AI Berkshire
Buffett, Munger, Klarman & Marks. One verdict per ticker.
What it does
AI Berkshire runs four value-investing frameworks — Buffett (moat), Munger (inversion), Klarman (margin of safety), Marks (cycle position) — as parallel agents on any ticker, letting them disagree on purpose. Real market data in (US via Nasdaq/SEC, HK & A-shares via Tencent), four independent theses out, each with a 0-100 conviction score. On NVDA: Buffett Bullish, Klarman Bearish — same data, opposite verdicts. That tension is what a single AI analyst can never show you. Free: 1 analysis/day.
Does the same job
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Life & fun · Aug 2026 · toneyalexander.github.io
I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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