skysight-inc/HackerNews huggingface dataset:
Not necessarily on a timescale that can benefit you. Population decline, crappy weather, pollution, water supply, politics, war, so many things can influence the value of land.

There's a reason no one is clamoring to buy land in Somalia.
That's so true and some people are paying a lot of money for that.
The user accepted his profile information but they also got his friends information.

That was expected and agreed to behavior by all parties (users, developers, and Facebook) at the time. I know it’s out of fashion in 2018 to acknowledge that TOS exist and that users should have read them before agreeing to them (or at least before complaining after the fact), but this is the reality.

The “abuse” part was that you were supposed to only access data that was necessary for the operation of your app. Accessing friends’ profile information to make an app that shows people who work at the same company as you, for example, was completely acceptable and a good use case. Collecting it for purposes unrelated to the stated purpose of the app was and is abuse. The Obama For America app also abused the platform in this way, but on a vastly larger scale - they pulled the entire US social graph (about 4x as many profiles as Kogan had) after less than 1 million people actually authorized the app and used it in all sorts of ways outside their app. This technique was widely celebrated in the press, right up until the “wrong” candidate won.
There are a hundred valid answers to this question. Here's one that I think is a major factor: What is the degree of separation between the engineer, and the people who benefit most from the engineer's work?

If you're a startup founder, you eat what you kill. There is no degree of separation at all.

If you're working at a 10-person startup, you report directly to the founder. 1 degree of separation.

At a 50 person startup, you probably report to someone who reports to the founder. 2 degrees of separation.

At a place like Microsoft, you're probably 7-8 degrees removed from the CEO, who himself reports to the board-of-directors, who report to a decentralized mob of shareholders.

At every degree of separation, there is an amplification of:

- distortion of incentives

- "Not my job"

- "that decision is above my paygrade"

- "What's in it for me?"

I don't think individual productivity can ever be as high in mega-corps, the way they are in startups and smaller teams. Hence why mega-corps are generally best at milking existing cash-cows, whereas startups are much better at actually driving innovations.
Unlikely. What's more likely is the regulator will send you a letter asking if you are in compliance or not, and then send you information about current best practice to bring you back into regulation.

If your breaches are deliberate and flagrant you may end up with a fine. But regulation in Europe really is light touch.
I also wonder if, in some ways, devops (I mean the "idea", not the engineers themselves) could be commoditizing IT people (not implying there's some conspiracy), blurring the distinction between devs and sysadmins in particular.
Roundtable: Is 2018 the Year of STO (Security Token Offerings)?
FYI, there seems to be some disparity on two different pages:

On https://stripe.com/atlas:
Delaware tax filing: preparation is free, Delaware fee starts at $225

On https://stripe.com/docs/atlas/tax-obligations:
All LLCs formed or registered in Delaware must pay an annual LLC tax, currently at a flat rate of $300.00.
Just because something isn't easily enforceable it doesn't become legal or ethical.

A small company absolutely can get by with shoebox accounting, too, it's just not particularly advisable to do so.

The same applies to completely ignoring GDPR, whether it's enforceable or not.
That was a lot of fun to read.

I am finally getting to the point in my programming abilities where I have the confidence to solve problems like this.

"throw something together" never is that easy, but its getting easier.
Alternatively, they should be acknowledging that they're becoming more of an ISP and less of a TV provider, consumers are less interested in traditional TV service, and that they need to adapt in some way.
It's mixed C/C++, and the codebase does not contain a lot of "heavy" features like templating and header-only implementations (I'm looking at you, boost).
OpenID and OpenID Connect are different and practically unrelated technologies. StackOverflow will still have social login.
I used to run Netflix just fine with a 10mbps line (roughly 8mbps effective), although that was "only" at HD I think.
Just to warn people who might have a different situation, sometimes cable companies say something along the lines of "$19.99 bundle!" And in the small print it says each, so it's actually $60 for phone, internet, and TV.
>> I also don't believe that data about me is data I own.

If I place a camera in my house so that it's recording what's going on in your bathroom- is that data you would like to be kept private, or not?
No problem :)
re transparent walls I'd say they might have been suitable in late 17th century or so...

But seriously. To begin, the whole construct of comparing theoretical discovery to "seeing new things" is very old.
Take Newton's famous "If I have seen further it is by standing on the shoulders of Giants." That actually is late 17th, although wikipedia says it could be even from the 12th, [1]. The windows probably have been used metaphorically even before that, but to be on the safe side, google ngrams finds them before 1900, [2]. Don't see much numbers about actual transparent walls, but a "glass ceiling" was used metaphorically as early as 1848, [3]. Thats remarkable on its own, although thats a different metaphor. Literal uses are even earlier.

