Eight legendary investors’ AI bets — one score for consensus vs. divergence
The Compass Consensus Score turns the disclosed moves of Buffett, Duan Yongping, Cathie Wood and five more legends into a 0–100 score per AI stock — fully published methodology, refreshed every 13F season. With theme maps, stock profiles, and a long-term framework. Sourced and traceable, never a black box.
AI market snapshot
From picks-and-shovels to the energy base layer, the AI market splits into four clear layers. Know which one you are buying.
Compute & AI Chips
4 namesThe “pick-and-shovel” layer of the AI boom. Training and inference demand drives GPU/accelerator sales — the clearest cash flows today, but also the most crowded and richly valued.
Cloud & AI Infrastructure
3 namesThe layer that turns compute into rentable services: hyperscalers and emerging GPU clouds. Capex is enormous, but it locks in long-term AI workload demand.
AI Applications & Platforms
2 namesThe layer that turns models into products and revenue: search, ads, productivity, vertical SaaS. Winners are decided by distribution and data, not raw compute.
AI Energy & Power
1 namesThe overlooked bottleneck: surging data-center power demand puts nuclear, grid, and cooling on the AI map — a “second-order” beneficiary.
Learn more →China AI
3 namesThe AI story at China’s internet giants: in-house models + cloud + e-commerce/ad monetization. Usually cheaper than U.S. peers, but carrying policy and geopolitical risk.
Latest updates
Updates →Coatue’s Laffont explains his biggest AI trade
Running ~$22.7B, Laffont trimmed Nvidia and Meta and added application leaders (e.g., Netflix), shifting toward AI-driven, higher-certainty monetization.
Tepper trims Nvidia, doubles Amazon — betting on AI monetization
Appaloosa nearly doubled Amazon into its top position on accelerating AWS, while trimming Nvidia and AMD and adding Micron — a rotation from compute toward where AI revenue lands.
Duan Yongping leans into AI: adds Nvidia & Alphabet, opens Palantir
In Q1, Duan made Nvidia his #3 position and opened Palantir, Synopsys, CrowdStrike and Snowflake while exiting Alibaba and CoreWeave — a value investor tilting toward AI.
Featured legendary investors
Rather than chase the theme, see how genuine long-term investors allocate capital across AI.
Warren Buffett
CautiousAvoids chasing the AI theme; gains AI exposure indirectly through high-quality, moat-rich businesses — notably Amazon and Apple.
Cathie Wood
BullishOne of the most aggressive AI bulls. Bets on AI infrastructure and next-gen compute — CoreWeave, Cerebras — and on nuclear (X-Energy) as AI’s energy base layer.
Stanley Druckenmiller
CautiousThe macro legend sidesteps the most crowded AI trade, rotating toward platforms with clearer monetization — adding Amazon and Alphabet for two straight quarters, not Nvidia or Palantir.
Bill Ackman
BullishHolds only a handful of high-conviction names. Gains AI exposure through quality compounders like Alphabet rather than speculation.
Duan Yongping
CautiousA value investor anchored in Apple and Berkshire who clearly leaned into AI from 2026 — sharply adding Nvidia and Alphabet and opening Palantir, Synopsys and other AI names, while holding a large PDD stake. Especially relevant for Chinese readers.
David Tepper
BullishIn Q1 2026 he nearly doubled Amazon into his #1 position (AI angle = accelerating AWS), while trimming Nvidia and AMD and leaning into Micron — “betting on AI monetization and the memory cycle, not pure compute.”
Philippe Laffont
CautiousA tech-growth heavyweight running ~$22.7B whose top-10 holdings are nearly all AI-influenced. He recently trimmed Nvidia and Meta and added names like Netflix — rotating from hardware toward AI-benefiting application leaders.
Michael Burry
BearishThe “Big Short” investor, famed for contrarian, bubble-skeptical bets. Featured here as the counterweight: a reminder of AI’s rich valuations, crowded narrative, and cycle risk — skeptical of the price paid for growth, not of AI the technology.
Long-Term
AI will swing, but the principles of long-term investing do not. Put discipline into a checklist.
Circle of competence: invest in what you understand
Only bet where you can explain the business model and competitive landscape. Depth of understanding is what lets you hold through volatility.
AI · With AI, first separate compute vs. infrastructure vs. applications vs. energy — each layer has a very different moat and risk profile.
Moats: look for durable competitive advantage
Durable high returns come from advantages that are hard to copy: network effects, switching costs, scale, proprietary data, or ecosystem lock-in.
AI · Beware moat-less “wrapper” apps; favor companies that own distribution, proprietary data, or a full-stack position.
Valuation discipline: a great company still needs a fair price
The price you pay for growth determines your return. Even a great story can pre-spend years of future gains if bought too dear.
AI · Rich valuations make AI leaders acutely sensitive to any slowdown; keep a margin of safety and avoid going all-in at peak euphoria.
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