bagrow

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.

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)

Technically, you should plot this with `plt.step`.

> 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.