Author

@Yuchenj_UW Yuchenj_UW

AI-infra founder mapping frontier-lab compute dynamics to public-equity proxies

Comments on and analyzes the frontier AI landscape — model r

trader score
-0.51
hit rate
43%
mean α
-0.71%
signals 14d
5

Grade = how their written analysis reads (A best). Trader score = how their last-20 timestamped calls performed vs SPY.

Their picks, scored

Across their last 7 scored bets: 43% hit rate, -0.71% mean alpha, trader score -0.51. Their last-14d mentions, direction-adjusted, have moved -3.8% since posting (mean over 1 mentions with price data).

Recent signals5receipts included
date (PT)tickerauthorsentwhat they saidsince thenreceipt
2026-08-27·@Yuchenj_UW·Reports GLM-5.3-Flash at 270 tokens/s, 10% higher benchmark quality, and one-tenth the cost.·
2026-08-26·@Yuchenj_UW·Announces GLM-5.3 open weights in 22 hours with enthusiasm.·
2026-08-26NVDA@Yuchenj_UW-0.25Says GLM-5.3-Flash achieved massive usage on Chinese chips, supporting an independent AI stack.+3.8%
2026-08-26·@Yuchenj_UW·Reports GLM-5.3-Flash beating GLM-5.2 across benchmarks at less than half the size.·
2026-08-18·@Yuchenj_UW·Praises speculative decoding and imagines local trillion-parameter inference at 100 tokens per second.·

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.