touch!

How will universities ration internal access to LLMs?

I’m increasingly preoccupied by the question of how universities will cope with the impending reality of inference rationing. These firms are facing what Mills and Whittle describe as the AI pricing problem: “the prices generative AI companies must charge are higher than the prices consumers are likely willing to pay, given the value consumers receive from these products”. I’m increasingly convinced that inference is effectively being offered at a loss in ways that need to be at the centre of how we see LLMs within organisations: our access to AI is being subsidised and that subsidy is likely to end soon. Mills and Whittle break down the cost structure of labs providing access to their models:

• The cost of developing the models: the cost of building the infrastructure to train the models, the compute used in training and the labour costs of the developers
• The costs of making the models available: the development and labour costs of making the models available as software, building the infrastructure required for inference and the inference costs of how users utilise the models

When I’ve tried to raise this problem (in my own possibly less authoritative sociological register) I’ve inevitably met the belief that ‘technology will make it cheaper’. The most frequent example is DeepSeek but my understanding is that the aggressive use of synthetic data from frontier models was a huge part of reducing their training costs. They effectively skipped one of the costliest bits of the process by relying on other firms who had already done it. While there are undoubtedly technological developments which can reduce costs of training and inference, the parallel imperative towards pushing the frontier means bigger and more expensive models over time, at least for the large AI labs. That is the closest thing they have to a ‘moat’. So while technology will plausible reduce fixed costs in some dimensions, there are countervailing trends pushing up fixed costs in other dimensions. In other words it just seems obviously implausible to me that we see a significant reduction across the entire cost structure. It will remain extremely expensive to build, train and operate these models. Even if cost-per-token falls the labs will still have to claw back huge capital investments through inference pricing.

These aren’t reflected in huge subsidies at the moment to institutional users across public sector organisations, including the American government:

The GSA (2025b) has struck agreements with OpenAI and Anthropic to access their technologies for only $1 per agency, while Google will provide its Gemini for Government product at a cost of only $0.47 per agency, with xAI’s technologies costing only $0.42 per agency (GSA, 2025c). Microsoft is providing its Copilot product for free (GSA, 2025d).

If they are correct that profitable firms would have to charge more than consumers are willing to pay, that is a huge problem for the labs. It also means we’re likely to see a period of intense volatility when all manner of explicit and opaque strategies are used in order to experiment with different ways of fiddling with the overall cost structure. The nearest term one is going to be a shift from pricing by seat to pricing by inference at least once current contracts come to an end. But there will be other modes as well because AI labs are currently selling an extremely expensive service to organisations at a significant loss.

What does this mean for universities who have subscribed to enterprise AI? I can see three potential pathways here:

1. They exit from the space entirely leaving LLM-access a matter of staff and student individual preference. The information governance problem remains and the potential to work on culture and integrity is lost, but a huge cost is removed.
2. They pivot towards adapting open-weights models for sector-specific purposes. This would likely need to be consortium based due to the costs involved in getting it right, but it could be the best of both words in a sense.
3. They develop internal processes to distinguish between better or worse uses of LLMs which would ultimately entail a form of internal inference rationing. I suspect this would be just guidance initially but if normative prompting isn’t sufficient to reduce costs then at some point someone is going to start mapping inference onto cost centres within the university. An awful lot could flow from that, none of it good.

The easiest way out of this dilemma would be if staff and students simply don’t engage with the platform in the first place. There’s enough evidence of polarisation around enterprise AI and reluctance to trust in house provision of AI that enterprise platforms might just not take off in the first place. But if they do then I struggle to see any options other than the other three but this is a first speculative attempt to map out the issues here.

I’m thinking of organising a workshop about this. If you’re interested please get in touch!

How will universities ration internal access to LLMs?

I’m increasingly preoccupied by the question of how universities will cope with the impending reality of inference rationing. These firms are facing what Mills and Whittle describe as the AI pricing problem: “the prices generative AI companies must charge are higher than the prices consumers are likely willing to pay, given the value consumers receive from these products”. I’m increasingly convinced that inference is effectively being offered at a loss in ways that need to be at the centre of how we see LLMs within organisations: our access to AI is being subsidised and that subsidy is likely to end soon. Mills and Whittle break down the cost structure of labs providing access to their models:

• The cost of developing the models: the cost of building the infrastructure to train the models, the compute used in training and the labour costs of the developers
• The costs of making the models available: the development and labour costs of making the models available as software, building the infrastructure required for inference and the inference costs of how users utilise the models

