The New Stack Podcast

Machine Learning AI Finds its Place in the Production Pipeline

Episode Summary

Machine learning-aided artificial intelligence (AI) might one day be able to eventually emulate the intelligence of hundreds or even thousands of human brains simultaneously, in such a way that human input would be obsolete throughout the software development cycle. In theory, a single system could not only replace a hundred-member DevOps teams, but assume the roles and tasks performed by hundreds of similar-sized DevOps teams. You could easily imagine, like taxi and truck drivers, the days of the software developer are numbered — except they really are not.As far as thinking outside of the box or finding ways to write elegant and creative code or when chaos occurs, AI is largely lost. This but only partially explains why machine-learning taught computers may never be able to create art or write poetry to the extend a human can, while the mass replacement of men and women in the software development and operations should thus not happen anytime soon.But what machine learning is already good at, Nick Durkin, field CTO for Harness said during this episode of The New Stack Maker podcast, is assuming a lot of the more data-crunching and mundane tasks in the production and deployment pipelines.

Episode Notes

Machine learning-aided artificial intelligence (AI) might one day be able to eventually emulate the intelligence of hundreds or even thousands of human brains simultaneously, in such a way that human input would be obsolete throughout the software development cycle. In theory, a single system could not only replace a hundred-member DevOps teams, but assume the roles and tasks performed by hundreds of similar-sized DevOps teams.

You could easily imagine, like taxi and truck drivers, the days of the software developer are numbered — except they really are not.As far as thinking outside of the box or finding ways to write elegant and creative code or when chaos occurs, AI is largely lost.

This but only partially explains why machine-learning taught computers may never be able to create art or write poetry to the extend a human can, while the mass replacement of men and women in the software development and operations should thus not happen anytime soon.But what machine learning is already good at, Nick Durkin, field CTO for Harness said during this episode of The New Stack Maker podcast, is assuming a lot of the more data-crunching and mundane tasks in the production and deployment pipelines.