The cost of intelligence is dropping at an unprecedented rate. Just as the drop in the cost of computing unlocked the PC era and the drop in the cost of connectivity enabled the internet era, falling costs today are driving explosive demand for AI adoption. That demand creates opportunity on the supply side too, in the infrastructure, energy, and technologies needed to support and scale this shift.

In our Thesis 3.0, we highlighted how this AI-driven platform shift will reshape behaviour at massive scale. But identifying the how also means knowing where to look.

Every era of technology has a set of areas where breakthroughs cluster, where infrastructure, capital, and talent converge to create the conditions for outsized returns. For the age of intelligent systems, we see five such areas, each distinct but deeply interconnected.

1. Vertical AI Platforms

After large language models, the next wave of value creation will come from Vertical AI Platforms that combine proprietary data, hard-to-replicate models, and orchestration layers designed for complex and large-scale needs.

Built on unique datasets, workflows, and algorithms that are difficult to imitate, these platforms create proprietary intelligence layers that are increasingly agentic. They can actively make decisions, initiate actions, and shape workflows. This makes them both defensible and transformative, even when part of the foundation rests on commodity models.

This shift from passive tools to active participants marks a profound change in how entire sectors operate.

2. Physical AI

The past two decades of digital transformation mostly played out behind screens. The next era brings AI into the physical world.

Physical AI spans autonomous devices, robotics, and AI-powered equipment that can perceive, act, and adapt in real environments. From warehouse automation to industrial robotics to autonomous mobility, this is where algorithms leave the lab and step into society.

We are still early in this curve. Just as industrial machinery transformed factories in the nineteenth century, Physical AI will reshape industries that rely on labour-intensive, precision-demanding, or hazardous work.

The companies that succeed will combine world-class AI models with robust hardware integration and build the trust that humans place in systems operating alongside them every day.

3. AI Infrastructure

Every transformative technology wave has required new infrastructure that is robust, reliable, and efficient. For AI, this means going beyond raw compute to ensure systems that are secure, safe, and trustworthy at scale.

We need security, safety, efficiency, and trustworthiness as first-class priorities. That means building the tools, frameworks, and protocols that make AI more energy efficient, explainable, and interoperable.

The infrastructure layer determines not only who can build AI, but who can trust it. And trust is ultimately what drives adoption.

4. Advanced Computing Hardware

Every computing revolution has been powered by a revolution in hardware. Just as the transistor enabled mainframes and the microprocessor ushered in personal computing, the next era will be defined by breakthroughs in semiconductors and specialized architectures.

From custom chips to new communication fabrics, hardware is what makes new classes of AI and computation possible, both in the cloud and on the edge. But it is not only about raw compute power. The winners will also tackle energy efficiency, latency, and connectivity, areas that become bottlenecks as models scale.

As Moore’s Law hits its limit, we are entering an age of architectural innovation with neuromorphic computing, photonics, quantum computing, and other advances. Much like the steam engine once unlocked new industries, these architectures will redefine what is computationally possible. This is deep tech meeting industrial adoption, and those who can scale it will capture immense value.

5. Smart Energy

Every technological leap has demanded a new energy paradigm. The electrification era was powered by the grid. Today, AI and computing are demanding unprecedented amounts of energy, and the grid as it exists cannot sustain this future.

This is why smart energy is not peripheral, but central. From new energy sources to intelligent distribution networks, the way we generate, store, and allocate energy is being reimagined. The idea of programmable energy, where supply and demand adapt dynamically using AI, will become as fundamental to the AI era as packet switching was to the internet.

Here, deep engineering meets societal need. Without resilient and efficient energy, AI progress stalls. With it, the future scales.

Shaping What Comes Next

The drop in the cost of intelligence is driving demand at a scale we have never seen before. That demand creates opportunity on the supply side too, in the platforms, hardware, energy, physical systems, and infrastructure that make this future possible.

The five areas — Vertical AI Platforms, Physical AI, AI Infrastructure, Advanced Computing Hardware, and Smart Energy — represent the biggest opportunities of this era. They are not isolated. They form an interconnected landscape where advances in one accelerate breakthroughs in the others.

We are domain experts in these five areas. The TSF team brings technical, product and commercialization expertise that helps founders build and scale in precisely these spaces. We are uniquely qualified to do so.

At Two Small Fish, this is the canvas for the next generation of 100x companies. We are excited to partner with the founders building in these areas globally, those who not only see the future, but are already shaping it.

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