INSUBCONTINENT EXCLUSIVE:
Streamlit, a new machine learning startup from industry veterans who worked at GoogleX and Zoox, launched today with a $6 million seed
investment and a flexible new open-source tool to make it easier for machine learning engineers to create custom applications to interact
with the data in their models.The seed round was led by Gradient Ventures with participation from Bloomberg Beta
Combinator partner Daniel Gross, Docker co-founder Solomon Hykes and Insight Data Science CEO Jake Klamka.As for the product, Streamlit
co-founder Adrien Treuille says as machine learning engineers, he and his co-founders were in a unique position to understand the needs of
engineers and build a tool to meet their requirements
Rather than building a one-size-fits-all tool, the key was developing a solution that was flexible enough to serve multiple requirements,
machine learning engineers to interact with the dataTreuille says that highly trained machine learning engineers that have a unique set of
skills actually end up spending an inordinate amount of their time building tools to understand the vast amounts of data they have
Streamlit is trying to help them build these tools faster using the kind of programming tools with which they are used to working.He says
that with a few lines of code, a machine learning engineer can very quickly begin building tools to understand the data and help them
interact with it in whichever way makes sense based on the type of data
That may mean building a set of sliders with different variables to interact with the data, or simply creating tables with subsets of data
that make sense to the engineer.Treuille says that this toolset has the potential to dramatically transform the way machine learning
engineers work with the data in their models
