The Apple Machine Learning Journal is aimed at researchers, developers, and students interested in learning about machine learning and interacting with the tech company on the subject. The site, says Apple, will offer users an opportunity to “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.”
The site launched with one paper already uploaded – “Improving the Realism of Synthetic Images.” It discusses a method for refining simulated/synthetic images – which, for cost reasons, are often used for training neural networks – to make them look more realistic and consequently improve accuracy on various machine learning tasks.
The post appears to be based on a previously published academic paper from last year – “Learning from Simulated and Unsupervised Images through Adversarial Training.” It is not indicated how frequently the site will be updated with new papers.
The launch of the Apple Machine Learning Journal comes on the heels of other recent AI pushes from competitors. Google recently announced its PAIR (“People + AI Research”) initiative, and Microsoft launched a new Microsoft Research AI group.
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