<description>This blog is the best explanation of AI intelligence increase I've seen: https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/

### Defining Market Bubbles

- Traditional definition: 20%+ share price decline with economic slowdown/recession
- Alternative perspective: hype/story not matching reality over time (dot-com example)
- Duncan’s view: share prices ahead of future expectations
  - Share prices predict future revenue/profit
  - Decline when reality falls short of predictions

### Historical Bubble Context

- Recent cycles analyzed:
  - COVID (2020) - pandemic-led, quickly reversed with government intervention
  - GFC (2008) - housing bubble, financial crisis, deeper impact
  - Tech bubble (1999) - NASDAQ fell 80%, expectations vs reality mismatch
  - S&amp;L crisis (1992) - mini financial crisis
  - Volcker era (1980s) - interest rates raised to break inflation

### Current AI Market Dynamics

- OpenAI: fastest growing startup ever, $20B revenue run rate in 2 years
- Anthropic: grew from $1B to $9B revenue run rate this year
- Big tech revenue acceleration through AI-improved ad platform ROI
- Key concern: if growth rates plateau, valuations become unsustainable

### Nvidia as Market Bellwether

- Central position providing GPUs for data center buildout
- Recent earnings beat analyst expectations but share price fell
- Market expectations vs analyst expectations are different metrics
- 80% of market money judged on 12-month performance vs long-term value creation

### AI Technology Scaling Laws

- Intelligence capability doubling every 7 months for 6 years
- Progress from 2-second tasks to 90-minute complex programming tasks
- Cost per token declining 100x annually on frontier models
- Current trajectory: potential for year-long human-equivalent tasks by 2028

### Investment Scale and Infrastructure

- $3 trillion committed to data center construction this year
- Power becoming primary bottleneck (not chip supply)
- 500-acre solar farms being built around data centers
- 7-year backlog on gas turbines, solar+battery fastest deployment option

### Bubble vs Boom Scenarios

- Bear case: scaling laws plateau, power constraints limit growth
  - Short-term revenue slowdown despite long-term potential
  - Circular investment dependencies create domino effect
- Bull case: scaling laws continue, GDP growth accelerates to 5%+
  - Current 100% GPU utilization indicates strong demand
  - Structural productivity gains justify investment levels

### Market Structure Risks

- Foundation model layer: 4 roughly equal competitors (OpenAI, Anthropic, Google, XAI)
  - No clear “winner takes all” dynamic emerging
  - Private company valuations hard to access for retail investors
- Application layer: less concentrated, easier to build sustainable businesses
- Chip layer: Nvidia dominance but Google TPUs showing competitive performance</description>

This blog is the best explanation of AI intellige…

This blog is the best explanation of AI intelligence increase I've seen: https://metr.org/blog/2025-03-19-measuring-ai-ability-to-complete-long-tasks/

### Defining Market Bubbles

- Traditional definition: 20%+ share price decline with economic slowdown/recession
- Alternative perspective: hype/story not matching reality over time (dot-com example)
- Duncan’s view: share prices ahead of future expectations
  - Share prices predict future revenue/profit
  - Decline when reality falls short of predictions

### Historical Bubble Context

- Recent cycles analyzed:
  - COVID (2020) - pandemic-led, quickly reversed with government intervention
  - GFC (2008) - housing bubble, financial crisis, deeper impact
  - Tech bubble (1999) - NASDAQ fell 80%, expectations vs reality mismatch
  - S&L crisis (1992) - mini financial crisis
  - Volcker era (1980s) - interest rates raised to break inflation

### Current AI Market Dynamics

- OpenAI: fastest growing startup ever, $20B revenue run rate in 2 years
- Anthropic: grew from $1B to $9B revenue run rate this year
- Big tech revenue acceleration through AI-improved ad platform ROI
- Key concern: if growth rates plateau, valuations become unsustainable

### Nvidia as Market Bellwether

- Central position providing GPUs for data center buildout
- Recent earnings beat analyst expectations but share price fell
- Market expectations vs analyst expectations are different metrics
- 80% of market money judged on 12-month performance vs long-term value creation

