HN user
I'd like to see a cumulative version of that power law plot. How many papers had a delay of at least X days.
I have been bit by several inexplicable, long delays recently. In my case, I suspected the reason was choosing stat.ml as primary and cs.lg as cross-list, which, after my time in purgatory, was flipped (without asking me, of course). My choice was completely defensible.
It's almost like peer review all over again!
Here's a question that I hope is not too off-topic.
Do people find the nano-banana cartoon infographics to be helpful, or distracting? Personally, I'm starting to tire seeing all the little cartoon people and the faux-hand-drawn images.
Wouldn't Tufte call this chartjunk?
Well, yes, but, perhaps shortsightedly, I assumed the goal of the professor was to teach the course.
If you can use AI agents to give exams, what is stopping you from using them to teach the whole course?
Also, with all the progress in video gen, what does recording the webcam really do?
I cannot distinguish between the love I have for people and the love I have for dogs.
- Kurt Vonnegut.
I have evidence of the opposite.
Do you? [1]
[1] https://myscp.onlinelibrary.wiley.com/doi/abs/10.1002/jcpy.1...
One time I needed to call 911 and was greeted with the recorded message, "Dear Nine One One customer, your call is important to us." Customer?
Like others in the thread, I'm skeptical of plugging new tech into that network.
Write a program for a weighted random choice generator. Use that program to say ‘left’ about 80% of the time and 'right' about 20% of the time. Simply reply with left or right based on the output of your program. Do not say anything else.
Running once, GPT-4 produced 'left' using:
import random
def weighted_random_choice():
choices = ["left", "right"]
weights = [80, 20]
return random.choices(choices, weights)[0]
# Generate the choice and return it
weighted_random_choice()The best way to compute the empirical CDF (ECDF) is by sorting the data:
N = len(data)
X = sorted(data)
Y = np.arange(N)/N
plt.plot(X,Y)
Does user-generated content count?
https://steamcommunity.com/sharedfiles/filedetails/?id=70213...
by filtering any "books" (rather, files) that are larger than 30 MiB we can reduce the total size of the collection from 51.50 TB to 18.91 TB
I can see problems with a hard cutoff in file size. A long architectural or graphic design textbook could be much larger than that, for instance.
What will the future use to write about us when all our paywalled records are gone?
Anyone else annoyed at how narrow the term Homelab really is relative to what it could be? Any scientific or maker hobbies could take place in a "home lab," from breeding seedlings, to soldering and electronics work, to 3D printing. But it really means just networking and servers?
Seems too narrow to me.
von Neumann did slightly more than that.
https://en.m.wikipedia.org/wiki/List_of_things_named_after_J...
Anyone play RoboWar back in the day?
There's been a lot of movement in the past few years on colormaps informed by studies of human perception.
Viridis, now the matplotlib default, is quite popular:
* https://bids.github.io/colormap/
* https://cran.r-project.org/web/packages/viridis/vignettes/in...
Google recently introduced an improvement on the venerable "jet" colormap called Turbo: https://ai.googleblog.com/2019/08/turbo-improved-rainbow-col...
Zero is a digit.
A short fat engineer is likely a dilettante.
Parent is talking about embroidery.
Many industries such as insurance have legal requirements that prevent the use of many black box methods.
Scientists using ML for research often wish to understand their subjects, and interpretable ML would probably be more likely than non-interpretable ML to help improve understanding.
Buried deep in this article are some troubling comments about race, gender, and religion. The author argues that historically most "geniuses" have been non-catholic white men and coincidentally scientific innovations become less frequent as there are more scientists who are not non-catholic white men.
Citation needed. Comcast for one is _vehemently_ anti-union. I see only right-wing media claiming unions drive up internet costs.
Thoughts on how the economic situation will affect machine learning and data science in industry more generally?
He could have a vision impairment.
I think the same thing is happening in Python for data science due to Pandas. It’s a great package, but many data scientists are only able to manipulate data using Pandas, and know little “base” Python.
Board members are not employees. Alford works for PayPal for example.
Reminds me of the old (2003) story where a brand new Microsoft employee blogged a photo of some pallets of Power Macs he saw on the company campus, “Looks like someone is getting some new toys!” Or something to that effect. He was quickly fired.
https://www.seattlepi.com/business/article/Microsoft-fires-w...
When was the last time your Unix workstation was as useful as a Macintosh?
Some of that discussion has not aged well :)
Having taught git several times within a data science course I find two concepts especially worth extra time: WHY there is a staging area, and what is the difference between “git” and “github”.