Ivy Grad Trading Analogy: Reading More Doesn't Help Without Deliberate Practice
minhnguyen · x · 2026-11-15
minhnguyen's human analogy for the pretraining-vs-alignability argument: an Ivy League grad who reads a lot about macro/business/tech will inherit analysts' biases when trading, and reading more won't improve results at the margin. But pair the reading with trading-specific heuristics and deliberate practice, and they'll beat someone with the same process but less reading—mirroring how models benefit from pretraining data only when paired with specialized RL objectives.
More from Research
- Flint 40B self-improves into Flint-Law, gaining 15% on legal tasks over 11 steps — RichardSocher · 2026-11-15
- Sebastian Raschka publishes from-scratch RoPE tutorial and survey of positional embeddings in modern LLMs — rasbt · 2026-11-15
- Training your own LLM judge for ~$5 in 1h40 on one GPU, 89.5% accuracy — MaziyarPanahi · 2026-11-15
- LeCun's CoRL slide: 'If you are interested in human-level AI, don't work on LLMs' — Heavy-Ad9232 · 2026-11-15
- Dataset Distillation via Drifting compresses 1,300 ImageNet images per class into just 10 — kastnerkyle · 2026-11-15
- "Double-blind review doesn't work": reviewers see author names, and rival students reject competitors — Temporary_Switch_339 · 2026-11-15