Over 15 years ago, I decided I needed to do a website for my photography hobby. I also wanted to do one for travel. Being a software engineer and a geek, I wrote it in HTML. Websites then were very simple, so what I had wasn’t fancy either, just a couple of pages with a blurb about me, and a bunch of photos.
The next version was fancier – I wanted it to pick up photos automatically from a directory structure, so I wrote a bunch of Perl scripts and had an automated website. If I uploaded photos into the structure in a particular way, the scripts would automatically pick them up and display them.
The third version (and partly my current fourth) was much fancier. I purchased a nice template, and customized it by hand. I was still fluent with Emacs and HTML, so it was easy.
My current version is still a template, but now I’m not so good with Emacs and HTML any more, so for the parts I cannot manage, such as my blog, I use WordPress. WordPress (or Wix, Hugo, etc.) is what anyone would use these days if you wanted to build and run a website. This has become the norm – people expect slick websites, and nobody wants to actually code them. And WordPress is not just for building, it’s used to manage the website for ever and monitor, update – all those things required for production.
The Relationship to Machine Learning
So, what WordPress did to websites is mostly what KuberLab is doing to Machine Learning (KuberLab does more, but this is a good analogy). In the early days the companies like Google and Facebook, that have already crossed the Machine Learning Application deployment chasm, probably did the equivalent of what I did with my first HTML website. Then of course, they developed tools and frameworks, and now it became like my CGI-Perl website. With the current movement towards democratization of machine learning, there is now a lot of code available via the Kaggle competitions, Github repositories and so on. So, this is like the template website, one can pick up somebody’s code, tinker with it, and use it for oneself. This is also what is happening on the cloud, with AWS, GCP, Azure and others providing many tools, frameworks and templates for building machine learning applications.
KuberLab is like the WordPress of machine learning. If you are an enterprise wanting to deploy a machine learning application, this is what you want. Sure, you could put time and effort, spend lots of money, and build it yourself and perhaps even feel good about it. But that effort doesn’t scale, deviates from your core business, and will not be production grade for everyone. For this, you need KuberLab. KuberLab is the platform that helps enterprises accelerate their adoption of AI applications. See http://www.kuberlab.com, or try it out at https://go.kuberlab.io