TheSequence Scope: Can Machine Learning Write Better Machine Learning?

This is a summary of the most important published research papers, released technology and startup news in the AI ecosystem in the last week. This compendium is part of TheSequence newsletter. Give it a try by subscribing below:

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📝 Editorial

Writing machine learning programs remains a relatively subjective process. Given a problem, we trust data scientists and machine learning engineers to select the best models and architectures, but how do we know those are correct? Data scientists have their own preferences and biases which can influence the machine learning models they apply to a specific problem. Emerging thinking in space is that we can use machine learning to build better machine learning models.

Writing machine learning with machine learning is not a problem with a single solution. Methods such as neural architecture search (NAS, covered in Edge#4) try to select the best model for a given problem. Meta-learning focuses on creating models that can “learn to learn” while program synthesis tackles…