### AI Technology Scaling Laws

- Intelligence capability doubling every 7 months for 6 years
- Progress from 2-second tasks to 90-minute complex programming tasks
- Cost per token declining 100x annually on frontier models
- Current trajectory: potential for year-long human-equivalent tasks by 2028

### Investment Scale and Infrastructure

- $3 trillion committed to data center construction this year
- Power becoming primary bottleneck (not chip supply)
- 500-acre solar farms being built around data centers
- 7-year backlog on gas turbines, solar+battery fastest deployment option

### Bubble vs Boom Scenarios

- Bear case: scaling laws plateau, power constraints limit growth
  - Short-term revenue slowdown despite long-term potential
  - Circular investment dependencies create domino effect
- Bull case: scaling laws continue, GDP growth accelerates to 5%+
  - Current 100% GPU utilization indicates strong demand
  - Structural productivity gains justify investment levels

### Market Structure Risks

- Foundation model layer: 4 roughly equal competitors (OpenAI, Anthropic, Google, XAI)
  - No clear “winner takes all” dynamic emerging
  - Private company valuations hard to access for retail investors
- Application layer: less concentrated, easier to build sustainable businesses
- Chip layer: Nvidia dominance but Google TPUs showing competitive performance

92. Is there an AI bubble? Thoughts On What Markets Are Really Pricing In. Mentioning Warren Buffet, Paul Volcker, Larry Page  & More

<description>https://a16z.com/the-techno-optimist-manifesto/

"
Techno-optimism is the belief that rapid technological progress is the main driver of human prosperity and should be pursued as a moral imperative. It argues that:

Growth = Good: Innovation creates abundance, longer lives, and better living standards.

Barriers = Bad: Regulation, caution, and pessimism slow down progress and should be resisted.

Technology as Solution: Challenges like poverty, disease, and climate change are best solved by accelerating science and technology rather than restricting them.

In short: Techno-optimism sees faster innovation as the surest path to human flourishing — and treats resistance to technological progress as harmful.
"

Here’s a structured overview of the major schools of economic thought, mapped across time, followed by an estimate of which views dominate public and policy thinking today.

📜 Timeline of Major Economic Schools
 1.⁠ ⁠Mercantilism (1500s–1700s)

Core idea: National wealth measured by gold/silver; exports &gt; imports; heavy state control.

Influence: Guided colonial empires, trade monopolies, and tariffs.

 2.⁠ ⁠Classical Economics (1776–1870)

Key figures: Adam Smith, David Ricardo, John Stuart Mill.

Core idea: Free markets, division of labour, “invisible hand”; emphasis on production and growth.

Impact: Industrial Revolution policy, laissez-faire capitalism.

 3.⁠ ⁠Marxism &amp; Socialist Economics (mid-1800s–present)

Key figure: Karl Marx.

Core idea: Critique of capitalism, labour theory of value, class struggle, state ownership.

Impact: Inspired communist revolutions, socialist policies, labour movements.

 4.⁠ ⁠Marginalism &amp; Neoclassical Economics (1870s–present)

Key figures: Jevons, Walras, Marshall.

Core idea: Value determined by marginal utility; equilibrium analysis; rational individuals.

Impact: Foundation of modern mainstream economics, microeconomics.

 5.⁠ ⁠Keynesian Economics (1930s–present)

Key figure: John Maynard Keynes.

Core idea: Markets can fail (esp. in depressions); governments should manage demand using fiscal &amp; monetary policy.

Impact: Guided post–WWII Western economies, welfare state expansion.

 6.⁠ ⁠Monetarism &amp; Chicago School (1950s–1980s)

Key figure: Milton Friedman.

Core idea: Control money supply to manage inflation; limit government intervention.

Impact: Reaganomics, Thatcherism, central bank independence.

 7.⁠ ⁠Austrian School (late 1800s–present, revived 1970s)

Key figures: Carl Menger, Ludwig von Mises, Friedrich Hayek.

Core idea: Importance of entrepreneurship, spontaneous order, critique of central planning.

Impact: Free-market think tanks, libertarian movements.

