Author
@ramez
grade Cx.com/ramez ↗
Ramez Naam is a credible clean-energy investor and sector thinker, but recent/profile evidence is mainly climate, clean energy, AI, and policy rather than public-stock/ticker analy
trader score
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hit rate
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mean α
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signals 14d
17
Grade = how their written analysis reads (A best). Trader score = how their last-20 timestamped calls performed vs SPY.
Their picks, scored
Not yet in the scored-bets universe (fewer than 20 scoreable calls).
Recent signals15receipts included
| date (PT) | ticker | author | sent | what they said | since then | receipt |
|---|---|---|---|---|---|---|
| 2026-10-15 | · | @ramez | · | Presents a framework linking AI capability gains to data volume, accuracy and verifiability in compute. | · | tweet ↗ |
| 2026-10-11 | · | @ramez | · | Argues AI-driven mathematical progress is beneficial despite labor displacement. | · | tweet ↗ |
| 2026-10-11 | · | @ramez | · | Advocates layered AI safety combining alignment and engineering safeguards. | · | tweet ↗ |
| 2026-10-11 | · | @ramez | · | Argues scaling and learning-by-doing reduce costs in clean energy, compute, and AI. | · | tweet ↗ |
| 2026-10-10 | · | @ramez | · | Highlights a discussion comparing the power of agent swarms with more intelligent models. | · | tweet ↗ |
| 2026-10-10 | · | @ramez | · | Expresses skepticism that current AI evidence supports imminent runaway recursive improvement. | · | tweet ↗ |
| 2026-10-10 | · | @ramez | · | Outlines an AI framework spanning diminishing returns, narrow superintelligence, energy and access. | · | tweet ↗ |
| 2026-10-10 | · | @ramez | · | Says AI scaling with more tokens has lagged human thinking-time scaling but the gap is narrowing. | · | tweet ↗ |
| 2026-10-10 | · | @ramez | · | Argues narrow superintelligence is likely while broad ASI remains constrained and uncertain. | · | tweet ↗ |
| 2026-10-08 | · | @ramez | · | Bullish on AI labs but argues most value accrues to AI users absent a monopoly. | · | tweet ↗ |
| 2026-10-08 | · | @ramez | · | Argues current models underperform claims and AI progress faces steep diminishing returns. | · | tweet ↗ |
| 2026-10-07 | · | @ramez | · | Argues AI-assisted cheating destroys economic value and will face strong opposition. | · | tweet ↗ |
| 2026-10-07 | · | @ramez | · | Predicts narrow superintelligence in verifiable symbolic domains while remaining cautious elsewhere. | · | tweet ↗ |
| 2026-10-07 | · | @ramez | · | Says empirical testing finds AI is not yet reliably producing novel AI-research ideas. | · | tweet ↗ |
| 2026-10-06 | · | @ramez | · | Evaluates an AI optimization benchmark as positive evidence for recursive improvement while noting its limitations. | · | tweet ↗ |
Grade is our human read-worthiness rating; trader score is a rolling 20-bet hit-rate/alpha composite — different things, often disagreeing. “Since then” is direction-unaware in the table; the summary line above adjusts for which way they leaned.