AI as a Service

How Data and Models Feed Computing

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Not every company, nor every developer will have the resources or the time to collect vast amounts of data to create models from scratch. Fortunately, the same repetition that I described in my last post occurs within and across industries. Because of this, particularly with deep learning, we’ve seen two very important trends: (1) creation and sharing of public data to build models; and (2) sharing of the models themselves even when the data is not released. While the companies that have the most data may never release it, such data is not a requirement for every problem. It’s clear, however, that teams that leverage existing public models and combine public and proprietary datasets will have a competitive advantage. They must be “smart” about how they use and leverage the data they are able to collect, again with an AI mindset and strategy in mind. Supervised and Unsupervised Learning The…