Key takeaways

• The demand for AI is so large it may outstrip supply, leading to potential bottlenecks.
• A fundamental shift in business cycles is occurring, moving from labor versus capital to compute versus energy.
• Current chip and energy supply shortages are creating significant bottlenecks.
• Technological advancements in AI and data centers are driving a super cycle of capital expenditure.
• AI advancements are fueled by improvements in algorithms and human feedback mechanisms.
• Exponential growth in intelligence is a new phenomenon not seen in biological systems.
• Short-term technological advancement may slow due to bottlenecks, but long-term outlook remains positive.
• Bottlenecks in technology can drive innovation by concentrating capital on specific issues.
• Power infrastructure bottlenecks are affecting the full utilization of the US grid.
• Battery innovations could enable the US grid to meet energy needs by 2030 if capacity issues are resolved.
• Recursive self-improvement in AI suggests continued exponential growth.
• The imbalance between AI demand and supply is a critical issue for investors and stakeholders.
• Technological growth is reshaping economic paradigms and business cycles.
• Energy and chip shortages could impact various industries significantly.
• The super cycle of capital expenditure is unprecedented in its scale and impact.

Guest intro

Jordi Visser is the founder and chief strategist at Visser Labs. He is a veteran macro investor and strategist who previously led global equity strategy at Morgan Stanley, where he developed a reputation for analyzing major market rotations and long-term structural trends.

The demand-supply imbalance in AI

• The demand for AI is so large that it may outstrip supply, leading to bottlenecks. – Jordi Visser

• The bottlenecks themselves may slow the earnings of these companies not because the demand is not there because the demand is too big.

  — Jordi Visser

• Understanding the current state of AI demand and supply dynamics is crucial for investors.
• This imbalance highlights a critical issue in the AI sector.
• The demand-supply dynamics are essential for industry stakeholders.
• The imbalance could slow earnings for companies despite high demand.
• Investors need to be aware of these dynamics to make informed decisions.
• This issue is vital for understanding the future landscape of AI technology.

The shift from labor to compute in business cycles

• The transition from labor versus capital to compute versus energy signifies a fundamental shift in business cycles. – Jordi Visser

• In compute versus energy it’s a very very different thing.

  — Jordi Visser

• Understanding historical business cycles is essential to grasp this shift.
• This shift emphasizes the impact of technology on business growth.
• The change reflects broader economic paradigms influenced by technology.
• Businesses now rely more on computational power than traditional labor.
• This shift could redefine how companies strategize and grow.
• The evolution of business cycles is crucial for future economic planning.

Supply chain challenges in technology and energy

• We are starting to see a phase of bottlenecks and shortages in the supply of chips and energy. – Jordi Visser

• If we can’t actually make all the chips we need and we can’t actually get the power we need in a delayed fashion you end up with a little bit of demand versus supply mismatch.

  — Jordi Visser

• Current supply chain issues are critical for understanding industry challenges.
• These shortages could impact various sectors significantly.
• The demand-supply mismatch is a pressing issue for technology and energy sectors.
• Understanding these challenges is vital for strategic planning in affected industries.
• The shortages highlight vulnerabilities in current supply chains.
• Addressing these issues is essential for maintaining technological growth.

The super cycle of capital expenditure in technology

• The current technological advancements in AI and data centers indicate we are entering a super cycle of capital expenditure. – Jordi Visser

• There is almost no way for this not to be a super cycle… what you’ve got is the largest capex cycle I think humanity will ever see at this rate.

  — Jordi Visser

• This super cycle reflects unprecedented investment in technology.
• Understanding capital expenditure trends is crucial for stakeholders.
• The scale of this cycle is unmatched in history.
• This cycle is driven by advancements in AI and data centers.
• The super cycle could redefine investment strategies across sectors.
• Stakeholders need to adapt to this new investment landscape.

Advancements in AI and exponential growth

• The advancements in AI are driven by improvements in algorithms and human feedback mechanisms. – Jordi Visser

• The algorithmic side got better human feedback reinforcement learning reasoning everything kind of happened and that’s why we’ve been able at least to stay up to here.

  — Jordi Visser

• Exponential growth in intelligence is a new phenomenon not seen in biology. – Jordi Visser

• Reid’s law which is squared or to the power of two has never existed in biology not even you know viruses it doesn’t exist and now we’re seeing it and it’s fucking everywhere.

  — Jordi Visser

• Understanding algorithmic advancements is key to grasping AI growth.
• The role of feedback loops is crucial in AI development.
• This growth represents a unique phase in technological evolution.
• The exponential nature of this growth is unprecedented.

Short-term slowdown and long-term outlook in technology

• There will be a slowdown in the pace of technological advancement due to bottlenecks and shortages. – Jordi Visser

• I do believe there’s gonna be a slowdown to some degree…even if for the next four months the focus shifts to bottlenecks and shortages…you’re gonna be blown away more than you are today.

  — Jordi Visser

• The long-term outlook remains positive with recursive self-improvement.
• Bottlenecks can drive innovation by concentrating capital on specific issues. – Jordi Visser

• What that bottleneck does is concentrate capital into that particular issue because if the universe is solving for intelligence per unit of energy it will clear all roadblocks to get there.

  — Jordi Visser

• Understanding the current technological landscape is crucial for forecasting.
• The relationship between bottlenecks and innovation is significant.
• Stakeholders should prepare for both short-term challenges and long-term opportunities.

Power infrastructure and energy utilization challenges

• There is a significant bottleneck in power infrastructure that affects the ability to utilize the US grid fully. – Jordi Visser

• It’s very clear to everyone now based on the data center delays based on the turbines and the transformers and every other part that it’s we’ve got a bottleneck.

  — Jordi Visser

• Battery innovations will enable the US grid to meet energy needs by 2030 if capacity issues are resolved. – Jordi Visser

• If we could store and have it to deal with those peak capacity days then we wouldn’t we’d be able to use the grid almost completely to get the needs that we have by 2030.

  — Jordi Visser

• Understanding power infrastructure issues is crucial for energy planning.
• Addressing these bottlenecks is essential for future energy utilization.
• Innovations in battery storage are key to resolving capacity challenges.
• The future of energy utilization depends on overcoming these obstacles.