I think many CS degrees teach FP, I remember learning a variant of SML (mosml) for my first programming course. Now the same university is teaching the same course in F#.
Of course a lot of the data science/machine learning is being done in Python, but that is likely due much of the frameworks/tooling around is Python in general in that world.
Honest question: Have you ever used a MacBook trackpad long term?
From my experience with Dell XPS/Precision, Lenovo Thinkpads, IBM Thinkpads, and finally MacBooks, the MacBooks are far ahead.
The Thinkpads trackpad are way too small, and Dell's are now days large enough but too imprecise. Both the Dell ones will sometimes trigger a click when typing on the keyboard since the trackpad is too sensitive.
I've tried them every time someone with a Macbook came over and told me I have to try the touchpad because it's the best thing since sliced bread. It's definitely a big touchpad, but that's about all I can say about it. It's definitely not worth the extra spend on Apple hardware and neither is it worth dealing with macOS. It's not a bad touchpad at all, it's just unremarkable in the higher end laptop space.
I'll agree that they used to be exceptionally good before the Windows 10 precision drivers became widespread, though. Those made a huge difference in the PC world, for Windows and Linux support, and it took the industry many years to get to that level.
Going by the current state of my touchpad, I use about 60% of the area of my current touchpad so honestly I'm fine with the size on my Thinkpad P1 gen3. The HP Probook I had before that (which, to be fair, is eight years old now) definitely had a touchpad that was too small.
Apple also seems to be the only company that produces a decent external touchpad, which is irritating. I feel like I'm more productive with a touchpad but finding an affordable touchpad with decent reviews is nearly impossible, except for Apple's magic trackpad. The best alternatives seem to be Chinese clones from Aliexpress but I don't feel like writing my own drivers to get those to work well with Linux.
Yeah, I posted a blog post [1] that explains my motivation in curating this list. Seeing the broad range of companies that do this kind of work was really helpful early in my career.
That's true. I could have added a "Neither is offensive" button, but my goal was just to show that you can't really tell the difference between what Twitter is doing and random chance and I thought that "Neither" would dilute that.
I think the quiz as it stands is a good way to demonstrate how bad twitter is. In particular I got a few sets of tweets that were identical and had to choose one as offensive at random.
I think a better measure of how accurate a filter is overall would be to show 1 tweet and response at a time and pick offensive or not offensive and then compare to the algorithms.
An earlier idea I had for this was to put two tweets side by side and ask the user to say which tweet was more offensive. Then, I figured I could use the ELO rating system to come up with an "Offensive score" for each tweet. e.g. "This tweet has an offensiveness of 2200" or something like that. I could then compare the average offensiveness of tweets that Twitter considered offensive versus not.
I wound up not going with that approach because many times you just have two completely innocuous tweets and picking which of the two of them is "more offensive" is just arbitrary. I could have curated the tweets so that only ones that were kind of offensive were in the quiz, but then I might be putting my thumb on the scales to get the answer I already believed in. I'd also need to get lots of ratings for each Tweet to have a stable score.
I think your idea is pretty interesting. It would allow a conclusion like "The average tweet Twitter marks as offensive is X% likely to offend a rater." I was coming at it more from a "Twitter's offensive identification is like random chance" perspective rather than just trying to assess quality. If I had considered this idea while creating the quiz I might have gone with it!
This is a cool article in the sense that it gives an idea of tuning that can be done on one extreme. While most applications won't need this level of tuning and some of them might be hurting if one isn't CPU bound, it is great to know which options exists.
Does anyone have further articles exploring the topic of os tuning for various types of applications? Maybe also for other OS, BSD/Win?
As a member of the Nordic societies I find it important to point out some important information. In these countries we already have rather sizable unemployment benefits.
If you read the (better) article by NYT[0] on the same subject, you will be given an example showing her income under basic income only increased with 50$ out of 635$.
that's my point, normal people value social interaction over an absolutist position of "well at least my data is secure!". normal people view never seeing their lil' cousin again as punishment, not the correct position to adopt bc it prevents being caught in a data breach
I'm not sure if it is still the case nowadays, but back when I had an iPhone I remember that Apple had a killswitch which allowed them to remove already installed apps on one's phone.
Nevertheless, I doubt that Apple is more inclined to give away their control of your device. I would guess that they could do the exact same as Google did.
Of course a lot of the data science/machine learning is being done in Python, but that is likely due much of the frameworks/tooling around is Python in general in that world.