Big Data Is Not the Way to Go
Last Updated on July 25, 2023 by Editorial Team
Author(s): Andre Ye
Originally published on Towards AI.
The significance of the data distribution
a la unsplash
This member-only story is on us. Upgrade to access all of Medium.
A lot of discourse around deep learning would have you believe that more data is better. This is a fairly intuitive idea. Data represents the ‘real world’ in some capacity, and models training on such data learn a sampled representation of this ‘real world’. Ergo, the more sampled data, the closer the model’s understanding approximates the ‘real world’.
This proposition appears to be corroborated by, well, the entire history of deep learning. “Good research requires good resources,” the ImageNet website reads. “To tackle this problem at scale… it… Read the full blog for free on Medium.
Join thousands of data leaders on the AI newsletter. Join over 80,000 subscribers and keep up to date with the latest developments in AI. From research to projects and ideas. If you are building an AI startup, an AI-related product, or a service, we invite you to consider becoming a sponsor.
Published via Towards AI
Towards AI Academy
We Build Enterprise-Grade AI. We'll Teach You to Master It Too.
15 engineers. 100,000+ students. Towards AI Academy teaches what actually survives production.
Start free — no commitment:
→ 6-Day Agentic AI Engineering Email Guide — one practical lesson per day
→ Agents Architecture Cheatsheet — 3 years of architecture decisions in 6 pages
Our courses:
→ AI Engineering Certification — 90+ lessons from project selection to deployed product. The most comprehensive practical LLM course out there.
→ Agent Engineering Course — Hands on with production agent architectures, memory, routing, and eval frameworks — built from real enterprise engagements.
→ AI for Work — Understand, evaluate, and apply AI for complex work tasks.
Note: Article content contains the views of the contributing authors and not Towards AI.
Related posts
Recent Posts
