DataStax Underpins Base Blocks In AI Application Lifecycle

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AI,Data,AI Lifecycle

I am a technology journalist with three decades of press experience. Primarily I work as a news analysis writer dedicated to a software application development ‘beat’. I have spent much of the last twenty years focusing on open source, analytics & data science, cloud computing, mobile devices & data management.

Software has a lifecycle. Our apps are code-based entities created inside what the IT industry likes to call the software application development lifecycle, or SDLC. Code is laid down, put through testing and debugging, released to live production and then augmented, enhanced, maintained and extended. In the longer term, some applications hang on to graduate to legacy status and some are refactored, retired, decommissioned and killed off.

DataStax has eyes on making a good portion of the backend part of the lifecycle equation easier so that developers can focus on application development, rather than infrastructure management. Now styling itself as an AI platform company, DataStax has focused on generative AI development with extensions to make retrieval augmented generation simpler.

“The generative AI stack and its lifecyle is a big and complex ball of technology that many are working to get their arms around. We’re focused on helping developers stay true to their roots so they can do what they do best: build and develop, rather than worrying about application infrastructure,” said Ed Anuff, chief product officer, DataStax.

 

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