When I’ve tried to raise this problem (in my own possibly less authoritative sociological register) I’ve inevitably met the belief that ‘technology will make it cheaper’. The most frequent example is DeepSeek but my understanding is that the aggressive use of synthetic data from frontier models was a huge part of reducing their training costs. They effectively skipped one of the costliest bits of the process by relying on other firms who had already done it. While there are undoubtedly technological developments which can reduce costs of training and inference, the parallel imperative towards pushing the frontier means bigger and more expensive models over time, at least for the large AI labs. That is the closest thing they have to a ‘moat’. So while technology will plausible reduce fixed costs in some dimensions, there are countervailing trends pushing up fixed costs in other dimensions. In other words it just seems obviously implausible to me that we see a significant reduction across the entire cost structure. It will remain extremely expensive to build, train and operate these models. Even if cost-per-token falls the labs will still have to claw back huge capital investments through inference pricing.

These aren’t reflected in huge subsidies at the moment to institutional users across public sector organisations, including the American government:

The GSA (2025b) has struck agreements with OpenAI and Anthropic to access their technologies for only $1 per agency, while Google will provide its Gemini for Government product at a cost of only $0.47 per agency, with xAI’s technologies costing only $0.42 per agency (GSA, 2025c). Microsoft is providing its Copilot product for free (GSA, 2025d).

If they are correct that profitable firms would have to charge more than consumers are willing to pay, that is a huge problem for the labs. It also means we’re likely to see a period of intense volatility when all manner of explicit and opaque strategies are used in order to experiment with different ways of fiddling with the overall cost structure. The nearest term one is going to be a shift from pricing by seat to pricing by inference at least once current contracts come to an end. But there will be other modes as well because AI labs are currently selling an extremely expensive service to organisations at a significant loss.

What does this mean for universities who have subscribed to enterprise AI? I can see three potential pathways here:

1. They exit from the space entirely leaving LLM-access a matter of staff and student individual preference. The information governance problem remains and the potential to work on culture and integrity is lost, but a huge cost is removed.
2. They pivot towards adapting open-weights models for sector-specific purposes. This would likely need to be consortium based due to the costs involved in getting it right, but it could be the best of both words in a sense.
3. They develop internal processes to distinguish between better or worse uses of LLMs which would ultimately entail a form of internal inference rationing. I suspect this would be just guidance initially but if normative prompting isn’t sufficient to reduce costs then at some point someone is going to start mapping inference onto cost centres within the university. An awful lot could flow from that, none of it good.

The easiest way out of this dilemma would be if staff and students simply don’t engage with the platform in the first place. There’s enough evidence of polarisation around enterprise AI and reluctance to trust in house provision of AI that enterprise platforms might just not take off in the first place. But if they do then I struggle to see any options other than the other three but this is a first speculative attempt to map out the issues here.

I’m thinking of organising a workshop about this. If you’re interested please get in touch!

Microsoft starts rationing AI tokens for its own engineers

Share if you found this interesting.

https://1ban.news/microsoft-token-rationing-engineers-2026/

#1ban #microsoft #token #rationing #engineers #tech

Thanks #Bibi!

Major #OilCompanies reap massive profits as US and Iran fighting drives energy prices higher

By CATHY BUSSEWITZ
Updated 11:11 AM EDT, July 31, 2026

NEW YORK (AP) — "American oil and gas giants raked in massive spring profits while fighting between Iran and the U.S. impeded petroleum shipments and consumers around the world paid more for fuel and confronted shortages.

"The conflict, now in its sixth month, halted most shipping through the Strait of Hormuz, a narrow waterway that previously served as a delivery route for a fifth of the world’s oil and natural gas. With global supplies constrained, prices for Brent crude, the international standard, soared from about $70 to above $100 a barrel for much of March, April and May, and at one point reached $126.

"The money that oil companies accrued between the beginning of April and the end of June could receive extra scrutiny this year. Gasoline, diesel and jet fuel prices climbed sharply during that period, increasing costs for drivers and airline passengers. Supplies ran low in some countries, leading to sporadic fuel rationing in #Australia and government office closures in #Nepal and #SriLanka.

" #ExxonMobil on Friday reported that its second quarter profits doubled to $14.53 billion, boosted by record diesel production. The oil giant, based in Spring, Texas, brought in $116.02 billion in revenue, up 42%.

" #Chevron, based in Houston, nearly quadrupled its profits to $12.07 billion and revenue jumped 56% to $70.06 billion.

