8 ms·

The Economics of Recursive Self-Improvement [pdf]

149 points by apsec112 2mo ago

zuzuen_1 2mo ago
"We make a tentative calibration of the self-sustaining ac celeration condition using the existing data that is available, measuring AI capabilities using the Epoch Capabilities Index (Ho et al., 2025). We find that the condition is met if a one-unit increase in AI model capabilities results in at least 15% higher AI R&D pro ductivity. A rough back-of-the-envelope calculation based on reported AI engineer uplift suggests this return has been around 9% since the launch of coding agents. This number is below the model-implied threshold, suggesting we are not experiencing a self-sustaining acceleration." And the source of this data seems to be self-reported productivity gains from surveys: 1.4–2X in METR’s survey of technical workers (Becker, 2026). A bit flimsy basis but an interesting paper nonetheless.
- lumost 2mo ago
  I do wonder if the productivity gains control for increased bug findings and token costs.
Mistletoe 2mo ago
When I hear recursive self improvement all I remember are the ridiculous articles a few years ago about how 3d printers were going to make themselves and take over the world.
- anthonyrstevens 2mo ago
  So because some optimistic wacko said something implausible in the past you dismiss the entire topic and have nothing to contribute to the conversation. Gotcha.
vatsachak 2mo ago
RSI isn't anything new though; computers have been used to make computers better for about 80 years now. Imagine having a secretary who could read 1 million records and give you back your answer in 100 microseconds, for just 10 cents an hour. That's Postgres. So I'd imagine that if R&D can be automated, everything becomes better and cheaper but we'd all lose our jobs, as secretaries did to postgres. UBI season
- eru 2mo ago
  > Imagine having a secretary who could read 1 million records and give you back your answer in 100 microseconds, for just 10 cents an hour. That's Postgres. Well, that secretary can only answer very specific questions in a rather peculiar format. > [...] but we'd all lose our jobs, as secretaries did to postgres. I doubt many secretaries were replaced by postgres. However, you might like reading about https://en.wikipedia.org/wiki/Unit_record_equipment https://en.wikipedia.org/wiki/Unit_record_equipment
  - inglor_cz 2mo ago
    "I doubt many secretaries were replaced by postgres." The maximal relative share of typists, secretaries, admin assistants et al. in the US workforce was 4% and this apogee was reached in 1980 after ~ 100 years of sustained growth. In 1980, the curve bent and started declining as systematically as it used to rise. Now it is less than half of that. So are other office roles. https://forklightning.substack.com/p/the-past-present-and-future-of-office https://forklightning.substack.com/p/the-past-present-and-fu... (Look at the "The Rise and Fall of Office Work" graph in the middle of the page.) Given the neat correlation with the tech revolution, I'd be surprised if there wasn't a causal relation. Maybe not exactly with Postgres, but with automation in general. Data collection and management does not involve nearly as many people as it once did.
    - eru 2mo ago
      > Data collection and management does not involve nearly as many people as it once did. Yes, hence my link to the cardboard fueled data processing and storage.
- goatlover 2mo ago
  That would be a failure of imagination when it comes to everything secretaries actually do. Which is a problem with the idea that AI is coming for all our jobs anytime soon. It totally undersells everything humans do on the job.
  - 2mo ago
reader9274 2mo ago
First thing I thought when reading the title was "is this about those never ending self-help books?"
- blitzar 2mo ago
  What happens when self-help books read self-help books that read self-help books is what you see on linkedin.
joka88xj 2mo ago
[flagged]
charcircuit 2mo ago
>Best evidence in favor of acceleration: It's important to recognize that LLMs accelerating development of LLMs does not imply it will lead to self-sustaining acceleration.
godelski 2mo ago
> But our models make it clear that such an [intelligence] explosion may not follow if there are diminishing returns (“ideas become harder to find”) or if feedback loops become bottlenecked. How is this not obvious to everyone? As we advance it becomes more difficult to advance. You obviously make most advancements around the things that are easiest to improve. Then all the easy things are done. So you go onto the next easiest things. They're "the easy things" from that standpoint but that doesn't mean they aren't harder than "the easy things" when you started. Complexity increases as precision increases.
- EarlKing 2mo ago
  > How is this not obvious to everyone? Because everyone's thinking around intelligence is incredibly muddled by a variety of factors, and no one is particularly motivated to actually correct anyone's mistaken notions on the matter.
  - godelski 2mo ago
    I'm conflicted. On one hand I think we should more openly call people idiots and push back. On the other hand there's Descartes argument for idiots in good company. I just wish all the people that claimed to care only about truth would actually care about truth. Feels like society is more that trope where someone says a joke to a crowd and no one hears it except one charismatic person who repeats it and gets all the laughs. In reality it feels like the repeated version of the joke doesn't even make sense, it is just vibes.
- red75prime 2mo ago
  > How is this not obvious to everyone? That RSI can be bottlenecked? I guess this is obvious to many people. Whether RSI will be bottlenecked (at some not very interesting stage) is another question.
  - RandomLensman 2mo ago
    Why would it not be bottlenecked? Is intelligence so valuable as such?
reducesuffering 2mo ago
Reminder that while there are many naysayers who have been on the wrong side of AGI development progress the last decade… There are two $1T companies who are all-in on RSI internally right now. They are supported by $20T of market cap plowing R&D into their efforts. You can think it’s dumb money at your own peril, however the market rewards intelligent allocation…
- baq 2mo ago
  The market can also be quick and brutal to punish mistakes, especially when leverage is high. We can be in 1998, but we can be in 1995; you stand to make a ton of money if you know which one we’re in
- goatlover 2mo ago
  How do the markets know it's intelligent allocation before RSI is actually a thing? What makes those companies immune to failure?
  - not-a-llm 2mo ago
    them having an actual product with huge demand makes them immune Just like Tesla was immune from all the naysayers which were saying its a highly unprofitable company which will 100% go bankrupt because its economics dont make any sense, and they lost huge amounts of money shorting the stock
    - yorwba 2mo ago
      Tesla is profitable, but income per share has been very low relative to share price. People who were short Tesla weren't necessarily betting on a bankruptcy, just that shareholders wouldn't put up with the low ROI for much longer. And depending on exactly when they shorted it, they might've actually made a profit. In contrast, AI companies that are actually unprofitable are dependent on continuously raising additional money to sustain their operations, so a sudden drop in market confidence could become a self-fulfilling prophecy as it makes it more difficult to raise money which makes the business more risky which decreases market confidence in a downward spiral. An actual product with huge demand is not enough to avert bankruptcy, you also need to serve that demand profitably (like Tesla does).
LoMoGan 2mo ago
[dead]
drdrek 2mo ago
I love that Sci-Fi fan-fiction is having a moment <3
1317 2mo ago
NB this is about AI, not about improving your self
khalic 2mo ago
No DOI?
casey2 2mo ago
Notice: viXra.org only accepts scholarly articles written without AI assistance. Please go to ai.viXra.org to submit new scholarly article written with AI assistance or rxiVerse.org to submit new research article written with or without AI assistance.