 8.⁠ ⁠Development Economics (1940s–present)

Core idea: Structural transformation, role of institutions, tackling poverty in Global South.

Impact: World Bank, UN development policy, debates on aid.

 9.⁠ ⁠New Keynesian &amp; New Classical Synthesis (1980s–present)

Core idea: Rational expectations (New Classical) + sticky wages/prices (New Keynesian).

Impact: Dominant academic framework; forms the basis of central bank models today.

10.⁠ ⁠Modern Schools (1990s–present)

Behavioural Economics: Psychology meets economics (Kahneman, Thaler).

Post-Keynesian / MMT (Modern Monetary Theory): Governments with sovereign currencies can run large deficits to ensure employment.

Ecological Economics: Sustainability, climate change, “beyond GDP”.

Techno-Optimist / Data-driven Economics: Big data, market design, platform economies.
</description>

https://a16z.com/the-techno-optimist-manifesto/

…

https://a16z.com/the-techno-optimist-manifesto/

"
Techno-optimism is the belief that rapid technological progress is the main driver of human prosperity and should be pursued as a moral imperative. It argues that:

Growth = Good: Innovation creates abundance, longer lives, and better living standards.

Barriers = Bad: Regulation, caution, and pessimism slow down progress and should be resisted.

Technology as Solution: Challenges like poverty, disease, and climate change are best solved by accelerating science and technology rather than restricting them.

In short: Techno-optimism sees faster innovation as the surest path to human flourishing — and treats resistance to technological progress as harmful.
"

Here’s a structured overview of the major schools of economic thought, mapped across time, followed by an estimate of which views dominate public and policy thinking today.

📜 Timeline of Major Economic Schools
 1.⁠ ⁠Mercantilism (1500s–1700s)

Core idea: National wealth measured by gold/silver; exports > imports; heavy state control.

Influence: Guided colonial empires, trade monopolies, and tariffs.

 2.⁠ ⁠Classical Economics (1776–1870)

Key figures: Adam Smith, David Ricardo, John Stuart Mill.

Core idea: Free markets, division of labour, “invisible hand”; emphasis on production and growth.

Impact: Industrial Revolution policy, laissez-faire capitalism.

 3.⁠ ⁠Marxism & Socialist Economics (mid-1800s–present)

Key figure: Karl Marx.

Core idea: Critique of capitalism, labour theory of value, class struggle, state ownership.

Impact: Inspired communist revolutions, socialist policies, labour movements.

 4.⁠ ⁠Marginalism & Neoclassical Economics (1870s–present)

Key figures: Jevons, Walras, Marshall.

Core idea: Value determined by marginal utility; equilibrium analysis; rational individuals.

Impact: Foundation of modern mainstream economics, microeconomics.

 5.⁠ ⁠Keynesian Economics (1930s–present)

Key figure: John Maynard Keynes.

Core idea: Markets can fail (esp. in depressions); governments should manage demand using fiscal & monetary policy.

Impact: Guided post–WWII Western economies, welfare state expansion.

 6.⁠ ⁠Monetarism & Chicago School (1950s–1980s)

Key figure: Milton Friedman.

Core idea: Control money supply to manage inflation; limit government intervention.

Impact: Reaganomics, Thatcherism, central bank independence.

 7.⁠ ⁠Austrian School (late 1800s–present, revived 1970s)

Key figures: Carl Menger, Ludwig von Mises, Friedrich Hayek.

Core idea: Importance of entrepreneurship, spontaneous order, critique of central planning.

Impact: Free-market think tanks, libertarian movements.

 8.⁠ ⁠Development Economics (1940s–present)

Core idea: Structural transformation, role of institutions, tackling poverty in Global South.

Impact: World Bank, UN development policy, debates on aid.

 9.⁠ ⁠New Keynesian & New Classical Synthesis (1980s–present)

Core idea: Rational expectations (New Classical) + sticky wages/prices (New Keynesian).

Impact: Dominant academic framework; forms the basis of central bank models today.

10.⁠ ⁠Modern Schools (1990s–present)

Behavioural Economics: Psychology meets economics (Kahneman, Thaler).