"Six of #Europe’s largest oil companies posted combined first-quarter profits of $22 billion, more than 40% higher than last year.

" 'There are constituencies around the world who are having a very good crisis, and the oil producers are one of them,' said Patrick Galey, #FossilFuels lead at #GlobalWitness, a nonprofit organization that investigates environmental issues. 'When you compare that to the hundreds of millions of people who are struggling with #RollingBlackouts, with #ElectricityCurbs, #rationing, waiting in line for #FoodQueues, or the disruption to fertilizers and the potential impact that that has on food prices, we don’t think that it’s a justifiable price for the rest of the world to be paying.' "

Source:
https://apnews.com/article/oil-companies-profits-exxon-chevron-9375fbf8f6f40426f7428e07d54000c7

#USPol #WorldPol #USWarOnIran #EndlessWar #TrumpsWar #BibisWar #BibiIsAWarCriminal #TrumpIsAWarCriminal #BigOilAndGas #Oiligarchy #CorporateCriminals #CorporateColonialism

Thanks #Bibi!

Major #OilCompanies reap massive profits as US and Iran fighting drives energy prices higher

By CATHY BUSSEWITZ
Updated 11:11 AM EDT, July 31, 2026

NEW YORK (AP) — "American oil and gas giants raked in massive spring profits while fighting between Iran and the U.S. impeded petroleum shipments and consumers around the world paid more for fuel and confronted shortages.

"The conflict, now in its sixth month, halted most shipping through the Strait of Hormuz, a narrow waterway that previously served as a delivery route for a fifth of the world’s oil and natural gas. With global supplies constrained, prices for Brent crude, the international standard, soared from about $70 to above $100 a barrel for much of March, April and May, and at one point reached $126.

"The money that oil companies accrued between the beginning of April and the end of June could receive extra scrutiny this year. Gasoline, diesel and jet fuel prices climbed sharply during that period, increasing costs for drivers and airline passengers. Supplies ran low in some countries, leading to sporadic fuel rationing in #Australia and government office closures in #Nepal and #SriLanka.

" #ExxonMobil on Friday reported that its second quarter profits doubled to $14.53 billion, boosted by record diesel production. The oil giant, based in Spring, Texas, brought in $116.02 billion in revenue, up 42%.

" #Chevron, based in Houston, nearly quadrupled its profits to $12.07 billion and revenue jumped 56% to $70.06 billion.

"Six of #Europe’s largest oil companies posted combined first-quarter profits of $22 billion, more than 40% higher than last year.

" 'There are constituencies around the world who are having a very good crisis, and the oil producers are one of them,' said Patrick Galey, #FossilFuels lead at #GlobalWitness, a nonprofit organization that investigates environmental issues. 'When you compare that to the hundreds of millions of people who are struggling with #RollingBlackouts, with #ElectricityCurbs, #rationing, waiting in line for #FoodQueues, or the disruption to fertilizers and the potential impact that that has on food prices, we don’t think that it’s a justifiable price for the rest of the world to be paying.' "

Source:
https://apnews.com/article/oil-companies-profits-exxon-chevron-9375fbf8f6f40426f7428e07d54000c7

#USPol #WorldPol #USWarOnIran #EndlessWar #TrumpsWar #BibisWar #BibiIsAWarCriminal #TrumpIsAWarCriminal #BigOilAndGas #Oiligarchy #CorporateCriminals #CorporateColonialism

Thanks #Bibi!

Major #OilCompanies reap massive profits as US and Iran fighting drives energy prices higher

By CATHY BUSSEWITZ
Updated 11:11 AM EDT, July 31, 2026

NEW YORK (AP) — "American oil and gas giants raked in massive spring profits while fighting between Iran and the U.S. impeded petroleum shipments and consumers around the world paid more for fuel and confronted shortages.

"The conflict, now in its sixth month, halted most shipping through the Strait of Hormuz, a narrow waterway that previously served as a delivery route for a fifth of the world’s oil and natural gas. With global supplies constrained, prices for Brent crude, the international standard, soared from about $70 to above $100 a barrel for much of March, April and May, and at one point reached $126.

"The money that oil companies accrued between the beginning of April and the end of June could receive extra scrutiny this year. Gasoline, diesel and jet fuel prices climbed sharply during that period, increasing costs for drivers and airline passengers. Supplies ran low in some countries, leading to sporadic fuel rationing in #Australia and government office closures in #Nepal and #SriLanka.

