I agree with this. From my experience most of the data scientists I have worked with didn't exit the world of Jupyter notebooks. For them, code management, CI/CD, dev/stage/prod separation, etc. is a world of its own that they are not very comfortable with. Heck, they even used Sagemaker to create git repo for their Jupyter notebooks.
It doesn't mean that there aren't data scientists who have some engineering experience as well, but this seems to be rare. For that reason, getting those ML models that they painstakingly build to where they'll generate some real value is super hard. They just don't know where to start.
Working across multiple teams and multiple functions is very challenging and it often creates friction. Therefore, creating tools and systems that will enable those data scientists to see the actual value of their labor is paramount.
That's why we're seeing a huge resurgence of so called MLOps tools and platforms that aim to solve all or some of the problems of the entire stack. We are very very early in this journey, but I believe 2020's will be for ML and AI what 2010's were for the cloud and data, ie. new Snowflakes and Databricks but for the actual ML apps. It's exciting.
It doesn't mean that there aren't data scientists who have some engineering experience as well, but this seems to be rare. For that reason, getting those ML models that they painstakingly build to where they'll generate some real value is super hard. They just don't know where to start. Working across multiple teams and multiple functions is very challenging and it often creates friction. Therefore, creating tools and systems that will enable those data scientists to see the actual value of their labor is paramount.
That's why we're seeing a huge resurgence of so called MLOps tools and platforms that aim to solve all or some of the problems of the entire stack. We are very very early in this journey, but I believe 2020's will be for ML and AI what 2010's were for the cloud and data, ie. new Snowflakes and Databricks but for the actual ML apps. It's exciting.