Deep Learning As A Service

After a quick overview of how Google has utilized its Artificial Intelligence (AI) technology, the article states, "Some companies have built their own AI research units and need to build highly customized models for specific applications. Yet, in doing so they quickly run up against the immense hardware requirements of building large deep learning models, often requiring entire accelerator farms for rapid iteration. In Google's case it offers a hosted deep learning platform called Cloud Machine Learning Engine that takes care of the hardware needs of deep learning development, allowing companies to focus on building their models and offload the computing requirements to Google. After all, few companies have invested so much in AI that they have built their own custom accelerator hardware like Google did with its Tensor Processing Units (TPUs)." Further into the article, the author, Kalev Leetaru, states analytics companies "are interested in building services for their customers, not conducting AI research. In following its externalization trend, Google has risen to this challenge by releasing many of its internal AI systems as public cloud APIs."