" #ExxonMobil on Friday reported that its second quarter profits doubled to $14.53 billion, boosted by record diesel production. The oil giant, based in Spring, Texas, brought in $116.02 billion in revenue, up 42%.

" #Chevron, based in Houston, nearly quadrupled its profits to $12.07 billion and revenue jumped 56% to $70.06 billion.

"Six of #Europe’s largest oil companies posted combined first-quarter profits of $22 billion, more than 40% higher than last year.

" 'There are constituencies around the world who are having a very good crisis, and the oil producers are one of them,' said Patrick Galey, #FossilFuels lead at #GlobalWitness, a nonprofit organization that investigates environmental issues. 'When you compare that to the hundreds of millions of people who are struggling with #RollingBlackouts, with #ElectricityCurbs, #rationing, waiting in line for #FoodQueues, or the disruption to fertilizers and the potential impact that that has on food prices, we don’t think that it’s a justifiable price for the rest of the world to be paying.' "

Source:
https://apnews.com/article/oil-companies-profits-exxon-chevron-9375fbf8f6f40426f7428e07d54000c7

#USPol #WorldPol #USWarOnIran #EndlessWar #TrumpsWar #BibisWar #BibiIsAWarCriminal #TrumpIsAWarCriminal #BigOilAndGas #Oiligarchy #CorporateCriminals #CorporateColonialism

Thanks #Bibi!

Major #OilCompanies reap massive profits as US and Iran fighting drives energy prices higher

By CATHY BUSSEWITZ
Updated 11:11 AM EDT, July 31, 2026

NEW YORK (AP) — "American oil and gas giants raked in massive spring profits while fighting between Iran and the U.S. impeded petroleum shipments and consumers around the world paid more for fuel and confronted shortages.

"The conflict, now in its sixth month, halted most shipping through the Strait of Hormuz, a narrow waterway that previously served as a delivery route for a fifth of the world’s oil and natural gas. With global supplies constrained, prices for Brent crude, the international standard, soared from about $70 to above $100 a barrel for much of March, April and May, and at one point reached $126.

"The money that oil companies accrued between the beginning of April and the end of June could receive extra scrutiny this year. Gasoline, diesel and jet fuel prices climbed sharply during that period, increasing costs for drivers and airline passengers. Supplies ran low in some countries, leading to sporadic fuel rationing in #Australia and government office closures in #Nepal and #SriLanka.

" #ExxonMobil on Friday reported that its second quarter profits doubled to $14.53 billion, boosted by record diesel production. The oil giant, based in Spring, Texas, brought in $116.02 billion in revenue, up 42%.

" #Chevron, based in Houston, nearly quadrupled its profits to $12.07 billion and revenue jumped 56% to $70.06 billion.

"Six of #Europe’s largest oil companies posted combined first-quarter profits of $22 billion, more than 40% higher than last year.

" 'There are constituencies around the world who are having a very good crisis, and the oil producers are one of them,' said Patrick Galey, #FossilFuels lead at #GlobalWitness, a nonprofit organization that investigates environmental issues. 'When you compare that to the hundreds of millions of people who are struggling with #RollingBlackouts, with #ElectricityCurbs, #rationing, waiting in line for #FoodQueues, or the disruption to fertilizers and the potential impact that that has on food prices, we don’t think that it’s a justifiable price for the rest of the world to be paying.' "

Source:
https://apnews.com/article/oil-companies-profits-exxon-chevron-9375fbf8f6f40426f7428e07d54000c7

#USPol #WorldPol #USWarOnIran #EndlessWar #TrumpsWar #BibisWar #BibiIsAWarCriminal #TrumpIsAWarCriminal #BigOilAndGas #Oiligarchy #CorporateCriminals #CorporateColonialism

Thanks #Bibi!

Major #OilCompanies reap massive profits as US and Iran fighting drives energy prices higher

By CATHY BUSSEWITZ
Updated 11:11 AM EDT, July 31, 2026

NEW YORK (AP) — "American oil and gas giants raked in massive spring profits while fighting between Iran and the U.S. impeded petroleum shipments and consumers around the world paid more for fuel and confronted shortages.

"The conflict, now in its sixth month, halted most shipping through the Strait of Hormuz, a narrow waterway that previously served as a delivery route for a fifth of the world’s oil and natural gas. With global supplies constrained, prices for Brent crude, the international standard, soared from about $70 to above $100 a barrel for much of March, April and May, and at one point reached $126.

