They need to get rid of the concept of weed out courses. It's bad for learning. If you are paying 30-50K a year for an education, course availability should be a given. Don't use the bell curve as an excuse to deny students an education, or if you are going to use a threshold, use a fixed one, not one that limits by percentage of students. The fat cat admins and professors need to be fired. Too many schools take the students' money and plow it into research and other areas, with zero regard for undergraduate education. "You are in university now, it's sink or swim. Can't make it? Too bad." This attitude is especially prevalent in the state/public unis, especially places like Berkeley where demands exceeds supply. Your traditional private colleges like Dartmouth and Harvard don't have this problem.
Ideally people who can't handle the course should get filtered out before being accepted to the college, so they don't waste any money. But since it's impossible to filter reliable at that stage, surely it makes sense to also filter early on in the course. (from the perspective of the student. If the college wants to take more of their money they could still direct them to a different, easier/more suitable subject).
A lot of schools these days weed out at the application level: if you have a great portfolio from middle school through high school, great! You have it made.
I sort of like the change to redeem yourself during the first two years of your university if you didn't have the ideal secondary school experience to get into a hot department of a hot university. CC can do that as well, I guess, but it is a much harder hill to climb.
There are a vast number of critiques regarding the model those ecosystems have used; it would be unwise to stick the label 'progress' on them until some of those core problems are resolved.
With regards to dependency versioning? I wasn't aware of that. I've been very happy with Cargo's handling of versioning so far, but maybe I've been lucky and haven't hit the pain spots.
That's rich considering Python is routinely criticized here for lack of proper dependency management until recently. Just because Racket is a cute Lisp/academic language does not mean it should be held to lower standards especially considering their recent efforts in relicensing and marketing to be regarded as a "serious" production language.
Rent the runway is a billion dollar company. A bigger issue is the danger of deplatforming and corporate terms of services when it comes to fundamental transport infrastructure.
You could spin any bullshit story around any device. If you do not have some degree of discipline with your meatspace domain, there's no hope for the hardware domain either. Even the most secure devices on earth can eventually be compromised if you allow all policy to fall away and just let the hardware fend for itself.
The police can and should be held to a higher standard regarding evidence and chain of custody. The tools are only half of this picture. It is a synergistic approach.
Wow, i’ve read all her 3 long blog posts about what happened and it angers me so much. I knew Vice was shit, but I had higher expectations from NY Times, Google or Twitter.
Correct, in fact Wu had posted the article in order to somehow protest NYT's hiring of Jeong. I personally think that Jeong was simply misguided in this particular incident and doesn't deserve that much criticism especially compared to the Vice reporter in question, though.
Why is it relevant? Do you know what they use for forecasts? I work in industry and have built weather applications for 5+ years now. Let me tell you, everyone uses the same source data. Machine learning is not going to help predict weather. If it was that simple, someone would have machine learned the weather already and they would be making zillions of dollars with their accurate AI weather predictions. Do you post climacell just because they say AI and weather?
OP i hate to break it to you. but a weather station wont tell you the right clothes to wear for the day. IT will tell you if it's raining outside currently. Consider this, station says it's raining and cold. You wear lots of clothes, umbrella etc. The rain storm is out of area by 9am and rest of day is hot and sunny.
One thing ClimaCell seems to advertise is that they have access to, "Millions of data points from proprietary sources such as IoT, Drones, Airplanes, Cellular Signals, Sat Com Signals, Cameras, and more, combined with traditional data sources."[1] Another of their pages[2] claims they use signal strength on wireless networks as one of their sensor methods, which is where I assume the "cell" might come from in their name. [3] says, "Instead of relying exclusively on NOAA radar data, as other forecasting services do, ClimaCell also gathers information from closer-to-the-ground sources: cell towers, street cameras, connected vehicles, and internet of things devices such as smart garbage cans situated throughout a city."
I'm not familiar with the industry. Are other providers doing this?
(I assume that the question of whether these sensors are at all useful is another matter entirely.)
Hi. first i'm asking you a question about why you posted climacell, not sure you answered it? Feel free to answer it or not.
To answer your question, if you want to obtain raw sensor data our government (and some volunteers) maintains a network of thousands of weather stations. Many are automated, many are people doing manual obs. If you know how to write code you can programmatically obtain these data.
However you might be confused... climacell does forecasts and you asked about finding station data? They are completely different things. I have no insight into what climacell does but i am a knowledge person in industry. I can tell you that nobody has some groudnbreaking 'AI' machine learning algorithm that is amazingly great at forecasting weather. If such a thing did exist, that person would have zillions of dollars because they can accurately predict weather better then anyone else.
I thought when they said they use existing wireless communication technology, they meant something like Microsoft's distributed signal processing arrays:
Perhaps using 4G and GSM signal quality as an ad-hoc doppler or metric for precipitation. Is their landing page inaccurate? Are they no different from other companies (besides the good at sales and marketing bit)? They seem to have a lot of big names on their customer list.
