compare's comments

You really need to stop the personal attacks and trying to raise a downvote brigade against my comments, just because we disagreed about a law and culture topic.

I wish the site admins would place a clear written policy against these and other personal attacks next to every comment box.

It got great traction and decent press coverage, in fact I was a bit surprised when journalists decided to go with a nudity angle. In the end I never pursued it further, due to another startup I was working on at the time.

Seems a bit comical that the article claims this to be the first disappearing photo app. I created and launched one myself a year before Snapchat started...

The normal way for start founders to receive equity, is only from one or more of these 3 things:

- For hours worked, based on the vesting and usually the hours must be beyond the cliff or you get nothing.

- If you built a crucial part of the IP that the company needs to buy from you with equity.

- Cash invested up front - less common.

He fulfilled none of those. Not even close to being a cofounder. Ideas aren't included among those.

The effectiveness of the relationship between investors and startups in SV is built on upon being upstanding and not being overly manipulative. Founder/Investor agreements that are born from the manipulation of unexperienced founders always should be EXPECTED to turn out badly.

There's a child-like expectation that once the deal is signed or agreement is made that it's over. It never is, that's just the beginning. If you're expecting that everything is finalized as soon as an agreement is made, regardless of the conditions, then you're simply bad at business and taking risks that you haven't yet realized.

(Of course this isn't true in Europe. They love taking contracts extremely literally, and their economies suffer enormously for it.)

So many accelerators behave wildly unprofessionally and inappropriately for the space that they're in.

Perhaps all that's needed is more high-visibility guidelines like what YC is doing now. Perhaps we need better platform for evaluating investors from the founders perspective, instead of networks that really only care about evaluating startups.

Either way, the situation seems to be getting worse, with the continued explosion of accelerator programs around the world. I hope we find an effective solution.

No, that's insane. Investors commonly invest in multiple competitors at once. Not to mention that this is a huge security vulnerability to have this stuff floating around the investor's office and on their personal computers.

Sad that some investors are so manipulative.

I've been looking everywhere for the inverse of these graphs = states that former-residents of each state moved to.

I used to live in a state that many went to college in, but none of those stayed after graduation.

Correct. The solution is usually that they'll just create special functions for doing numeric comparisons, that accept an adjustable epsilon margin of error, to use instead of the built-in numeric comparison functions.

There're a lot of silly myths about investment software on hacker news / reddit. Truth is that the code is usually much more hastily written, but with more tests or redundant systems implemented to cross validate results.

The idea that precise decimal types will be used throughout the systems is a bit silly. All the data typically will be going though off the shelf machine learning models, all of which just used plain floating types.

If you do end up finding a way to make a break up with non-technical founders go smoothly, without them running your name through the mud or threatening to blackmail you, then please do let us know. Not sure it's possible.

Was really hard to figure out what in that article has anything to do with "design". If anyone is as confused as I was, it seems that "design thinking" is something totally different:

http://en.wikipedia.org/wiki/Design_thinking

and I'm not too sure what that phrase really means either.

Thanks for this. Design trends really are detached from any sensible reality. They're turning good designs into bad designs whenever a site tries to modernize themselves to match these trends.

Here's my rule for web app design: 90% of the page, by area, should be somehow derived from the app's dynamic content, versus static filler content from the designer, no matter how pretty the filler is.

Second rule: Designers, stop calling your OWN apps sexy or beautiful. Would you walk up to someone that you just met, and tell them that you're beautiful while they're looking directly at you? What the f## are you designers thinking?

Great concept. One feature request: Better calculations for cities with Bi-modal price distributions.

Certain cities have a extremely bi-modal distributions of pricing. I.e. they can support both the "broke artist" lifestyle, and the "upper middle class" lifestyle. Two separate cost distributions. If you try to take the mean or median of these cities, you'll end up either arbitrarily landing on one of the distributions, or a nonsense number in the middle.

A good example is Manhattan. For example, pizza can actually be cheaper in Manhattan than Sofia. In Manhattan, the broke artist lifestyle of living with multiple roommates who barely know each other, all sharing a rent controlled apartment for a few hundred dollars a month is more socially acceptable and much more common. Just taking prices from the realtor-controlled apartment websites is a poor reflection of reality. Almost no one except the richer consultants bothers with a full-time coworking desk in either city. In this case, Manhattan can actually cost less than Sofia.

So, I think the "broke artist" price distributions would better reflect what a remote working nomad would be looking for, instead of the "upper middle class" prices.

This is a serious problem that requesters face. Often the workers who spam everyone with fake work will report anyone who rejects their work as retribution.

Is there actually any dataset of upon which the accuracy of this detector is measured and improved? Or is it just some hard-coded rules?

For example, does it really differentiate between people who ask for votes, and people who just vote up the content of someone they recognize?

I'm working on a search product now. I find it really fascinating that many people immediately know and have adopted this "specific-type general-type" query structure, whereas many others have no idea.

It feels like we're on the verge of slowly evolving a new human-computer communication language. Definitely within the next 20 years it will happen. Not just a list of instructions or model descriptions like programming languages are, for example you can't translate an arbitrary Engish sentence into a programming language. No, I think this time we're watching a full language, in the linguistic sense, evolve in front of us.

Of course, search engines will also have to evolve beyond the "do-know-go" communication types that they're married to now, to get to the next stage.

I'm about to deploy a new autocomplete on my site, probably with 10s to 100s of millions of records, at least 100 users at once. Would the new Redis commands help here? How would the memory usage be? Is it better to just use something else like Cleo for autocomplete?

Like the basic idea. I'm often finding myself hacking together basic alerts on feeds, similar to this.

And that, to me, is the strangest thing about Bitcoin:

https://blockchain.info/charts/hash-rate

The miners, never, stop. Completely disconnected from the market pricing.

Cool tool for developers, but since this one is open source, I think it opens up even more interesting possibilities for these tools to be integrated into part of a consumer app. Curation is the next big trend, right? I think I'll give that a try.

So many original content posts have been nailed by the voting ring detector. I can almost guarantee that many of those "friends asking friends for votes" usually have no connection to the original author at all. Maybe it's just friends sharing things with each other... I really wonder how accurate training / testing data could be gathered for this classification task. Maybe it needs to be refreshed.

Anyway thanks for bringing original content back to HN. Anyone know if there's a demo page for this library?