"The money that oil companies accrued between the beginning of April and the end of June could receive extra scrutiny this year. Gasoline, diesel and jet fuel prices climbed sharply during that period, increasing costs for drivers and airline passengers. Supplies ran low in some countries, leading to sporadic fuel rationing in #Australia and government office closures in #Nepal and #SriLanka.

" #ExxonMobil on Friday reported that its second quarter profits doubled to $14.53 billion, boosted by record diesel production. The oil giant, based in Spring, Texas, brought in $116.02 billion in revenue, up 42%.

" #Chevron, based in Houston, nearly quadrupled its profits to $12.07 billion and revenue jumped 56% to $70.06 billion.

"Six of #Europe’s largest oil companies posted combined first-quarter profits of $22 billion, more than 40% higher than last year.

" 'There are constituencies around the world who are having a very good crisis, and the oil producers are one of them,' said Patrick Galey, #FossilFuels lead at #GlobalWitness, a nonprofit organization that investigates environmental issues. 'When you compare that to the hundreds of millions of people who are struggling with #RollingBlackouts, with #ElectricityCurbs, #rationing, waiting in line for #FoodQueues, or the disruption to fertilizers and the potential impact that that has on food prices, we don’t think that it’s a justifiable price for the rest of the world to be paying.' "

Source:
https://apnews.com/article/oil-companies-profits-exxon-chevron-9375fbf8f6f40426f7428e07d54000c7

#USPol #WorldPol #USWarOnIran #EndlessWar #TrumpsWar #BibisWar #BibiIsAWarCriminal #TrumpIsAWarCriminal #BigOilAndGas #Oiligarchy #CorporateCriminals #CorporateColonialism

Rationing
by Kevin Ahern

Two roosters per man
I say to you
Are just too many
A cock a dude’ll do

#funny #comedy #laugh #silly #humor #humour #verse #poetry #poem #rationing #rooster #cock

“When you compare that to the hundreds of millions of people who are struggling with rolling #blackouts, with #electricity curbs, #rationing, waiting in line for #food queues, or the disruption to #fertilizers & the potential impact that that has on food #prices, we don’t think that it’s a justifiable price for the rest of the world to be paying,” Galey added.
#BigOil #WarProfiteering #FossilFuels #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #inflation #affordability #oil #energy

“When you compare that to the hundreds of millions of people who are struggling with rolling #blackouts, with #electricity curbs, #rationing, waiting in line for #food queues, or the disruption to #fertilizers & the potential impact that that has on food #prices, we don’t think that it’s a justifiable price for the rest of the world to be paying,” Galey added.
#BigOil #WarProfiteering #FossilFuels #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #inflation #affordability #oil #energy

“When you compare that to the hundreds of millions of people who are struggling with rolling #blackouts, with #electricity curbs, #rationing, waiting in line for #food queues, or the disruption to #fertilizers & the potential impact that that has on food #prices, we don’t think that it’s a justifiable price for the rest of the world to be paying,” Galey added.
#BigOil #WarProfiteering #FossilFuels #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #inflation #affordability #oil #energy

“When you compare that to the hundreds of millions of people who are struggling with rolling #blackouts, with #electricity curbs, #rationing, waiting in line for #food queues, or the disruption to #fertilizers & the potential impact that that has on food #prices, we don’t think that it’s a justifiable price for the rest of the world to be paying,” Galey added.
#BigOil #WarProfiteering #FossilFuels #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #inflation #affordability #oil #energy

“When you compare that to the hundreds of millions of people who are struggling with rolling #blackouts, with #electricity curbs, #rationing, waiting in line for #food queues, or the disruption to #fertilizers & the potential impact that that has on food #prices, we don’t think that it’s a justifiable price for the rest of the world to be paying,” Galey added.
#BigOil #WarProfiteering #FossilFuels #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #inflation #affordability #oil #energy

The money that #oil companies accrued between the beginning of April & the end of June could receive extra scrutiny this year. #Gasoline, #diesel & #JetFuel prices climbed sharply during that period, increasing costs for drivers & airline passengers. Supplies ran low in some countries, leading to sporadic #fuel #rationing in Australia & government office closures in Nepal & Sri Lanka.

#BigOil #WarProfiteering #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #affordability #energy

The money that #oil companies accrued between the beginning of April & the end of June could receive extra scrutiny this year. #Gasoline, #diesel & #JetFuel prices climbed sharply during that period, increasing costs for drivers & airline passengers. Supplies ran low in some countries, leading to sporadic #fuel #rationing in Australia & government office closures in Nepal & Sri Lanka.

