NucleusResearch.com
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Document Number: T176 December 2019
L O O K I N G A H E A D
The future for machine learning is promising as hardware improvements continue to
increase data processing speeds and storage capabilities while algorithmic improvements
increase the accuracy of inferences and widens the scope of problems that can be solved.
Companies of all sizes in all industries are recognizing the potential of these technologies,
and those that don't have the resources or personnel to pursue them will lag behind.
Amazon SageMaker is helping lower the barriers to entry for bringing machine learning
applications into production. It will accelerate the pace of machine learning progress and
create additional value for customers. Nucleus is already seeing strong adoption that is
growing quickly. In 2018 approximately one third of 177 deep learning projects on AWS
were using or exploring use of SageMaker. In 2019, 63 percent of 316 deep learning
projects running on AWS were using SageMaker. The rapid growth and adoption
demonstrates that Amazon is meeting a need in the market; it continues to innovate and
expand the offering, with the IDE for machine learning in SageMaker Studio, among other
highlights announced at re:Invent 2019. With services like SageMaker, AWS further
differentiates itself in a crowded cloud infrastructure market by offering mature, value-add
services and developer tools that other vendors lack along with mastery of table stakes
components: security, compute, and storage.
