In the last couple of years, they have certainly managed to make a lot of waves in the digital landscape and have made app development much more accessible to the general public. However, being a great tool for app development, does not mean it will be a great tool for AI use cases.So here we are; we’ve got these amazing low-code platforms like Mendix or Outsystems that help companies to deliver new apps quickly, and without having to hire a bunch of developers which are scarce.
Low-code platforms are made for ease of use and rapid development, they are simply not made for efficiency and speed. For simple applications, that’s perfectly fine, but for AI this can really be a blocker. Think about a recommendation model for instance, that uses AI to recommend items or topics to app users. A model like that needs to be able to make a recommendation in the milliseconds range to be effective otherwise you will lose customers.
The most important thing when putting AI behind a low-code app is that your AI code needs to be callable from your app. To do so, it’s good to have your AI code reside behind an API. That way you can just send a request from your low-code app, to the API, which will, in turn, run the AI code.
I disagree. To say that low-code automatically assumes high overhead and latency and hence unsuitable for AI? Not a valid assumption at all... That's like saying only assembly language is useful, because higher level languages like Java & Python add too much overhead.
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