Anyway, the point is cliche alert went off right at that first stanza.

There's a deeper problem, though. And that is that "proving" a theorem is not the thing that enables one to see. Proving is typically a rather mundane process, once one knows what one wants to prove. Take Pythagorean theorem even. Once one can formulate it, its not really hard to prove. But coming up with the notion that that is a thing that could be right, thats more difficult, thats the moment of "seeing". Its a bit of a simplification, but its mostly the discovery of new formulations that drives mathematics, not proofs. And so, the opening "I proved a theorem and then whooaaa..." is quite ridiculous.

[1] https://en.wikipedia.org/wiki/Standing_on_the_shoulders_of_g...

[2] https://books.google.com/ngrams/graph?content=window+on+the+...

[3] https://books.google.com/ngrams/graph?content=glass+ceiling&...
As another practitioner, I wholeheartedly agree - most of what is called AI today is ML, and thats basically pattern recognition via boundary relaxation solutions - it is necessary for "AI" but not sufficient - BUT - my problem with the authors position is that he keeps not noticing A stands for artificial - we've had other solutions in other techs, Mycin and Dendral come to mind - no, they weren't AI either, however I think when future work begins to incorporate more than the PDP groups seed stock, we may see AI's begin to appear - and then the arguments will start all over with 'too narrow to be intelligent' - first we'll have to figure out 'it looks like cognition' before we move on to anything remotely resembling actual cognition - at present, not only can we not do it, we have never ending arguments about its very definition.
This going to be more obtuse from what you would expect but i can give it a go

this is because efficiency isnt a goal , impact is. you might be efficient enough to iterate 10 times a month. but that is not what a customer wants. planning goes a long way compared to just doing something. as software Engineers we often mistaken efficiency as "getting shit done". which is great but there are too many instances when it is shit. the bigger the org and the user base / affected population, the things you do has an impact . i've known users to shift loyalty due to small mistakes that companies do. as a dev deeply connected to the impact of your product, you realize that decisions make a big difference. you plan ahead and mitigate probable failures. these require time.A good product can go a longer way than an efficient team with no direction. this does not imply that everything takes time. but repercussions of a bad decision can be lasting in a big organisation. you have a large number of stakeholders involved who would want to and can help you achieve your goal. this is however not always good. the greater amount of red tape involved can lead to competitors gaining an edge and also several cases of "i fucked up". the bottom line being. efficiency isnt merely moving fast. its about building things which matter and having an impact. if you look at efficiency in that manner, then big orgs aren't any less efficient than the smaller ones since their reach is much greater. perspective matters
www.geocities.com ;)
I once went to a hypno-therapist who did a germ-line regression (as contrasted with a "past-life" regression) where I was lead back in time through my familial linage to talk one of my ancestors. YMMV

> Epigenetics is the study of heritable changes in gene function that do not involve changes in the DNA sequence.

https://en.wikipedia.org/wiki/Epigenetics

> After all, when a new cell is made, the parent replication mechanism also builds the child's replication mechanism.

The whole organism splits in two so the daughter cells' entire mechanism is half of the parent cell's mechanism.

One of the thoughts that trips me out is that each Amoeba (for example) is billions of years old.
What I'm wonder is if Netflix has explored entering the ISP game. Google experimented with this a bit but has apparently bowed out, but I could see it maybe being a valid direction for someone like Netflix. ISPs are going to keep squeezing customers, and companies alike until something gives, because it's their one leverage point. They've all but lost the battle on cable television, especially as all the major sports leagues have begun their own streaming services. Netflix probably has the market cap to afford the upfront costs of rolling their own fiber, and I'd imagine they'd save millions just from not having to pay the cable companies fees for Fast Lanes.
Generally, because managing passwords (both for the end user and for the server) is difficult, and there's no reason to get into the identity management business if you don't absolutely need to.
I have worked at many companies ranging in size from small two person startups to massive megacorps (Hewlett Packard, Salesforce). One big difference I saw was that, in a small company, everyone succeeds or fails together. Everyone wins or everyone loses. This creates focus on shipping good product, not getting promoted over other people or competing for a bonus pool for the top 10% of the team. Larger companies have numerous structures and methodologies that decouple this and create many paths to "winning" that have nothing to do with shipping anything of value. You can completely fail to do anything and still get promoted. There is tremendous internal competition and politics, fighting over budgets, hiring, resources and power plays of all sorts. I personally got huge bonuses for literally doing nothing as managers and teams optimized around the internal political structure rather than any kind of product strategy.
That doesn't mean the ads aren't working.
It's very easy to notice who has crappy upload when you Facetime them, I imagine this applies to many families.
>>If I refuse tracking for ads, then a newspaper can’t refuse me access to their articles.