Post-Keynesian / MMT (Modern Monetary Theory): Governments with sovereign currencies can run large deficits to ensure employment.

Ecological Economics: Sustainability, climate change, “beyond GDP”.

Techno-Optimist / Data-driven Economics: Big data, market design, platform economies.


91. Techno Optimism Vs Socialism. Mentioning Marc Andreessen, Sam Altman & More

<description>Jon Haidt three great untruths: 
(1) “What doesn’t kill you makes you weaker”; (2) “Always trust your feelings”; and (3) “Life is a battle between good people and evil people.” 

Possible opposites for the three untruths: 
(1) “What doesn’t kill you makes you weaker” =&gt; What doesn't kill you makes you stronger. Or post traumatic growth. 
(2) “Always trust your feelings” =&gt; Your feelings are signals that you should always listen to, but not your boss that you must obey. 
(3) “Life is a battle between good people and evil people.” =&gt; This is zero sum fallacy. The world is mainly positive sum, where people work together to get a better outcome. 

Stephen Fry: 
- They'd rather be right then effective. 

Sam Altman: 
- I believe in techno-capitalism. We should encourage people to make tons of money and then also find ways to widely distribute wealth and share the compounding magic of capitalism. One doesn’t work without the other; you cannot raise the floor and not also raise the ceiling for very long.
 
The world should get richer every year through science and technology, but everyone has to be in the “up elevator”. I think the government usually does a worse job than markets, and so we need to encourage our culture of innovation and entrepreneurship. I also believe that education is critically important to keeping the American edge.

I believed this when I was 20, when I was 30, and now I am 40 and still believe it. The Democratic party seemed reasonably aligned with it when I was 20, losing the plot when I was 30, and completely to have moved somewhere else at this point. So now I am politically homeless. But that’s fine; I care much, much more about being American than any political party.

I’d rather hear from candidates about how they are going to make everyone have the stuff billionaires have instead of how they are going to eliminate billionaires.</description>

Jon Haidt three great untruths: 
(1) “What doesn’…

Jon Haidt three great untruths: 
(1) “What doesn’t kill you makes you weaker”; (2) “Always trust your feelings”; and (3) “Life is a battle between good people and evil people.” 

Possible opposites for the three untruths: 
(1) “What doesn’t kill you makes you weaker” => What doesn't kill you makes you stronger. Or post traumatic growth. 
(2) “Always trust your feelings” => Your feelings are signals that you should always listen to, but not your boss that you must obey. 
(3) “Life is a battle between good people and evil people.” => This is zero sum fallacy. The world is mainly positive sum, where people work together to get a better outcome. 

Stephen Fry: 
- They'd rather be right then effective. 

Sam Altman: 
- I believe in techno-capitalism. We should encourage people to make tons of money and then also find ways to widely distribute wealth and share the compounding magic of capitalism. One doesn’t work without the other; you cannot raise the floor and not also raise the ceiling for very long.
 
The world should get richer every year through science and technology, but everyone has to be in the “up elevator”. I think the government usually does a worse job than markets, and so we need to encourage our culture of innovation and entrepreneurship. I also believe that education is critically important to keeping the American edge.

I believed this when I was 20, when I was 30, and now I am 40 and still believe it. The Democratic party seemed reasonably aligned with it when I was 20, losing the plot when I was 30, and completely to have moved somewhere else at this point. So now I am politically homeless. But that’s fine; I care much, much more about being American than any political party.

I’d rather hear from candidates about how they are going to make everyone have the stuff billionaires have instead of how they are going to eliminate billionaires.

