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– Keywords : Artificial intelligence Platforms –
AI Platform makes it easy for machine learning developers, data scientists, and data engineers to take their ML projects from ideation to production and deployment, quickly and cost-effectively. From data engineering to “no lock-in” flexibility, AI Platform’s integrated tool chain helps you build and run your own machine learning applications.
AI Platform supports Kubeflow, Google’s open-source platform, which lets you build portable ML pipelines that you can run on-premises or on Google Cloud without significant code changes. And you’ll have access to cutting-edge Google AI technology like TensorFlow, TPUs, and TFX tools as you deploy your AI applications to production.
The use of Big Data has continued to grow and mature, with some organizations reaping considerable rewards. The processing of Big Data has recently advanced to a new level of evolution, in the form of AI (Artificial Intelligence) platforms. AI platforms promise significant impact (and disruptions) over the next decade. The use of AI to process massive datasets will bring previously unknown improvements to Business Intelligence and Analytics among innumerable other technologies.
An AI Platform is a framework designed to function more efficiently and intelligently than traditional frameworks. “When designed well,” said Kaul. “It provides organizations with faster, more efficient, more effective collaboration with Data Scientists and staff.” It can help minimize costs in a number of ways – preventing duplication of effort, automating simple tasks, and eliminating some expensive activities, such as copying or extracting data. An AI Platform can also provide Data Governance, ensuring the use of best practices by a team of AI scientists and ML engineers. And it can aid in ensuring that work is distributed more evenly and completed more quickly.