This arbitrarily limits the range of businesses that can exist. For the sake of people who value their privacy having nothing denied to them, it reduces the services available to everyone.
According to this example in their repo, it does indeed support mathjax: https://github.com/RelaxedJS/ReLaXed-examples/blob/master/ex...
Well, first I don't really consider myself part of the crypto community, although i do own a bit own a bit of one coin. Second, I wasn't addressing the website/project at all. I was addressing the comment that was advocating for the users to be "exploited for fun and profit", and that not doing so was a characteristic of a "loser".

If not exploiting your users is considered "holier than thou", then yeah I guess that's an accurate description of me.
With respect but it's you who says it isn't. You need to explain why it isn't.
That won't fix my experience, unless you can get everyone else to turn it off too
I quite enjoy using/assisting this -

https://github.com/Netflix/conductor
It really depends on the market. Comcast's prices and service can very significantly based on your zip code. That's why they require you to put in a house number before they'll even let you look at plans or prices. Also, if you put in an address without Comcast service in your neighborhood you'll get very different offerings than if you use your own address.
Thanks; will correct.
Large companies are distributed systems. You trade efficiency of individual units for scale provided by being able to bring more units of production than bear on the problem then it costs you in efficiency.

eg. If a large company is 10x more inefficient it simply hires 11x more people.

Startups are more like predators, you need highly skilled individuals capable of leading a pack and killing frequently. This skill is rare and hard to execute / scale. (Notice how when a pack/pride gets too large it splits) Large companies are more like a herd, most individuals can figure out how to eat grass and run away when a predator appears, since the predators pick off the weak individuals anyway, they are actually doing a service to the herd organization which lacks the predatory nature to kill the weaker members / deny them resources. Herds can grow almost infinitely limited only by grassland / water.
James we can all see you with your phone under the table
I come from a small german town too.

In times of the skateboard hype, we certainly played on the street, mostly because you could ride it down, hehe.
There is also the language barrier and geographical considerations (travel).

I am sure you (as a european in country A) could ask your local DPA to assist or forward a complaint to my DPA (country B).

The same goes for the financial regulation and lots of other stuff already...
Big companies tend to optimize for business continuity rather than pure efficiency.

It is a systems tradeoff.

You can hire 5 10X people, but if one of them leaves (10X invariably do), you would have a harder time replacing, on-boarding, ramping up, culture-indoc, etc. another 10X person, assuming you can find one. In the mean time, this could potentially mean anything from a chaotic breakage of process or severe team reorg.

Whereas if you hire 50 1X people, if 5 leave, the system will likely still run at reduced capacity while you backfill if you have good process (not all big companies do, but those that survive in competitive industries tend to).

Good process often wins over a concentration of pure talent over the long run.
> I imagine we'll probably develop some AI pidgin language that provides more formality that as long as we follow it AI voice interactions become less annoying (but you have to spend a bit of time before to formulate it).

There's been some tentative discussion of using Lojban as a basis for just that!

https://en.wikipedia.org/wiki/Lojban#Lojban_as_a_potential_m...

http://www.goertzel.org/new_research/Loglish.htm
> I personally think it's disingenuous because when people hear Watson they think Jeopardy and they think that somehow that technology is involved when they use any of the Watson.* products.

The use of the Watson name is a deliberate attempt to take advantage of the Jeopardy game. It's a name that has cachet, and I've seen just enough of the marketing perspective to know that marketing will push very hard to reuse a successful name.
ic™
Secrets Behind the New Facebook Algorithm:Revealed
I don't care about likes either. You don't get many likes on a stock photo site even if you are a pro anyway. I got into uploading simply to use them as a photo host, but later it became an outlet for the basic effort I put into being more creative with photography (learning LR). The logic many use is that it is better to upload photos than just have them collect dust. Besides, it is fun to be browsing the web and see pictures you have taken. The reach of Unsplash and other sites is really impressive. My pics are meh quality at best and yet they still have ~60M views. Real photographers have way more than that with one approaching 1B views.
Valhalla is an open-source routing engine, like for from traveling from point A to point B. I think Tesla uses it as the basis for their in-car navigation system. It produces routes very quickly and has a pretty robust costing model (cars can travel on different roads from bikes, bikes can travel different places than pedestrians, right turns are easier than left turns, sharp left turns are worse than slight left turns, etc). It can produce turn-by-turn instructions and gpx output. It also does map matching pretty well (converting messy GPS data to an actual snapped-to-streets path), traveling salesman solutions and a few other things.

