When To Use Free Or Open Solutions For AI

There are many free and open platforms and tools for developers of AI solutions. Should you go for them, or avoid them?

- SWAPNIL SHARMA

Today artificial intelligence (AI) systems are everywhere. They can do a lot of unbelievable things, like predicting behaviour and patterns.

Many big tech companies are integrating AI into their hardware as well. Apple has incorporated it into its chips to perform various machine learning (ML) operations. Even graphical processing units today are having some form of AI integrations for improved performance within them, which was not the case a few years ago.

AI comes at a cost

But AI does not come cheap. We have been using classical AI for a while now. But with the emergence of neural networks, things have changed drastically. We have reached a point where you can just put a prompt and generate images straight out of your imagination.

Neural networking was discovered twenty years ago and the reason it worked back then is computation. Adding computational layers back then was not easy and required a huge cost to implement, but that is not the case today.

Machine learning is highly mathematically intensive and requires a lot of statistical knowledge. Applying artificial intelligence solutions is not a child’s play as it requires you to study every aspect of it thoroughly. Only then will you be able to make those models and apply them.

It is not an easy task to learn tools like Tensorflow and Kiras to spin up your own servers, and that is where we need free and open AI solutions. There was a time when using ML solutions was not so easy either, as it required a lot of steps to be followed. Thankfully, that is not the case today as you can pick the model that suits your needs the best to work on.

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