The age of machine learning is a new phase of computing. Powered by a dynamic research community, computers can now recognize images and audio, translate languages, generate realistic text, and beat humans at games.
Machine learning is likely the most significant technological shift happening between 2010 and 2030. Aside from a few innovative products from large tech companies, machine learning has not yet made a tremendous impact.
Our vision was that Big Data would change the way machine learning works. Data driving learning.
— Fei-Fei Li
Machine learning replaces a specialized resource constraint (software engineers) with a commoditized one (data labelers). This significantly accelerates technological progress on a global scale. The growth rate of software will accelerate over the next decade as more software is created by machine learning.
It is early in the age of machine learning. Deeply impactful technology takes time to gestate. Google was founded 15 years after the invention of the internet. iPhone was invented 24 years after the invention of the internet.
It’s only been 8 years since AlexNet was first launched. Being early makes our work exciting. We have the opportunity to be profoundly influential.
Building infrastructure is more durable than building applications—Scale will amplify the whole impact of machine learning if we succeed, which will reach further than any single application. In this way, we will bend the curve of technology, and therefore the curve of humanity. Our mission is critically important, and needs to happen now. By structurally increasing the coefficient of growth, we are enabling a new age of software.
Join us as we accelerate the development of AI applications.