Location: Blog Menu ▼

I write about design, technology, and people. Sometimes I take photos of places I visit.

Featured posts

Archive – if you're interested in older posts or looking for something specific.

Latest posts

Learning machine learning

The hype around artificial intelligence (AI) and machine learning (ML) skyrocketed in late 2016. I felt at the time that my lack of understanding of the topics affected my ability to discuss them with others and my ability to grapple with some of the more existential questions around algorithm fairness. At that moment I decided to immerse myself in the world of data science. I’ll share the resources and educational materials I’ve used for more than a year with a hope that you’ll find them helpful too. Read more

My thoughts on machine learning

Context: I’ve spent around 15 months learning statistics and machine learning (ML). I’ve written a post about the journey and resources I’ve used. Here I try to share my thoughts and observations about what ML is in essence, why we experienced the recent hype, and some of the potential dangers and opportunities that await us in the future.

Machine learning is pattern recognition

If I had to summarize what ML is as practiced today, I would say pattern recognition. Many of the algorithms try to find patterns in data or build patterns from rules and the environment. Many things are a pattern in some form or another. For example, home prices usually increase with size, a disease has similar symptoms across a population, people in the same life situation buy similar things (young families buy a lot of baby stuff), similar objects have recognizable shapes and color, traffic participants respond to changes in the environment similarly, and speech is just a collection of patterns of sound waves. There are more examples than I can think of, and that’s the beauty of ML—you can use it for so many things. It doesn’t mean it will replace everything we do today, just that it can help us in more areas than it does at the moment. Read more

Good books I read in 2017

Books on a shelf.

Even though I’ve listed only a few books on the topic, last year I read a lot about current technology and how it may affect our society in the future. Ethics, machines that “think,” and our inability to comprehend complexity around us were the themes of the year, prompted by my short post about fairness in late 2016. Here are some of the books you should consider putting on your reading list. Read more

Year in review 2017

Beach stones delicately balanced on top of each other.

As I was reflecting on the past year, the phrase “delicate balance” was the only thing that came to mind. There is one point at which opposing forces form a balance between work and family time, between pushing yourself to the limit and taking a break, and between being online and offline. There isn’t one correct ratio—it depends on the individual and the environment. I found mine in 2017. Read more

Red train in snow

A red train blazes next to a snowy path.

Red and white, and a lot of snow—so very Swiss.

If you want to read more, check out the archive.

Back to top ▲