149 points by apsec112 2mo ago

"We make a tentative calibration of the self-sustaining ac celeration condition using the existing data that is available, measuring AI capabilities using the Epoch Capabilities Index (Ho et al., 2025). We find that the condition is met if a one-unit increase in AI model capabilities results in at least 15% higher AI R&D pro ductivity. A rough back-of-the-envelope calculation based on reported AI engineer uplift suggests this return has been around 9% since the launch of coding agents. This number is below the model-implied threshold, suggesting we are not experiencing a self-sustaining acceleration." And the source of this data seems to be self-reported productivity gains from surveys: 1.4–2X in METR’s survey of technical workers (Becker, 2026). A bit flimsy basis but an interesting paper nonetheless.

lumost 2mo ago
I do wonder if the productivity gains control for increased bug findings and token costs.

Mistletoe 2mo ago

When I hear recursive self improvement all I remember are the ridiculous articles a few years ago about how 3d printers were going to make themselves and take over the world.

anthonyrstevens 2mo ago
So because some optimistic wacko said something implausible in the past you dismiss the entire topic and have nothing to contribute to the conversation. Gotcha.

vatsachak 2mo ago

RSI isn't anything new though; computers have been used to make computers better for about 80 years now. Imagine having a secretary who could read 1 million records and give you back your answer in 100 microseconds, for just 10 cents an hour. That's Postgres. So I'd imagine that if R&D can be automated, everything becomes better and cheaper but we'd all lose our jobs, as secretaries did to postgres. UBI season

