Spoiler alert: it does not understand Golang that well. But it’s still impressive. There are many resources online for prompting ChatGPT about Python code. I figure I’d try it with Golang since that’s my primary programming language. And secretly, I want to see if it’s good enough to obsolete me…

An opinionated sample answer to an interesting system design interview question. This blog post tries to answer this system design question on Leetcode: how do you distribute information to a large number of machines in a data center? The question is brief enough. It’s on us to explore its concrete…

A general introduction to a list of canonical tasks and corresponding datasets to measure your medical natural language processing — The field of natural language processing (NLP) has evolved really fast in recent years. Breakthroughs like transformer, BERT, GPT have emerged one after another. Practitioners of all industries are exploring how to leverage the exciting development of NLP in their specific business domains and workflows [1]. One such industry that…

A few canonical and research-proven techniques to adapt large language models to domain specific tasks and the intuition of why they are effective. — Ever since being popularized by ChatGPT in late 2022, large language models (LLM) have attracted intense interest from the research and industry communities. While general chatbot is an obvious application of large language models, enterprises are thinking about how to integrate large language models into their business workflows to leverage…

A visual and in-depth explanation of its implementations, suitable for readers who have heard of Kubernetes Informer and want to study its internal mechanics. Recently I dug into the Kubernetes Informer implementation in the official client-go library (release-1.26). I figured I’d write a short blog post to document the learnings…

The common diagnoses you’ll hear in healthcare data analysis. One canonical task in healthcare data analysis is to predict the diagnoses. If hospitals can predict it earlier, nurses and physicians can intervene preventatively to obviate the onset or deterioration of those diseases. We’ll look at a few common clinical conditions…

Simple and effective methods — designed for recurrent neural networks — that have stood the test of extensive academic evaluations — Background A great deal of medical data is, by nature, time series data — cardiogram, temperature monitoring, blood pressure monitoring, regular nurse checkups, and so many more. There is a sea of valuable information embedded in the trends, patterns, spikes and dips of those medical charts, waiting to be uncovered…

The common concepts that you’ll hear in healthcare data analysis. I’ve developed an interest in healthcare data analysis recently. Healthcare data analysis is already a common well-established practice. But as the healthcare industry adopts more open interoperable data standards and cloud technologies, which has been happening in the past few…

Simplified illustration based on Google Brain’s “scalable and accurate deep learning with electronic health records” and its supplementary materials. Background The healthcare industry started systematically digitizing healthcare data more than a decade ago. The hope is that one day, we’ll be able to harmonize data from disparate…