MLOps is similar to DevOps but focused on ML, and focuses on improving the quality of delivery for artificial intelligence applications. In this episode, Stephen Foskett discusses MLOps with Steph Locke, CEO of Nightingale HQ. DevOps is very much a cultural shift for software development, while MLOps in practice tends to be more of a team sport, with software developers, data scientists, machine learning experts, and IT infrastructure and operations. Another benefit of MLOps is the improvement of efficiency that results from having all these diverse groups collaborate on application development and deployment.
- How long will it take for a conversational AI to pass the Turing test and fool an average person?
- Are there any jobs that will be completely eliminated by AI in the next five years?
- How big can ML models get? Will today’s hundred-billion parameter model look small tomorrow or have we reached the limit?
Guests and Hosts
- Steph Locke, Data Scientist and CEO of Nightingale HQ. Connect with Steph on LinkedIn or on Twitter @TheStephLocke
- Stephen Foskett, Publisher of Gestalt IT and Organizer of Tech Field Day. Find Stephen’s writing at GestaltIT.com and on Twitter at @SFoskett
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