newsfilter.io

The Problem With Testing AI Architectures at Small Scale | Jerry Tworek, Core Automation

Sequoia CapitalJerry Tworek
Watch on YouTube →
  • Reinforcement learning architectures generally require a baseline level of compute capacity to produce effective results and function meaningfully.
  • Validation attempts on small datasets prior to scaling may fail to accurately reveal an architecture's true capabilities if they do not meet these minimum compute thresholds.
The Problem With Testing AI Architectures at Small Scale | Jerry Tworek, Core Automation — Outlook