Last modified: May-29-2022, 01:43PM +08

The Story So Far

It was around late 2018 when I decided to go knee-deep into the world of Artificial Intelligence(AI), Machine Learning(ML) and finally Deep Learning(DL). Coming with the background from biomedical science and psychology, meant that I have to pick up new entire fields relating to Computer Science(CS), software engineering(SE) and AI.

Putting aside new concepts, terminologies and principles. All these fields have one thing in common and that is mathematics. Combing through tons of research papers and reference books just to build a concrete foundational understanding of these new complexities proved to be extremely intensive. I realized one simple trick to filter technical jargon and that is go straight to the math.

Over the same period, I have basically become a sponge for the new influx of information and this is my humble attempt at the documentation and review of my life-long learning process.

Current Projects(2021-Beyond)

• tfx, kubeflow pipelines
• tensorflow-js models running in web browser
• tensorflow lite micro models running on embedded microcontroller
• nvidia jarvis(beta) as a backend service for flutter application
• implementation of modern multi-modal DL architectures

Text Editor

• Vim

I started with PyCharm without knowledge of vim’s existence at the time. Once I was using ubuntu for my daily and work, vim resonates with me instantly. It felt like a superpower with features such as macros, registers and integration with shell tools. Now I’m running it with ~30 plugins, supporting various languages/DSL, as well as development tools while keeping its startup time under 350ms.

Programming Languages

• Python
• C/C++, CUDA
• Dart
• Go
• JavaScript, TypeScript
• Rust

I have tried my best to steer clear of JavaScript, HTML and CSS as much as possible. Each passing year it seems less and less likely, and I am not looking forward to these days at all. Fingers crossed.

AI Software Stack