eru 2mo ago
> Imagine having a secretary who could read 1 million records and give you back your answer in 100 microseconds, for just 10 cents an hour. That's Postgres. Well, that secretary can only answer very specific questions in a rather peculiar format. > [...] but we'd all lose our jobs, as secretaries did to postgres. I doubt many secretaries were replaced by postgres. However, you might like reading about https://en.wikipedia.org/wiki/Unit_record_equipment https://en.wikipedia.org/wiki/Unit_record_equipment
- inglor_cz 2mo ago
  "I doubt many secretaries were replaced by postgres." The maximal relative share of typists, secretaries, admin assistants et al. in the US workforce was 4% and this apogee was reached in 1980 after ~ 100 years of sustained growth. In 1980, the curve bent and started declining as systematically as it used to rise. Now it is less than half of that. So are other office roles. https://forklightning.substack.com/p/the-past-present-and-future-of-office https://forklightning.substack.com/p/the-past-present-and-fu... (Look at the "The Rise and Fall of Office Work" graph in the middle of the page.) Given the neat correlation with the tech revolution, I'd be surprised if there wasn't a causal relation. Maybe not exactly with Postgres, but with automation in general. Data collection and management does not involve nearly as many people as it once did.
  - eru 2mo ago
    > Data collection and management does not involve nearly as many people as it once did. Yes, hence my link to the cardboard fueled data processing and storage.
goatlover 2mo ago
That would be a failure of imagination when it comes to everything secretaries actually do. Which is a problem with the idea that AI is coming for all our jobs anytime soon. It totally undersells everything humans do on the job.
- 2mo ago

reader9274 2mo ago

First thing I thought when reading the title was "is this about those never ending self-help books?"

blitzar 2mo ago
What happens when self-help books read self-help books that read self-help books is what you see on linkedin.

joka88xj 2mo ago

[flagged]

charcircuit 2mo ago

>Best evidence in favor of acceleration: It's important to recognize that LLMs accelerating development of LLMs does not imply it will lead to self-sustaining acceleration.

godelski 2mo ago

> But our models make it clear that such an [intelligence] explosion may not follow if there are diminishing returns (“ideas become harder to find”) or if feedback loops become bottlenecked. How is this not obvious to everyone? As we advance it becomes more difficult to advance. You obviously make most advancements around the things that are easiest to improve. Then all the easy things are done. So you go onto the next easiest things. They're "the easy things" from that standpoint but that doesn't mean they aren't harder than "the easy things" when you started. Complexity increases as precision increases.

EarlKing 2mo ago
> How is this not obvious to everyone? Because everyone's thinking around intelligence is incredibly muddled by a variety of factors, and no one is particularly motivated to actually correct anyone's mistaken notions on the matter.
- godelski 2mo ago
  I'm conflicted. On one hand I think we should more openly call people idiots and push back. On the other hand there's Descartes argument for idiots in good company. I just wish all the people that claimed to care only about truth would actually care about truth. Feels like society is more that trope where someone says a joke to a crowd and no one hears it except one charismatic person who repeats it and gets all the laughs. In reality it feels like the repeated version of the joke doesn't even make sense, it is just vibes.
red75prime 2mo ago
> How is this not obvious to everyone? That RSI can be bottlenecked? I guess this is obvious to many people. Whether RSI will be bottlenecked (at some not very interesting stage) is another question.
- RandomLensman 2mo ago
  Why would it not be bottlenecked? Is intelligence so valuable as such?

reducesuffering 2mo ago

Reminder that while there are many naysayers who have been on the wrong side of AGI development progress the last decade… There are two $1T companies who are all-in on RSI internally right now. They are supported by $20T of market cap plowing R&D into their efforts. You can think it’s dumb money at your own peril, however the market rewards intelligent allocation…

baq 2mo ago
The market can also be quick and brutal to punish mistakes, especially when leverage is high. We can be in 1998, but we can be in 1995; you stand to make a ton of money if you know which one we’re in
goatlover 2mo ago
How do the markets know it's intelligent allocation before RSI is actually a thing? What makes those companies immune to failure?
- not-a-llm 2mo ago
  them having an actual product with huge demand makes them immune Just like Tesla was immune from all the naysayers which were saying its a highly unprofitable company which will 100% go bankrupt because its economics dont make any sense, and they lost huge amounts of money shorting the stock
  - yorwba 2mo ago
    Tesla is profitable, but income per share has been very low relative to share price. People who were short Tesla weren't necessarily betting on a bankruptcy, just that shareholders wouldn't put up with the low ROI for much longer. And depending on exactly when they shorted it, they might've actually made a profit. In contrast, AI companies that are actually unprofitable are dependent on continuously raising additional money to sustain their operations, so a sudden drop in market confidence could become a self-fulfilling prophecy as it makes it more difficult to raise money which makes the business more risky which decreases market confidence in a downward spiral. An actual product with huge demand is not enough to avert bankruptcy, you also need to serve that demand profitably (like Tesla does).

LoMoGan 2mo ago

[dead]

drdrek 2mo ago

I love that Sci-Fi fan-fiction is having a moment <3

1317 2mo ago

NB this is about AI, not about improving your self

khalic 2mo ago

No DOI?

casey2 2mo ago

Notice: viXra.org only accepts scholarly articles written without AI assistance. Please go to ai.viXra.org to submit new scholarly article written with AI assistance or rxiVerse.org to submit new research article written with or without AI assistance.