A (Semantic) Search Engine will not Make you Organized

Maybe this time it will work?

A (Semantic) Search Engine will not Make you Organized

 Posted on July 6, 2025  |  3 minutes  |  578 words  | 

Ah it is so alluring! With this search engine you will finally be able to find the documents of your organization! This vendor even has a large language model so you can search on ‘meaning’ not only actual words! Alas one million dollars later you still can’t find your shit. I think the main reason you can’t find shit in your company is because you don’t organize your documents. As a messy person I empathize, but you need to get your shit together. [Read More]

The Disney+ App Really Sucks

The Disney+ App Really Sucks

 Posted on October 28, 2024   (Last modified on October 29, 2024)  |  3 minutes  |  429 words  | 

The disney+ app, really sucks. I have an Android device that hosts the app and I only every play on the chromecast. To be clear, I use a chromecast on a TV with CEC enabled. That is, you can send commands from your remote to connected devices. This is really nice, you can pauze, play, stop, rewind, toggle subtitles. And you can skip ahead, and back. There is even a button to accept things. [Read More]
webtechnologies  chromecast 

So you've just lost a million dollars in the genAI hype

what lessons can you learn?

 Posted on August 1, 2024  |  4 minutes  |  790 words  | 

Hi C-level person! Are you feeling down because AI is not working for you? Let me know if this is you: A smug consultant sold you a genAI solution. By now you’ve realised that it doesn’t work, it can not work in theory and now it also doesn’t work in practice. You still have data quality issues, and your promised profits are non-existing. Are there any lessons you can learn from this fiasco? [Read More]
LLMs  genAI  pseudoprofoundBS 

Just enough kubernetes to be dangerous

Just enough kubernetes to be dangerous

 Posted on July 30, 2024  |  2 minutes  |  401 words  | 

As a data scientist that wants to achieve production results, one of the best options is to make your work available in kubernetes. Because kubernetes runs on all clouds and because many organizations use kubernetes. Make your prediction API available in kubernetes and your organization can ‘just’ plug it into their systems. Many data scientists don’t know anything about docker, not to mention kubernetes and its main tool helm. I think you should learn and practice just enough helm to be dangerous1. [Read More]
data_science  kubernetes  MLOps  production 

An offline first smart home is really nice

Local first smart home was a great decision

An offline first smart home is really nice

 Posted on July 16, 2024  |  1 minutes  |  206 words  | 

Recently my internet connection was down for several days, where I live in Europe that almost never happens. I am so used to having an internet connection that I really had to adjust to this. Of course having mobile phones with data connections means my online addiction was regularly fed, but I can’t roam my home lan over my mobile connection (yet?). Home assistant just kept going and that is awesome! [Read More]
home-assistant  webtechnologies  smart-home 

Adaptive Plasticity and Life History Theory

April cools post

 Posted on April 1, 2024  |  5 minutes  |  856 words  | 

Happy April 1st! This post is part of April Cools Club: an April 1st effort to publish genuine essays on unexpected topics. I want to tell you about a fascinating topic of adaptive plasticity and life history theory. I haven’t read anything about this anymore since 2014 but the ideas have kept a place in my head (lived there rent free? a weird expression). This is also a free day for me, so I’m going to put minimal effort in writing about this topic, I am going to write without consulting even wikipedia. [Read More]
april-cools  biology 

High and Low Variance in Data Science Work

Consistency or peaks, pick one

High and Low Variance in Data Science Work

 Posted on March 6, 2023   (Last modified on August 13, 2023)  |  2 minutes  |  248 words  | 

I recently read “High Variance Management” by Sebas Bensu and this made me think about datascience work. First some examples from the post: Some work needs to be consistent, not extraordinary but always very nearly the same. Theatre actors performing multiple shows per week need to deliver their acting in the same way every day. Their work is low variance. Some work needs superb results, results you don’t know if you can reach it but you try it many times and between all of the failures, you might find gold. [Read More]
MLOps 

Are you a Fearless Deployer?

Fast experimentation and confident deployments should be your goal

Are you a Fearless Deployer?

 Posted on November 21, 2022  |  2 minutes  |  422 words  | 

how do you feel when you press the ‘deploy to production’ button? Confident, slightly afraid? I bet many data scientists find it a bit scary. It’s worth it to dig a bit deeper into this fear. In my ideal world we are not scared at all. We have a devops mindset. We have no anxiety, no fears at all. You should be confident that the deployment pipeline takes care of everything. [Read More]
deployment  iteration  MLOps  training-pipeline 

William Sealy Gosset one of the first data scientists

The father of the t-distribution

 Posted on August 17, 2019   (Last modified on November 9, 2022)  |  3 minutes  |  600 words  | 

I think William Sealy Gosset, better known as ‘Student’ is the first data scientist. He used math to solve real world business problems, he worked on experimental design, small sample statistics, quality control, and beer. In fact, I think we should start a fanclub! And as the first member of that fanclub, I have been to the Guinness brewery to take a picture of Gosset’s only visible legacy there. W. S. [Read More]
gosset  data_science 

Make more useless packages!

For fun! and like learning, but mostly fun, really...

 Posted on August 31, 2018   (Last modified on November 9, 2022)  |  4 minutes  |  646 words  | 

You should make more useless packages. To be more specific: make packages that are useful to you, but might be useless to others. Because building silly stuff is fun and sets the bar low for you to play and learn. I’m a big fan of Simone Giertz (see all the gifs in this post). Simone is known as the ‘Queen of Shitty Robots’ and has a youtube channel where she builds robots that are, uhm, not very good at the thing they’re designed for. [Read More]
package