The research desk smart investors and institutions build on
The same desk our AI-native fund — the QAI Fund — runs on. Ecosystem boards, company dossiers, and report decks on frontier AI and proprietary, web-grounded data; every figure sourced, every thesis falsifiable. The edge to build a smarter strategy — analyst work product, never advice.
Read the thesis before it’s consensus — every board, dossier & note the moment the desk ships it.
Durable margin migrates down + around the chip-design layers to chip-agnostic toll-booths (EDA/IP, foundry, HBM, EUV) + own-silicon hyperscalers — away from the merchant-GPU premium and the GPU-rental spread. At 25-Jun prices almost everything is a wonderful business at a peak-cycle multiple, so the disciplined book is mostly hedged/paired/waiting.
The AI Stack
AI value chain — 400+ top companies across 11 layers
Trending companies
Movers across public markets, pre-IPO and the startup atlas
Research boards
Argued ecosystem + single-name theses
State of AI for Healthcare
Where margin actually accrues in clinical AI once you follow the money path rather than the technology — US-first, August 2026
State of AI Compute
Margin-Pool Migration under Custom-Silicon Proliferation
State of Nvidia
The highest-quality franchise in semis, priced for perfection — own the moat at a re-anchored gross-margin floor.
Funds we track
Iconic hedge funds, ETFs and VC books — plus the internet-viral names
Serenity (@aleabitoreddit)
Serenity — anonymous independent trader / X & Reddit KOL (real legal name not publicly disclosed; Reddit u/AleaBito, ex-r/wallstreetbets). Self-described former AI research scientist / RISC-V Foundation member; >500k X followers.
Situational Awareness LP
Leopold Aschenbrenner (founder, ex-OpenAI Superalignment)
Atreides Management (Gavin Baker)
Gavin Baker — Managing Partner & CIO of Atreides Management, LP (founded 2019). Ex-Fidelity, where he ran the OTC Portfolio for ~13 years. Among the most-followed AI/semi voices on FinTwit (@GavinSBaker, ~400k+ X followers); widely circulated for technically deep podcast appearances (e.g. Invest Like the Best) on chip architectures, memory, and the AI compute stack.