Colleagues across academia and the AI industry are hammering away at the same concept: a better algorithm would make better decisions, regardless of the data. But I realized a limitation to this approach— the best algorithm wouldn’t work well if the data it learned from didn’t reflect the real world. My solution: build a better dataset.
Dr. Fei-Fei Li
Co-Director of AI at Stanford / Former Head of Google AI
Everyone is working on better algorithms and trying to throw as much data at the problem as possible. But the data must be prepared, curated, and managed for a life-long achievement of accuracy, yet, must be done in a timely manner to produce real-time results. My solution: build a better engine.
Founder & CEO, Farmwave
Perceived Conflicts in AI
Lower gross margins
Weaker defensive IP position
How We Differ
Automations decrease overhead
A whole new method of training
Technology Architecture Built For Growth
Farmwave combines powerful machine learning, proprietary algorithms, and techniques developed specifically for agriculture, and artificial intelligence to power intelligent decision-making capabilities.
We built a better engine to support a better dataset.
The Farmwave Advantage
Unbiased data set
Proprietary tools for image collection and curation
Patented technology in the agriculture space
AI models utilizing proprietary algorithms
API capability for 3rd party SaaS integrations