Pure bias reinforcing dopamine right there. @mgershoff summarizes #PrivacybyDesign at #measurecampto

"Collect everything" is easy to say. It can even be rationalized. Think a little deeper, though, and the dangers of this mindset are pretty easy to surface. That's the topic of our latest episode with @mgershoff! analyticshour.io/2024/09/03/…

Privacy by design and more with @mgershoff at @cbusdaw !

These recent slides from Susan Athey and Guido Imbens at NBER are a great recent review of the most valuable data science methods I'm aware of. They cover tons of ground with lots of pointers. conference.nber.org/confer/2…

1. osf.io/preprints/socarxiv/2a… Meta-analyses combine trials that are presumably *independent*. But social relatedness between researchers --> more similar effect estimates, suggesting dependency via same "school of thought"

Predicting the next word "only" is sufficient for language models to learn a large body of knowledge that enables then to code, answer questions, understand many topics, chat, and so on. This is clear to many researchers now, and there are nice tutorials on why this works by @ilyasut resorting to compression ( youtube.com/watch?v=AKMuA_TV… ) and by @geoffreyhinton ( youtube.com/watch?v=iHCeAotH… ). However, the emergence of types of understanding is not unique to language models. In arxiv.org/pdf/1804.06318.pdf by @notmisha and @brandondamos the authors trained models to predict the next few time stems of over a hundred robot hand sensors (Touch, Gyro, Accelerometer, Joint Info, Actuator Info, etc.). They ten found out that they could regress the shape of the thing the hand was touching from the activations of the neural networks using probes. That is, the model developed an internal representation of shapes even though it was simply used to predict "only" the next few senses. Awareness follows from simple predictions and interaction with the world.

IMO, the only thing an intro stats student really must learn is that the goal of "statistics" (inference, really) is to quantify uncertainty. Too many students get so lost in the mechanics that they loose site of what they are trying to do.

This is so very, very true. SQL is one of the most valuable skills for anyone working with data. It’s more than just about how to run queries - it helps you understand the entities you are querying better, and it gives you stronger mental models to make sense of the world.