#BigOil #WarProfiteering #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #affordability #energy

The money that #oil companies accrued between the beginning of April & the end of June could receive extra scrutiny this year. #Gasoline, #diesel & #JetFuel prices climbed sharply during that period, increasing costs for drivers & airline passengers. Supplies ran low in some countries, leading to sporadic #fuel #rationing in Australia & government office closures in Nepal & Sri Lanka.

#BigOil #WarProfiteering #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #affordability #energy

The money that #oil companies accrued between the beginning of April & the end of June could receive extra scrutiny this year. #Gasoline, #diesel & #JetFuel prices climbed sharply during that period, increasing costs for drivers & airline passengers. Supplies ran low in some countries, leading to sporadic #fuel #rationing in Australia & government office closures in Nepal & Sri Lanka.

#BigOil #WarProfiteering #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #affordability #energy

The money that #oil companies accrued between the beginning of April & the end of June could receive extra scrutiny this year. #Gasoline, #diesel & #JetFuel prices climbed sharply during that period, increasing costs for drivers & airline passengers. Supplies ran low in some countries, leading to sporadic #fuel #rationing in Australia & government office closures in Nepal & Sri Lanka.

#BigOil #WarProfiteering #ClimateChange #TrumpsWar #IranWar #US #Iran #Trump #economy #affordability #energy

I 100% guarantee the #rich #wealthy #millionaires #billionaires are getting the drugs before we plebs.

Shortage of #Chemotherapy #Drugs Brings #Rationing Fears

Doctors are contending with low supplies & unfilled orders of generic chemotherapy infusions that are crucial to the treatment of a long list of #cancers.

#FDT #Trump #tariffs #sanctions #law #healthcare #medicine #cancer #BigC
https://www.nytimes.com/2026/06/24/health/chemotherapy-drug-shortage.html?smid=nytcore-ios-share

I 100% guarantee the #rich #wealthy #millionaires #billionaires are getting the drugs before we plebs.

Shortage of #Chemotherapy #Drugs Brings #Rationing Fears

Doctors are contending with low supplies & unfilled orders of generic chemotherapy infusions that are crucial to the treatment of a long list of #cancers.

#FDT #Trump #tariffs #sanctions #law #healthcare #medicine #cancer #BigC
https://www.nytimes.com/2026/06/24/health/chemotherapy-drug-shortage.html?smid=nytcore-ios-share

I 100% guarantee the #rich #wealthy #millionaires #billionaires are getting the drugs before we plebs.

Shortage of #Chemotherapy #Drugs Brings #Rationing Fears

Doctors are contending with low supplies & unfilled orders of generic chemotherapy infusions that are crucial to the treatment of a long list of #cancers.

#FDT #Trump #tariffs #sanctions #law #healthcare #medicine #cancer #BigC
https://www.nytimes.com/2026/06/24/health/chemotherapy-drug-shortage.html?smid=nytcore-ios-share

I 100% guarantee the #rich #wealthy #millionaires #billionaires are getting the drugs before we plebs.

Shortage of #Chemotherapy #Drugs Brings #Rationing Fears

Doctors are contending with low supplies & unfilled orders of generic chemotherapy infusions that are crucial to the treatment of a long list of #cancers.

#FDT #Trump #tariffs #sanctions #law #healthcare #medicine #cancer #BigC
https://www.nytimes.com/2026/06/24/health/chemotherapy-drug-shortage.html?smid=nytcore-ios-share

I 100% guarantee the #rich #wealthy #millionaires #billionaires are getting the drugs before we plebs.

Shortage of #Chemotherapy #Drugs Brings #Rationing Fears

Doctors are contending with low supplies & unfilled orders of generic chemotherapy infusions that are crucial to the treatment of a long list of #cancers.

#FDT #Trump #tariffs #sanctions #law #healthcare #medicine #cancer #BigC
https://www.nytimes.com/2026/06/24/health/chemotherapy-drug-shortage.html?smid=nytcore-ios-share

😂 Uber's #AI #budget went poof in four months, so now they're #rationing #AI #tokens like it's the apocalypse! 💸 Because clearly, advanced AI needs to be managed like a #digital #lemonade #stand. 🍋🚗
https://simonwillison.net/2026/Jun/3/uber-caps-usage/ #Uber #comedy #HackerNews #ngated

😂 Uber's #AI #budget went poof in four months, so now they're #rationing #AI #tokens like it's the apocalypse! 💸 Because clearly, advanced AI needs to be managed like a #digital #lemonade #stand. 🍋🚗
https://simonwillison.net/2026/Jun/3/uber-caps-usage/ #Uber #comedy #HackerNews #ngated

