Amplify deep dive: how model training breeds slop, and what Taste does to fix it
sarahcat21 · x · 2026-11-13
sarahcat21 spotlights Amplify Partners' long-form piece "Engineering a Beautiful Mind" by Justin Gage (Amplify is a Taste Labs investor), arguing that before debating taste and methods to raise the ceiling, the field must first combat mediocrity and raise the floor.
Opening with how the Medici family leveraged the power of a beautiful world, the article tackles the technical question of what it actually takes to make models better at subjective domains: how model training systematically produces slop, and how Taste Labs' approach uses taste to reduce slop and amplify creative diversity.
More from Research
- Why wasn't Muon tried earlier? Yaroslav Bulatov on optimizer preconditioning mindsets — _arohan_ · 2026-11-13
- Speculative Self-Distillation cuts training tokens 38–69% with no accuracy loss — Azaliamirh · 2026-11-13
- tszzl: local minima are rare in high-dimensional spaces — the greatest whitepill — JensHonack · 2026-11-13
- Chronicle Bio announces first clinical trial with Prolong, using AI to match patients for ME/CFS drug — thekaransinghal · 2026-11-13
- Salesforce's A²-Bench: 500 scenarios expose 20 failure modes in multi-agent teamwork — mohitban47 · 2026-11-13
- Matrix optimizers likely within 5-10% CE of each other, researcher argues — _arohan_ · 2026-11-13