The AWS re:Invent conference is this week, and AI is all set to be the talking point of this gathering. Amazon Rekognition, the company’s deep learning image recognition platform is in focus now.
Ahead of this anticipated event, the cloud giant announced a couple of big developments.
First is the opening of a machine learning lab, conveniently named ML Solutions Lab, which pairs Amazon machine learning experts with customers that are looking to build solutions using artificial intelligence technologies.
Along with that, the company has also releases new features for Rekognition, which allows the service to do real time face recognition, but also recognize text in images.
These enhancements to its image recognition underscore the push that AWS is giving to AI — both internally and as potential B2B area of growth. Both these developments also come about a month after the cloud leader announced that it would be collaborating with Microsoft on Gluon.
Which is a deep learning interface designed for developers to build and run machine learning models for their apps and other services.
Of course, you may recall that it was last year at re:Invent that the company announced Amazon AI, a division that now oversees the solutions lab.
These new features for Rekognition shows how Amazon not only continues to make major advances in computer vision, but also the strong commitment from the company towards monetization, by turning them into products for external customers.
One of the biggest customers using these new Rekognition features is Pinterest, the social network.
Which is not all that surprising when you consider the fact that image related functions like search and classification are the core features that Pinterest has built its service on. While the social site developers the majority of its technology in house, it is using Rekognition as part of a smaller project.
It’s a logical choice for Pinterest, this new way to identify the text in images.
We’ll probably hear more about these AI infused features at re:Invent later this week, but if you needed more proof that deep learning and machine learnings algorithms are the future of technology, this is it.