😂 Uber's #AI #budget went poof in four months, so now they're #rationing #AI #tokens like it's the apocalypse! 💸 Because clearly, advanced AI needs to be managed like a #digital #lemonade #stand. 🍋🚗
https://simonwillison.net/2026/Jun/3/uber-caps-usage/ #Uber #comedy #HackerNews #ngated

😂 Uber's #AI #budget went poof in four months, so now they're #rationing #AI #tokens like it's the apocalypse! 💸 Because clearly, advanced AI needs to be managed like a #digital #lemonade #stand. 🍋🚗
https://simonwillison.net/2026/Jun/3/uber-caps-usage/ #Uber #comedy #HackerNews #ngated

😂 Uber's #AI #budget went poof in four months, so now they're #rationing #AI #tokens like it's the apocalypse! 💸 Because clearly, advanced AI needs to be managed like a #digital #lemonade #stand. 🍋🚗
https://simonwillison.net/2026/Jun/3/uber-caps-usage/ #Uber #comedy #HackerNews #ngated

Corporate America Is Starting to Ration AI as Cost Skyrockets

https://www.wsj.com/tech/ai/corporate-america-is-starting-to-ration-ai-as-cost-skyrockets-1eb99d7a

#HackerNews #CorporateAmerica #AI #Rationing #CostSkyrockets #TechTrends

Corporate America Is Starting to Ration AI as Cost Skyrockets

https://www.wsj.com/tech/ai/corporate-america-is-starting-to-ration-ai-as-cost-skyrockets-1eb99d7a

#HackerNews #CorporateAmerica #AI #Rationing #CostSkyrockets #TechTrends

Corporate America Is Starting to Ration AI as Cost Skyrockets

https://www.wsj.com/tech/ai/corporate-america-is-starting-to-ration-ai-as-cost-skyrockets-1eb99d7a

#HackerNews #CorporateAmerica #AI #Rationing #CostSkyrockets #TechTrends

Corporate America Is Starting to Ration AI as Cost Skyrockets

https://www.wsj.com/tech/ai/corporate-america-is-starting-to-ration-ai-as-cost-skyrockets-1eb99d7a

#HackerNews #CorporateAmerica #AI #Rationing #CostSkyrockets #TechTrends

Corporate America Is Starting to Ration AI as Cost Skyrockets

https://www.wsj.com/tech/ai/corporate-america-is-starting-to-ration-ai-as-cost-skyrockets-1eb99d7a

#HackerNews #CorporateAmerica #AI #Rationing #CostSkyrockets #TechTrends

https://www.theguardian.com/society/2026/may/18/nhs-nurses-believe-lack-of-staff-putting-patients-at-risk-survey-finds. I'm quite sure it is - but then, the #NHS has been underfunded for years, & I speak as someone who wrote an MA dissertation & PhD thesis on the subject of #healthcare #rationing in the #UK, @ChrisMayLA6.

https://www.theguardian.com/society/2026/may/18/nhs-nurses-believe-lack-of-staff-putting-patients-at-risk-survey-finds. I'm quite sure it is - but then, the #NHS has been underfunded for years, & I speak as someone who wrote an MA dissertation & PhD thesis on the subject of #healthcare #rationing in the #UK, @ChrisMayLA6.

https://www.theguardian.com/society/2026/may/18/nhs-nurses-believe-lack-of-staff-putting-patients-at-risk-survey-finds. I'm quite sure it is - but then, the #NHS has been underfunded for years, & I speak as someone who wrote an MA dissertation & PhD thesis on the subject of #healthcare #rationing in the #UK, @ChrisMayLA6.

https://www.theguardian.com/society/2026/may/18/nhs-nurses-believe-lack-of-staff-putting-patients-at-risk-survey-finds. I'm quite sure it is - but then, the #NHS has been underfunded for years, & I speak as someone who wrote an MA dissertation & PhD thesis on the subject of #healthcare #rationing in the #UK, @ChrisMayLA6.

https://www.theguardian.com/society/2026/may/18/nhs-nurses-believe-lack-of-staff-putting-patients-at-risk-survey-finds. I'm quite sure it is - but then, the #NHS has been underfunded for years, & I speak as someone who wrote an MA dissertation & PhD thesis on the subject of #healthcare #rationing in the #UK, @ChrisMayLA6.

