I may be biased since I interned at Google in 2013 and 2014, but Google in the 2000s and early 2010s felt downright magical as someone who wanted to pursue a career in systems software research. They made impressive technologies that still hold up today, like MapReduce, BigTable, and Spanner. They hired many legends of computer science and software engineering, such as Rob Pike and Jeff Dean.
I’m concerned about the power that Google and other Big Tech companies have, but from a technical point of view Google has a lot of impressive technologies, and from a workplace standpoint, it seemed idyllic back in the early 2010s, though I’ve heard the work culture has changed in the past decade, and I may have rose-colored glasses from only being an intern there, never a full-timer.
> who wanted to pursue a career in systems software research
I interacted with many professors in OS research and other adjacent systems fields when touring grad schools and I heard or saw that some were extremely toxic or intense compared to other fields I saw. With OS at least, big tech companies seem to hold a lot of influence over research directions (eg. so much of it is specifically for AI datacenters, or for one company's AI datacenter problems), and I asked OS professors about this and got disheartened replies that there was nothing they could do because of the incentives in the field. I was quite disillusioned. I know that AI being a hot new topic makes leaves more stones unturned and might lead to more publishability, but it's still depressing.
I’m out of the loop these days in systems research since I largely focus on programming languages and AI these days (though I still love systems) and I treat research more as a side hobby rather than a full-fledged career. It’s disappointing to hear about toxic systems labs. There’s also the “funding-or-perish” and “publish-or-perish” pressures of academia. This is one of the reasons why I teach at a community college, where 8 months of the year I focus on teaching, leaving me 4 months of break per year where I could do research without having to worry about my tenure chances or about funding, though it would be nice to be able to pay some students to help with research projects, and it would also be nice to have the funds to buy expensive equipment such as GPUs with large amounts of RAM.
That seems like a great setup, and maybe something I'll think about after grad school (or maybe look into being a professor at LACs or less research oriented schools)! I'm already sort of nervous about doing the PhD because of the insane toxicity I've encountered and the pressure to do research in direct support of industry (which is probably exacerbated by NSF funding being impossible to get), but hopefully I'll find things to enjoy about it. The career prospects also seem tenuous, as a lot of outcomes seem to be "go through a brutal tenure process" or work for FAANG/adjacent (probably not even in research since places like MSR are difficult to get). But I would like the creative freedom a professorship might offer.
There are lots of brilliant people at Google who do no evil.
The fact that the company makes evil decisions about the direction of the web, privacy, and performs blatantly monopolistic actions does not outweigh the good things people at Google have done. At least not yet.
You can hate the company but love the brilliant work the engineers have done. The same can be said of lots of companies: Apple, Anthropic, ...
Meta, on the other hand, I'm not so sure about. It's less of an overt monopoly, but some of its actions are heinously amoral.
And this folks is exactly the reason we need to remember that there are real costs to demanding transparency. There's a reason some things should have stayed redacted.
Weak country
Weak constitution
Thoughts and prayers masquerading as checks and balances
Military coup now, seize the global assets of everyone involved in this shambles of an administration, imprison them and their families. Disappear them.
Rewrite the constitution so this can never happen again.
It's like looking at the EU now and wondering, how did they not see this glaring dependency before now? Both the petro energy source and the US military support were never as secure as it seems they were assumed to be.
Here in the US, we're still sitting on a constitution from 250 years ago. Apparently no one though an incoming presidential administration would rape and pillage the place like we've seen in the last year and a half.
European countries did largely overhaul their constitutional documents after WWII. The EU in general has much more modern legislative bodies, and electoral systems.
Here in the US, we're still stuck with founding documents that expect Pony Express to deliver the ballots 8-/
Founding documents are worthless if you don't care to honor them.
EU might have more modern legislation but even there the far right is starting to realize when they are in power they can generally ignore the legislation or work quickly to dismantle it. Trump showed and emboldened them, tech bros are providing funding and oligarchs are steadily gaining power. It's quickly coming from the east and only reason EU might be a bit more ready than US is that it's many decentralized countries with always shifting powers.
Tax the tokens, I actually like that idea. It'd be like a gasoline tax -- drivers pay for infrastructure maintenance. In this case, token consumers would pay for the increased burden on the grid.
That's not true. From the article, type 2 is more familial than type 1, but not all of that association is genetic.
As a more concrete demonstration, the type 1 genetic risk score (GRS) has good predictability of the risk of someone getting type 1 diabetes. We have linked certain genetic variants to increased or decreased risk of getting type 1 diabetes (and it's mostly in the HLA complex on chromosome 6 that significantly influences the immune system). The AUC (area under curve) of the score's ROC curve is 0.87, which is good. We use the type 1 GRS for patients incoming with type 1-like symptoms to separate out those likely to have rare genetic conditions instead, alongside antibody testing, and it works very well.
The type 2 GRS is very weak in comparison. We haven't found much link between genetics and type 2 risk that we can use to predict the risk. The AUC of the type 2 GRS is only 0.63 in the very best studies, which is a poor predictor.
Having said that, type 2 risk varies quite considerably with race, with South Asians being more susceptible to type 2 diabetes than much of the rest of the world.
Note, an AUC of 0.5 indicates no predictive value whatsoever, and an AUC of 1.0 indicates perfect prediction.
