Could machine learning mean the end of understanding in science?

If prediction is in fact the primary goal of science, how should we modify the scientific method, the algorithm that for centuries has allowed us to identify errors and correct them?

Interesting piece by UofT’s Amar Vutha on how machine learning is reshaping the scientific landscape. I fundamentally disagree that the goal of science is predicting nature. Predicting is great for applied problems like weather-forecasting, but neglecting the understanding of things bears a great risk, because then the scientific method is basically reduced to guessing what the next step could be and is no longer effective at iterating towards a fundamental truth. With all due respect, let’s leave that “goal-oriented” approach to problem solvers and engineering.

How to Use t-SNE Effectively

Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. By exploring how it behaves in simple cases, we can learn to use it more effectively.

Working with t-SNE myself recently I found this post on Distill tremendously helpful. Especially the interactive part taught me what I could expect from this visualization method and what not.

How to delete Time Machine snapshots on your Mac

Nice post by Glenn Fleishman about how to delete Time Machine snapshots on Mac. Ever since APFS, Timemachine snapshots are automatically generated and deleted if Hard Disk space becomes rare. However if you want to manage that yourself (as most powerusers tend to want) here’s your solution.

Overcast 4.2: The privacy update

Nice informational post by Marco Arment about how the new Overcast 4.2 protects your privacy while listening to podcasts.

One of the ways publishers try to get around the limitations of the current model is by embedding remote images or invisible “tracking pixels” in each episode’s HTML show notes. When displayed in most apps, the images are automatically loaded from an analytics server, which can then record and track more information about you.

This is the first time I heard about tracking-pixels and I am horrified by the idea. As much as I am fascinated by data-analysis, I think this is just plainly wrong, one shouldn’t aquire data like this and I am convinced that these recent developments in podcasting are misguided.