ianbooker

They really do a lot to correct for bias, but is it enough?

I would suspect that a prosperous and thereby complex economy also has more resource to discover or document inscriptions. While they talk about researcher bias, they do not really mitigate this.

And yes, I searched the article and the extensive additional material.

Still a valuable contribution.

PageRank is fascinating, since it is so easy to explain.

Yet, this is not even half the work. It like a third of the way.

Before you could have invented PageRank, you must think in graphs. That is possible in 1996, but not as widespread as today.

After you invented PageRank, you still need to deploy it. Again, possible but challenging as well. Is Python performant enough in 96? Can you afford more than 4MB RAM?

At least Lego will not sue you for using their bricks to build a server rack in 1996.

> Since John Hammond "spared no expense", it is fair to say he picked 1GiB version at $3,598 a piece. That would give them 7 GiB of storage for a 2026 equivalent of $33,223.70. In 2026, 7 GiB of HDD would cost $0.49.

Did anyone ever try to estimate storage inflation across time? 7GiB could be one or two pc games in 2026, in 1992 one games likely was 1.4MB.

I use USB to teach students about European Union regulatory policies, because this is one obvious standard they all can connect to. (Pun intended).

Throughout the years they were cautious when it was introduced, thankful after it was established, and now they are too young to know any other world.

And yes, USB as main connection standard was driven by Apple. But USB as main charging standard was set by the EU.

> This couldn't have happened 10 years ago.

I agree. Something similar could have happened 30 years ago, and it did, see Transport Tycoon (or a lot of early games). But from 2000 to 2020?

I see "AI and R" in three perspectives:

First, usage: Using R for our undergrads in time of LLMs is brilliant. ChatGPT slops out working code for their needs. Not pretty but works better that in 2022.

Second, development: Mastering R is hard, because its kalkül. Tidyverse mediates some of it, but still. This is the perfect breeding ground for slopification. Lets see.

Third, errata: I would love to know the percentage of science built on R to this day. I mean insights and analysis supported by it and it vast packages. What if somewhere, deep down in the stack there is an ancient bug that dented all of this? I think AI might help us here, or review slop will negate this?

Confounders are included and therefore controlled for, and causality can be assumed since the DV is an event/hazard. This is also the reason you end up with the seemingly high average...

Why is Nvidia so central to LLMs? Because they embraced ML a decade ago. Apple did as well, machine learning is central to so many things in the iPhone. Its not so surprising then, that a strong showing in ML sets you up good for LLMs..

Its been years since I felt urged to congratulate someone for their "webdesign", but this is really good. No boring glossy landing picture, but a distinct claim, and the the before / whoisit / after Element is unique, in a good way.

Kidnapper is likely not Deutsche Bahn but a regional subsidairy.

This is an effect of privatization gone wrong, with the national service, the infrastructure, the regional services (each), the network (not in infra), cargo and then some (sub)companies split for privatisation and an IPO that never happened. The highly segmented network is not digitalized in to any standard, so regional trains have to operate in policy frameworks and network cells that favor long distance trains. Its utter chaos on a daily basis.

The reverse is kind of true: In the beginning, SVGs were not really an option since it lacked adoption across all major browsers, or more specifically its integration was very heterogenous.

So a SVG you authored 20 years ago for some browser will likely work everywhere today.

Solar sun roofs for ICEs were a thing 20 years ago. Solar was able to ventilate your car on sunny days.