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How is this different than just using s3?


With CloudBuddy, it costs $1 per 10GB per month and setup takes less than 1 minute.

s3 is both more expensive and much more involved to setup. With s3, it takes longer than 1 minute just to be able to figure out the pricing! LOL

Here is a link to s3 if your curious https://aws.amazon.com/marketplace/pp/B0764CYKPB (I found this by googling SFTP Gateway to Amazon S3)


these metrics are always pure garbage. Someone comes up with an equation like:

(start salary) + (median salary) + .5 * (job availablilty) + .75 * (growth) ... etc

then they rank everything, tweek it, make an article.

The scary part is people will read this and parrot this information for potentially years, "did you know actuary is the best job???"

This is actually how misinformation spreads.


Bingo. They've been saying this about actuarial science for a very long time. But they fail to mention that (1) there aren't that many positions available, (2) for students smart enough to qualify for the positions (passing the CAS etc) you are far better off going into finance or economics as an undergraduate, and (3) most importantly, actuarial science sets you up for a very specialized and narrow career path.


FWIW, I think there is a risk-reward trade off involved for many of us that end up going the actuarial route. I was broke coming out of college, without much of a network or pedigree to fall back on and the prospect of a solidly middle-to-upper class income drew me in. No regrets (other than no multimillion dollar startup exit), but I wouldn’t recommend it for most people.


I'm fine with metrics, as long as when people say "best", they'll quote an interpretable formula -- you have to start somewhere. The issue with this metric, however, is that there seems to be no given weight towards the population size. What is the point of a metric if it isn't generalizable?

I have the same grip with college rankings. When you look at the top 20, and then at the total student population, you'd realize these rankings are useless for the majority of Americans since only a small fraction will attend these schools.


Don't forget their inevitable spreadsheet errors.


Gotta be a startup opportunity somewhere here


Nothing is ever as it seems with people. Public perception and our methods of assigning legitimacy to public figures is deeply flawed. How any public individuals are we incorrectly demonizing? How many bad ones do we think are good? Surely more than we are currently aware of.


To make it personal, consider that the general practitioner that you see has likely been bribed by the pharmaceutical industry throughout their career. Starting in med school, with free food and toys. But if pressed, they'd all say that gifts don't affect their professional judgment. But in fact, studies have shown that they do. For example:[0]

> For years, the evidence has suggested that even small gifts can influence physicians’ behavior, create a mindset of entitlement, and help to promote allegiance to companies and their products. Recently, with the availability of Open Payments data and research made possible by these data, the evidence has become stronger. Using Open Payments data, a 2016 study found that receipt of industry-sponsored meals, even just a single meal, was associated with an increase in the rate of prescribing the brand-name drug that was being promoted.

0) Steinbrook (2017) Physicians, Industry Payments for Food and Beverages, and Drug Prescribing. https://sci-hub.tw/10.1001/jama.2017.2477


Curious that there's a lot of downvoting of reasonable comments in this thread.


Are you guys aware that major corporations i.e. T-Mobile and Sprint are selling app usage data to hedge funds? Forget the popular apps recording this, major telecommunications companies are selling it.


I've noticed this as well, the algorithm hones in on a few topics and videos. Interestingly enough, so does the algorithm on the Quora app. I hate this behavior, I want to use a recommendation algorithm to discover new similar content. My guess is that a "new similar content" algorithm doesn't get the same levels of engagement. Maybe its the same as radio stations playing the same twenty songs on a loop.

Clearly google knows what their doing, its just disheartening that this algorithm is the best for engagement. Also makes me wonder about human habit and reinforcement...


Here’s a Quora response to the question of why radio stations play the same songs over and over and over and over and over and over and over and over and ... again:

https://www.quora.com/Why-do-radio-stations-play-the-same-ha...


Sorry the developer wasnt thinking of you


Thinking about your users is kind of your job as a developer / entrepreneur...


You might not be there target user. You can't please every user and some sites want to add features that look great / add value when viewed on a larger monitors.

Mobile first sites make the desktop experience bland and simplier than they need to be.

It is still the best solution to the variable screensizes reality but it does make the web a little blander then need be.


You don't have to choose one or the other, you can have a simpler (but usable) interface for mobile and a more feature-ful version for desktop. This isn't rocket surgery.


You are referring to functionality my comment was more related to look / feel.

If you go with a popular framework with the mobile first approach you must design with those limitations on your full desktop site as well. If you go with Bootstrap and use the grid layout both layouts will use grid.


I know this might be shocking but you can make a website without a framework. In fact, it probably would have worked out better for this site as it has such a simple design. HTML plus a handful of custom CSS rules would have sufficed and it wouldn't lock you into any "limitations". This is not a hard problem, not even close.


…and all the other people who use phones?


NLP bots to influence political issues on the internet


Not being able to get 100% of the small edge cases the first time on complex algorithms problems.

--every large tech company


Maybe that's how it works at Amazon and Apple, but that wasn't my experience when I interviewed at Microsoft (twice!), Google, or Facebook. They weren't especially complex algorithm problems, either (how complex can it really get, when you're doing it on a whiteboard?). You just have to be able to think your way through a problem and explain what you're doing as you go; you should know what assumptions you're making about the limits of the problem, what you might do differently with different assumptions, and what kind of performance characteristics you should expect with those tradeoffs. There were definitely some complex design problems, especially during the Google interview, but I have really never experienced anything like the supposed "gotcha" coding interviews people stress out about so much.


This.

You can be a gold standard human who invented a distributed database. But at a large company, you're not going to be hired if you can't solve some string subsequence problem.


a million times this.


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