Hm? We sync our calendars using Nextcloud, but admittedly, that's not everyone's cup of tea.
216 karma · joined December 13, 2019
Not sure where you pulled 30 Mb/s for Viasat service but it regularly tests more than 2x as fast as that (on the current-gen satellites, the newest of which is 5 years-old by now. Viasat-3 Americas has actually over 5x the capacity of Viasat-2 along with a big bag of other goodies that will enable a class of service heretofore unseen.)
No doubt everyone has different experiences and tolerance levels for latency, but, really, I think the latency issue is vastly overblown.
An article like this is a nice alarm bell that maybe they should reconsider their approach, but nothing will really change until it impacts their bottom line, which is getting correct work done on a timely schedule.
That said, I think it's fair to say particle physics hasn't had any major discoveries since the Higgs and no sure-fire theoretical path toward one, either, so the best and brightest may start looking at other fields.
And this applied to both tenured and untenured professors. Don't want to name names but one of the high up profs I chatted with there worked roughly 60 hours a week, 6 10-hour days. I mean, he loved it, and he had a lot of responsibility, but I think it's fair to say it's pretty much all he did. His wife mostly traveled and his daughter was already in undergrad by then.
It is genuinely unclear to me how a new prof could hope to compete with that or make a meaningful contribution when even the "old guard" have given up everything to just work.
In my brief time there, it was not uncommon to hear stories of people who had moved there and not even unpacked all of their belongings after a year or more.
On the plus side, if you love particle physics and/or the surrounding context, it's one of the best places to be. On the minus side, you'll have to give up everything else and be quite smart in addition to move ahead.
We had a dataset with just about 30 records and about twice as many features, about 1:3 class balance between positive and negative. Not an impossible situation at all, but there was a big premium on performance, so we threw the book at it.
Lo and behold, SVM with some particular parameters comes out on top. Ship it, right?
Not so fast, what decision did the model learn? Turns out, the model was learning decision boundaries that did not make sense. It was overfitting because the model did not know about what kinds of decision boundaries were allowable.
In the end, someone looked at a 2D scatter plot, drew a line and called it a day. It took a fraction of the effort and time of running through a box of models. It'll save the company $MM and it's trivially explainable to engineers and execs.
AutoML with blind application would've completely botched this.
Idk, right now AWS is a money printing machine.
My understanding is that Zillow relies on realtors to add their listings, so that means, maybe-it-happens, maybe-it-doesn't, entry errors, maybe-it's-updated, maybe-it's not...
Eh, it's been a while now, though, and I guess most of that has gotten worked out.
To be honest, Desktops reached their peak for me with Gnome 2. I'm using MATE and I'm good.
To be clear, I love getting my food from the Central Valley, but I also think there are overdue discussions to be had about where the water's going and how much utility we're getting from it.