Last year, Apple did something that surprised everybody – the company decided to share their machine learning research to the public. They then published their first AI paper in an academic journal, and now, they have a blog dedicated to machine learning. Called the Apple Machine Learning Journal, it is a place where Apple engineers write about their work using machine learning technologies on Apple products.
In the welcome note, Apple Machine Learning Journal writes:
“Welcome to the Apple Machine Learning Journal. Here, you can read posts written by Apple engineers about their work using machine learning technologies to help build innovative products for millions of people around the world.”
Apple also encourages machine learning researcher or student, engineer, or developer to contact Apple via firstname.lastname@example.org for questions and feedbacks about this topic.
The first topic featured in this new blog, Vol. 1, Issue 1, focuses on “Improving the Realism of Synthetic Images”, similar to the research paper published in December last year.
“Most successful examples of neural nets today are trained with supervision. However, to achieve high accuracy, the training sets need to be large, diverse, and accurately annotated, which is costly. An alternative to labelling huge amounts of data is to use synthetic images from a simulator. This is cheap as there is no labeling cost, but the synthetic images may not be realistic enough, resulting in poor generalization on real test images.”
Check out Apple now to find out more about its Apple Machine Learning Journal.