Antony Belov

It so happened that for the covers of my works, I use style transfer based on a painting I really like. A free web app has been helping me with this. But sometimes its responses are poor. Plus, I worry that at some point it might go paid or bombard me with ads. So I started looking for a more reliable alternative.

My first thought was to use ChatGPT and its built-in tools. But no matter how promising the results seemed, sometimes the resources weren't enough, or it suspected me of improper use of photos. I could’ve tried another AI service or found a specialized solution, but then a second thought hit me.

The second thought - why not build my own? The task seems simple: apply the style from one image to another. The result would be an in-house solution and a better understanding of how it works “under the hood”. Long story short,

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Web Performance is one of those topics that’s constantly discussed as crucial for the modern web. It’s often framed as a key factor for user experience (UX), conversions, SEO, and overall success on the Internet. Every year kicks off with an article titled “New Challenges and Why Fast Websites Will Win in 20xx.”

Yet when it comes to implementation, performance tasks in the backlog often don’t get the priority they deserve. This happens for two main reasons, two key questions arise:

1.Is it really that important? - Users aren’t complaining; everything loads quickly for me, too. Plus, our internal research hasn’t shown a clear correlation between performance metrics and search rankings. What even is a CLS of 0.4, and why should I care?

2.Is it worth the effort? - There are too many metrics; they’re confusing, and new ones keep popping up all the time. On top of that, the tools are complex and expensive. Wouldn’t it be better to invest resources in product features instead?

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