Which PaaS is Winning the Machine Learning and Artificial Intelligence Race?

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Machine learning(ML) and artificial intelligence(AI) are becoming pivotal elements on the next wave of innovation in the platform as a service space. PaaS incumbents like AWS, Azure, Bluemix or Google Cloud are constantly trying to out innovate each other with new ML and AI capabilities. While the first wave of PaaS innovation was focused on core infrastructure and application platform services, this new wave is driven by data insights and knowledge. In the near future, ML and AI services will be as common as data and infrastructure in PaaS applications.

If we think about AI and ML as general categories, we will conclude that PaaS AI and ML capabilities are still in its infancy. The current race in the PaaS space has been focused on a very specific types of AI and ML capabilities and it seems to remain very consistent across all PaaS leaders. A few months after a PaaS platform announces a new AI-ML service, we can expect some of its competitors to release similar features.

What are the current AI-ML areas of focus in PaaS technologies. The following list is a good starting point:

· Machine learning platforms: Native cloud services that enable authoring, executing and managing traditional machine learning models (ex: classification ,clustering, regression, etc)

· Natural language processing service: Services that enable the syntactical and sematic analysis of natural language sentences. Some of the common disciplinice in this category include sentiment analysis, intend analysis, conversation modeling, etc.

· Vision analytic services: Services that provide understanding the content of images. Some of the common techniques in this category include automatic image classication, emotion analysis etc.

· Speech processing services: Services that enable speech analytic capabilities such as translation, conversion to text, etc

· Knowledge services: Services that complement data with knowledge performing operations such as concept extraction, entity linking etc.

· Data insights services: Services that provide insights about target data sources. Some of the common techniques in this category include tradeoff analysis, news analysis, etc

How are the top PaaS incumbents compared in these different areas. The following matrix provides an initial analysis:

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Written by

CEO of IntoTheBlock, Chief Scientist at Invector Labs, Guest lecturer at Columbia University, Angel Investor, Author, Speaker.

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