ML Tasks on Swift Without Python, Neural Networks and Libraries
Too Long; Didn’t Read
This article is not a guide on how to write something in Swift; rather, it is more like a thought piece about the current mindset of many developers who view Python as a bridge to the ultimate solution for ML libraries that will resolve any problem or task they encounter, regardless of the language they are using. I would wager that most developers prefer to invest their time in finding ways to integrate Python libraries into their language/environment rather than considering alternative solutions without them. While this is not inherently bad – reuse has been a significant driver of progress in IT over the past few decades – I have started to sense that many developers no longer even consider alternative solutions. This mindset becomes even more entrenched with the current state and advancements in Large Language Models. We will take a classic ML task and solve it by using Swift language and no Libraries.
Too Long; Didn’t Read
This article is not a guide on how to write something in Swift; rather, it is more like a thought piece about the current mindset of many developers who view Python as a bridge to the ultimate solution for ML libraries that will resolve any problem or task they encounter, regardless of the language they are using. I would wager that most developers prefer to invest their time in finding ways to integrate Python libraries into their language/environment rather than considering alternative solutions without them. While this is not inherently bad – reuse has been a significant driver of progress in IT over the past few decades – I have started to sense that many developers no longer even consider alternative solutions. This mindset becomes even more entrenched with the current state and advancements in Large Language Models. We will take a classic ML task and solve it by using Swift language and no Libraries.
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