I recently ended up in an interesting conversation with a university faculty member where we found that many of the most endowed universities could essentially make undergraduate education free and make back the difference (and often more) on straight interest accumulated from leaving their money in a bank.
Given that they are probably making more than the current interest rates by investing, I wonder why students still pay so much for tuition at these universities in particular.
>>You can save time by learning from the mistakes of others.
>Only barely. For important life decisions/paths, people only learn from their own mistakes (and often not even from those).
>Heck, Computer Science as a field itself forgets its own collected wisdom every new generation hits the market, and re-invents BS that other eras have tried and buried with another fad name.
Your last statement sounds like it's in favor of "learning from the mistakes of others" in that we could avoid re-inventing failed "BS" if we learned from others' mistakes. Are you saying that the idea that folks in CS re-invent work which has previously failed is evidence that it is not possible to learn from the mistakes of others?
There is also a fantastic video where Cliff Stoll describes the Friden EC-132 calculator and shows off its acoustic delay line here: https://youtu.be/2BIx2x-Q2fE
I remember being in high school when Google Plus came out and thinking it would be incredibly popular. I totally missed the mark, and it's funny because while I thought it would take off with other people, I never really used it myself.
I had a really hard time getting into Vim until I found out everyone I knew who was using it had mapped something else to escape. Once I did the same, it was much easier to get started.
I'm assuming by iterate you mean "generate outputs of a GAN which preserve some order that you can iterate through."
The answer is yes, but not in the way that one might think. Despite the fact that we seed the GAN with input noise, there is no guarantee that the GAN makes use of this at all. This is a theme with GANs: we often want to imbue them with prior knowledge that we think is important, but is easily ignored by the GAN. In this case, we want to generate samples from p(x|z), where x is in the space of our data (often images, in this case passwords), but provided it gets good results according the the loss function, your GAN may learn p(x|z)=p(x). This is fine if you don't care about enforcing some relationship between input and generated samples, but here we do.
One solution is to use InfoGAN (https://arxiv.org/abs/1606.03657), which adds a term to the loss function that the mutual information between a latent code and the generator output must be high. Your latent code might be drawn from a uniform distribution on [-1,1], and the generator output will be conditioned on this code. This being continuous, it's questionable what "iterate" might mean. On a computer, maybe you iterate through every possible float (as someone mentioned), but if you want to generate N different samples, you could also discretize this distribution to N values on the given interval, each with probability 1/N and sample from this PMF.
I haven't seen it posted yet here, but for anyone unfamiliar with mathematics in juggling (or anyone with an hour to kill watching something entertaining), there is a lecture/performance by Allen Knutson (https://www.youtube.com/watch?v=38rf9FLhl-8) that I found to be a great intro (before I even knew I was looking for one!) and got me excited about the subject.
All I could find on these archives were summaries of the letters, is there anywhere where we can view the actual documents that are archived (either scanned or OCR)? I admit, I had a hard time navigating that page, so I may have missed something obvious.
Edit: My bad, after reading the Conditions Governing Use I found this: "Photocopies and photographic copies of material in the archive can be supplied for private study purposes only, depending on the condition of the documents." So it looks like these written summaries are all we can get?
Yeah, I think so! That's exactly why I mentioned the accident rate reduction cited in the Wikipedia article shared above.
I'd love to see official work that explores that angle (rather than a claim from an interview, which is what the Wikipedia article refers to), I just haven't seen any document/study about it yet.
It's great seeing that more and more data is being collected about this all the time. I'm a huge proponent of this tech.
What I wonder when I see these statistics, though, is whether all miles are really equal? For example, are Tesla drivers more comfortable using Autopilot in "easy" driving situations? Is there really a one-to-one correspondence in the distribution of the kinds of miles driven with Autopilot on vs. normal cars?
Furthermore, the metric commonly cited is "fatalities ever N miles." Are there fewer fatalities because Autopilot is great, or because Teslas are safer in general? Has there been a comparison between fatalities with/without Autopilot strictly on Teslas? Even then, it seems to me we are subject to this potentially biased notion of "miles" I mentioned previously. The Wikipedia article you mentioned cites a 50% reduction in accidents with Autopilot, but the citation is to an Elon Musk interview. I haven't yet seen anything official to back this up, but if anyone has any information on this, I'd love to see it!
The phenomenon that is being described where melting ice causes the release of CO2 into the atmosphere seems to have been known to climate scientists, though I don't know whether it has been included in climate change models.
There is a great talk (video online here: https://www.facebook.com/WoodsHoleOcean/videos/1015459031268...) by Richard Alley where exactly this phenomenon is mentioned (see Q&A at ~50:55 in the video, though I highly recommend watching the whole thing).
I had no intention of criticizing any efforts. One should do whatever makes them happy, and as a frequent user of these libraries, it is to my own advantage for them to improve.
For the same reasons, I have nothing against people who "do anything that resembles anything that has been done before," and I certainly wouldn't attempt to discourage the author. I'm sorry if that cartoon is over-referenced (in attempts to be negative), I can't really control that, but I think it's something to think about when starting a new project (i.e. what is your goal, does it differ from other projects, is that important to you?)
Sorry if my comment seemed like I was shooting this down, I certainly had no intent of doing that.
I have tried the service, and my interactions with it have confirmed all perceived sketchiness:
In a moment of desperation, I signed up for this a while back. I found it not to be useful and tried to remove my account with the site, which turns out to be essentially impossible.
I ended up revoking access to my email account and continued to receive emails from unroll.me that the service "has lost its connection to your account," which I found hilarious, because in my desperate attempt to get rid of spam, I created more.
I've tried to unsubscribe from these unroll.me emails several times before, and the unsubscribe link takes me to a page containing all the subscriptions that the service once found on my account (the one you'd see if you were trying to use the service---so all that data is still there, for sure, and it has been many months), and I have never actually been unsubscribed.