The Real-Time AI Data Race Is On

As we now apply an increasing amount of Artificial Intelligence (AI) to our machines through increasingly sophisticated Machines Learning (ML) models, our machines are getting smarter all the time. We don't just need more intelligence, we need it according to specific vectors. Key among those vectors are AI at scale, AI that is validated, secured and bias-free (aka explainable AI) and AI engines that are capable of computation analysis in real-time. The question we must now ask is: should AI specialists develop more real-time competencies, should real-time data streaming specialists work to innovate new tiers of AI, or should the responsibility fall to higher-level data platform specialists or the hyperscaler Cloud Services Providers (CSPs) themselves? DataStax thinks this challenge is a data platform play, but then - it would, the company is an enterprise DataBase-as-a-Service (DBaaS) tools and technology specialist with a foundation in the Apache Cassandra open source database.