Some of you might be interested in this.. a blog with a lot of recipes based on UK wartime food rations with copies of the original leaflets from Ministry of Food. #1940s #1940sExperiment #recipes #FrugalFood #WW2 #rationing https://the1940sexperiment.com/

Some of you might be interested in this.. a blog with a lot of recipes based on UK wartime food rations with copies of the original leaflets from Ministry of Food. #1940s #1940sExperiment #recipes #FrugalFood #WW2 #rationing https://the1940sexperiment.com/

Some of you might be interested in this.. a blog with a lot of recipes based on UK wartime food rations with copies of the original leaflets from Ministry of Food. #1940s #1940sExperiment #recipes #FrugalFood #WW2 #rationing https://the1940sexperiment.com/

Some of you might be interested in this.. a blog with a lot of recipes based on UK wartime food rations with copies of the original leaflets from Ministry of Food. #1940s #1940sExperiment #recipes #FrugalFood #WW2 #rationing https://the1940sexperiment.com/

Some of you might be interested in this.. a blog with a lot of recipes based on UK wartime food rations with copies of the original leaflets from Ministry of Food. #1940s #1940sExperiment #recipes #FrugalFood #WW2 #rationing https://the1940sexperiment.com/

Even if Americans can somehow wrestle Donald Trump to end the #usisraelwaroniran next week, it is possible #fuel #rationing could be in by autumn, and supply chain failures could follow. We are already in trouble, but it’s not visible yet.

And to make it worse, I think the far right thinks it will win when people revolt and there is chaos, so it’s pushing ahead with this delayed-onset crisis nevertheless.

My advice is to learn to cook with potatoes and cabbage for next winter.. 🤔😕

Even if Americans can somehow wrestle Donald Trump to end the #usisraelwaroniran next week, it is possible #fuel #rationing could be in by autumn, and supply chain failures could follow. We are already in trouble, but it’s not visible yet.

And to make it worse, I think the far right thinks it will win when people revolt and there is chaos, so it’s pushing ahead with this delayed-onset crisis nevertheless.

My advice is to learn to cook with potatoes and cabbage for next winter.. 🤔😕

Even if Americans can somehow wrestle Donald Trump to end the #usisraelwaroniran next week, it is possible #fuel #rationing could be in by autumn, and supply chain failures could follow. We are already in trouble, but it’s not visible yet.

And to make it worse, I think the far right thinks it will win when people revolt and there is chaos, so it’s pushing ahead with this delayed-onset crisis nevertheless.

My advice is to learn to cook with potatoes and cabbage for next winter.. 🤔😕

Even if Americans can somehow wrestle Donald Trump to end the #usisraelwaroniran next week, it is possible #fuel #rationing could be in by autumn, and supply chain failures could follow. We are already in trouble, but it’s not visible yet.

And to make it worse, I think the far right thinks it will win when people revolt and there is chaos, so it’s pushing ahead with this delayed-onset crisis nevertheless.

My advice is to learn to cook with potatoes and cabbage for next winter.. 🤔😕

Even if Americans can somehow wrestle Donald Trump to end the #usisraelwaroniran next week, it is possible #fuel #rationing could be in by autumn, and supply chain failures could follow. We are already in trouble, but it’s not visible yet.

And to make it worse, I think the far right thinks it will win when people revolt and there is chaos, so it’s pushing ahead with this delayed-onset crisis nevertheless.

My advice is to learn to cook with potatoes and cabbage for next winter.. 🤔😕

UK businesses brace for jet fuel rationing

https://bmmagazine.co.uk/news/uk-jet-fuel-shortage-rationing-goldman-sachs-warning/

#HackerNews #UKbusinesses #jetfuel #rationing #news #GoldmanSachs #warning #fuelshortage

UK businesses brace for jet fuel rationing

https://bmmagazine.co.uk/news/uk-jet-fuel-shortage-rationing-goldman-sachs-warning/

#HackerNews #UKbusinesses #jetfuel #rationing #news #GoldmanSachs #warning #fuelshortage

UK businesses brace for jet fuel rationing

https://bmmagazine.co.uk/news/uk-jet-fuel-shortage-rationing-goldman-sachs-warning/

#HackerNews #UKbusinesses #jetfuel #rationing #news #GoldmanSachs #warning #fuelshortage

UK businesses brace for jet fuel rationing

https://bmmagazine.co.uk/news/uk-jet-fuel-shortage-rationing-goldman-sachs-warning/

#HackerNews #UKbusinesses #jetfuel #rationing #news #GoldmanSachs #warning #fuelshortage