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Themes

Editorial narrative buckets - the way we talk about pieces of the AI supercycle. Themes are curated groupings used for screens; they exist alongside bubbles, which are validated empirically by 252-day capital-flow co-movement. When a theme's avg correlation is high, the editorial story is also tradeable as a bloc.

19 themes116 stocks

Space

Decent

Launch, satellite comms, earth observation.

Stocks
7
Avg corr
0.58

Photonics

Weak

As AI clusters scale, copper hits physical limits and the next bottleneck becomes optical infrastructure. Lasers, transceivers, optical engines, specialty glass, and the test/burn-in capacity behind it.

Stocks
17
Avg corr
0.36

Drones

Decent

UAVs and counter-UAS - defense and commercial.

Stocks
5
Avg corr
0.46

Nuclear

Decent

Reactors, SMRs, uranium miners and enrichment.

Stocks
4
Avg corr
0.52

CPU Bottleneck

Decent

Server CPUs, packaging and ARM-based silicon - the non-GPU compute layer.

Stocks
4
Avg corr
0.48

AI Utility

Decent

AI-native cloud / GPU-as-a-service operators.

Stocks
5
Avg corr
0.55

AI Power

Weak

Power generation, fuel cells, distribution for AI datacenters.

Stocks
4
Avg corr
0.38

AI Hardware

Weak

Foundries, memory, lithography - the AI silicon supply chain.

Stocks
14
Avg corr
0.31

AI Applications

Weak

Enterprise software and platforms productizing AI for end-users.

Stocks
5
Avg corr
0.41

AI Inference

Weak

Custom silicon and connectivity for inference workloads.

Stocks
9
Avg corr
0.39

Agentic AI

Weak

Edge / serverless / dev infra enabling autonomous AI agents.

Stocks
5
Avg corr
0.29

Physical AI

Weak

Robotics, autonomy, manipulators - AI in the physical world.

Stocks
6
Avg corr
0.26

AI + Battlefield Software

n/a

Software platforms productizing AI for defense, intelligence, and battlefield decisions.

Stocks
1
Avg corr
-

Compute Capacity

Weak

GOOGL admitted Google Cloud is leaving revenue on the table because it cannot build capacity fast enough. The bottleneck has shifted from chips to deployment - value accrues to operators with the power, real estate, and operational scale to actually deliver AI compute. These names anchor multi-billion-dollar contracted backlogs from hyperscalers (MSFT, META, GOOGL, AWS) and frontier labs (OpenAI, Anthropic), turning grid-connected MW and GPU clusters into long-dated revenue.

Stocks
12
Avg corr
0.37

Missile Defense / Golden Dome

Decent

Primes building the next-gen US missile defense and Golden Dome architecture.

Stocks
4
Avg corr
0.56

Warships / Submarines

Decent

Naval platforms - surface combatants, submarines, and shipyards.

Stocks
2
Avg corr
0.54

Critical Materials

n/a

Rare-earth and strategic materials supply chain - the substrate of defense and AI hardware.

Stocks
2
Avg corr
-

Power Semis

Decent

Power conversion and management silicon - the unloved bottleneck of the AI buildout.

Stocks
4
Avg corr
0.48

Robot Foundation Models

Weak

The software layer powering next-gen robots in 2026. Generalist vision-language-action (VLA) models that train across embodiments - humanoid, quadruped, manipulation arms - are the bottleneck shifting value from hardware to the "robot brain". The investable public surface is dominated by NVDA (Isaac sim + Cosmos + GR00T) and the mega-cap diversifieds (GOOGL Gemini Robotics, MSFT/OpenAI-Figure axis, AMZN industrial fund, TSLA Optimus vertical, BIDU Apollo). The actual technological leaders - Skild AI (omni-embodied brain) and Physical Intelligence (π0/π0.5 manipulation models) - are still private, alongside the humanoid platforms (Figure, 1X, Apptronik, Agility) consuming those models. Tracked as an editorial theme rather than a bubble because the public basket would beta-drift into AI Compute / Hyperscalers.

Stocks
6
Avg corr
0.29