90. Is excess empathy a big problem? Mentioning Jon Haight, Nassim Taleb, Sam Altman & more

<description>“The media's the most powerful entity on earth. They have the power to make the innocent guilty and to make the guilty innocent, and that's power. Because they control the minds of the masses.”
― Malcolm X

https://ground.news/about
https://www.readtangle.com/</description>

“The media's the most powerful entity on earth. T…

“The media's the most powerful entity on earth. They have the power to make the innocent guilty and to make the guilty innocent, and that's power. Because they control the minds of the masses.”
― Malcolm X

https://ground.news/about
https://www.readtangle.com/

89. The media has "the power to make the innocent guilty and to make the guilty innocent" Malcolm X. Mentioning Rupert Murdoch, Isaac Saul,  Harleen Kaur (Ground News) & more

<description>Helpful Support = 1. Increased Trajectory + 2. Increase Resilience
Harmful Support = 1. No Improvement In Trajectory + 2. Lowered Resilience 

Support in Different Contexts
- Workplace: Managers should focus on developing employees' skills and independence
- Parenting: The goal is to raise independent adults, not perpetually dependent children
- Friendships: There's a delicate balance between being supportive and becoming a "coach"
- Addiction and mental health: Support should aim for long-term recovery and resilience, not enabling destructive behaviors

Jon Haidt's Three Great Untruths:
- "What doesn't kill you makes you weaker" =&gt; What doesn't kill you makes you stronger. 
- "always trust your feelings" =&gt; Feelings should be examined, sometimes immediate responses are counter productive and one should 'think slow, not think fast'. 
- "life is a battle between good people and evil people" =&gt; The world is not zero sum, most things are 'win-win'. 

Defining Effective Support
- Support done well leads to independence and growth, not dependence
- The goal is to "teach someone to fish" rather than continuously "giving them fish"
- Good support maximizes the trajectory of someone's improvement over time
- Effective support may involve allowing someone to struggle or fail in order to learn and grow

Challenges in Providing Support
- It can be difficult to let someone struggle or fail, especially in personal relationships
- There's a balance between intervening and allowing natural consequences
- The recipient's mindset (growth vs. fixed) impacts the effectiveness of support
- Clear communication about the intention and reasoning behind support is crucial

Reframing Support
- Support should be viewed as increasing resilience and ability to handle future challenges
- It's about being on the same "team" and working together for mutual growth and success
- Good support acknowledges feelings without necessarily endorsing them
- Support should aim for win-win outcomes rather than reinforcing a zero-sum mentality</description>

Helpful Support = 1. Increased Trajectory + 2. In…

Helpful Support = 1. Increased Trajectory + 2. Increase Resilience
Harmful Support = 1. No Improvement In Trajectory + 2. Lowered Resilience 

Support in Different Contexts
- Workplace: Managers should focus on developing employees' skills and independence
- Parenting: The goal is to raise independent adults, not perpetually dependent children
- Friendships: There's a delicate balance between being supportive and becoming a "coach"
- Addiction and mental health: Support should aim for long-term recovery and resilience, not enabling destructive behaviors

Jon Haidt's Three Great Untruths:
- "What doesn't kill you makes you weaker" => What doesn't kill you makes you stronger. 
- "always trust your feelings" => Feelings should be examined, sometimes immediate responses are counter productive and one should 'think slow, not think fast'. 
- "life is a battle between good people and evil people" => The world is not zero sum, most things are 'win-win'. 

Defining Effective Support
- Support done well leads to independence and growth, not dependence
- The goal is to "teach someone to fish" rather than continuously "giving them fish"
- Good support maximizes the trajectory of someone's improvement over time
- Effective support may involve allowing someone to struggle or fail in order to learn and grow

Challenges in Providing Support
- It can be difficult to let someone struggle or fail, especially in personal relationships
- There's a balance between intervening and allowing natural consequences
- The recipient's mindset (growth vs. fixed) impacts the effectiveness of support
- Clear communication about the intention and reasoning behind support is crucial

Reframing Support
- Support should be viewed as increasing resilience and ability to handle future challenges
- It's about being on the same "team" and working together for mutual growth and success
- Good support acknowledges feelings without necessarily endorsing them
- Support should aim for win-win outcomes rather than reinforcing a zero-sum mentality

87. Helpful Support (Independence) vs Harmful Support (Dependence). Mentioning Jon Haidt, Kim Scott,

Chats between Duncan Anderson and James Peck on anything we find interesting... hopefully you find it interesting as well :)

Please note all statements are the individuals own and do not represent the organisations they work for.

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