Miscellaneous

Initially, I wanted this post to focus solely on metrics in machine learning. However, the concept of metrics is far more universal, and it doesn’t make sense to treat it as an isolated problem. This is more of a philosophical post, the ultimate goal is to make you think and reflect. We live surrounded by metrics: grades from teachers, performance reviews from employers, publication counts in academia, FLOPs in computing, ELO in chess, salary, IQ for intelligence, movie ratings on IMDB, book ratings on Goodreads, stars/reviews on Amazon, election results in democracies, F1 score in machine learning, GDP for countries, EBITDA in finance, likes/followers on Instagram, time spent on TikTok for content recommendation algorithms, etc. ...

Last week I came across this very high-quality image, at first I thought that it must be one of those expensive satellites that cost millions of dollars. Then I started digging and found out how ignorant i am about the recent advances in satellites. Apparently, there are three main orbits used by current satellites [1]: LEO (Low Earth Orbit): ~160–2,000 km; short orbital period (90–120 min); low latency; used for Earth observation, Starlink, ISS. MEO (Medium Earth Orbit) ~2,000–35,786 km; orbital period ~2–12 hrs; GPS/GNSS satellites. GEO (Geostationary Earth Orbit): exactly 35,786 km, equatorial; 24-hr period, appears fixed above Earth; ideal for telecom, TV, weather satellites. Before talking about the satellites, we need to understand the main driver of these advancements. There’s been a huge decrease on rocket failure rates and reduction in the costs of putting them into orbit. To put things in perspective, between 1970s and the 2000s the average launch was about 18.5k USD/kg, while recently the Falcon Heavy only costs around 1.4k USD/kg (more than 10x reduction!!!) [2]. Also, success rate over 99.46% [5]. ...

I always thought that actions matter more than words. The ultimate expression of this idea is the stock market and, more recently, prediction markets (such as Polymarket). For example, you can bet on a wide variety of topics that stretch from who might win an election to how many tweets Elon Musk will post in a single day. Over the past few years, public trust in institutions and journalism has eroded [1], and this distrust has fueled the rise of new financial instruments like prediction markets. This data manipulation became clear during the last US election, where a big gap emerged between conventional polling data and the probabilities implied by market activity [2]. ...