What I learned from looking at 200 machine learning tools

huyenchip.com

To better understand the landscape of available tools for machine learning production, I decided to look up every AI/ML tool I could find.

Really good post—it pulls ML/AI tooling out of the overall ML/AI "vertical applications". In a given year, the author found that only 7 out of 50 ML/AI startups were focused on building tooling in the space whereas the other 43 were building applications to help businesses solve problems using ML/AI (like better email targeting, etc.)

The whole post is good, but I found the above chart to be particularly interesting. You can clearly see innovation moving up the stack—moving from data pipeline tools to modeling & training tools to serving infrastructure. This makes complete sense, and is a very solid foundation from which to make predictions about where the industry is headed next.

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