(https://github.com/valhalla/valhalla)
I'd think there is a point where it inverts, too: There is some number N such that the amount of work you can get done with N people is more than you can get done with N+1 people, and it keeps going down with any subsequent person you add. The Mythical Man Month talked about this. At some point, the extra communication overhead spent to sustain person N+1 costs more than the marginal extra output of that person.
I think you'll have a hard time finding conclusive research like this for any languages.

Many papers exist but often have conflicting results, or weird methodologies, or extreme artificiality. It's really expensive/ hard to generate good research on this topic that controls for the big variables - you basically need a company that's willing to throw away at on of developer time to build two versions of the same product in both languages, then a metric for measuring success, a way to ensure you take dev skill into account, etc.

So instead it seems a lot more worthwhile to not bother looking for objective research as it won't be found.

I think a better approach is to just use what we have - sense and anecdotes.

From a sensibility standpoint, let's take a step back from rust.

Do we expect fewer memory safety vulnerabilities in Java vs C? Probably yes - Java is a memory safe language with few escape hatches.

So what about Rust vs C? It's a bit less clear as rust has a more oft used escape hatch, but I think we can reason that it's likely to have fewer memory safety bugs.

Would we expect fewer bugs in general? That's much harder to discuss with that approach.

You can look at testaments from Servo devs, and other companies using Rust ( https://www.rust-lang.org/en-US/whitepapers.html ) and their experiences.
No, it's bad because it drives down the potential market value for good products that could become available in the market because the market expects that all AI is inferior to expectations.
Normally my comments are very sceptic, but this article is just spot on.

The problem is not only context or subtext, it is even worse from an entirely predictable standpoint:

Consider a large corpus of text (books, articles, ...).

1) Concepts that are WELL UNDERSTOOD BY HUMANS will not be explained by humans when they reference them: the word or concept "pet" (as a verb) will show up in many sentences refering to the petting of cats, dogs, horses,... and ML will correctly predict the conjunction of "pet" with any of these words in the sentence. It will even be able to train ML to confabulate realistic sentences in the sense of echolalia. Consider then the sentence:

"The lady pets the cat"

The computer will recognize that the presence of cat is not surprising (bingo!). The computer will have no idea that this probably involves one or more cycles of the lady's hand gently pressing down on the fur belonging to the cat, then while still preessing down, moving the hand in the 'natural direction of the hairs' (NOT the other way around) probably from closer to the head towards the tail, and probably lifting the hand before repeating the cycle so as to massage the cat or perhaps so as to remind the cat of its time as a kitten being licked by the mother cat.

No book or conversation in the corpus will give this detailed description exactly because humans expect each other to understand this.

2) Concepts that are POORLY UNDERSTOOD BY HUMANS will be vigorously (but often erroneously) explained by humans communicating to each other what they think is going on: endless texts about religion, sexuality, perpetuum mobiles, economy, ...

How do we even expect the computer to produce a sane result, even if it correctly guesses the context?

That said, I do believe relatively helpful natural language processors to be possible, but they will have to be vigorously trained by multiple human curators individually analyzing a sentence and trying to find (probably true) statements about what a sentence implies:

Starting again with:

"The lady pets the cat"

One curator might mention hands touching fur while moving.

Another curator might add that one can also conclude the hand probably presses down on the fur.

Yet another notes the sentence also implies the lady is still alive, for else she would not be able to pet.

The first curator now adds that the cat as well is probably alive, for else the lady would probably not want to pet the cat, since massaging is useless to a dead cat.

The third curator now mentions that the sentence implies one or more cycles of an individual pet stroke.

Etc...

As you can see this quickly becomes an expensive operation.

Now one might train an adversarial neural network to look at a sentence (or sentence with context) and a list of probable conclusions, to predict if the list of valid conclusions is complete or incomplete. And then only send the incomplete ones to humans?
It's general reporting by general reporters using general language for the general public. It's not a tech publication.

Joe Lunchbucket doesn't care if it's hardware that failed or software. The system failed. That's what his tax dollars pay for.
> All Model 3's DO have the HARDWARE to support full-self driving, even if the software is not there.

Please provide evidence.

Given that the only full-self driving system out there is Waymo's, which uses completely different hardware than Tesla's, it is impossible to back your claim, unless you develop a fully-self-driving system on top of Tesla's hardware.

So until that is done, your claim is false, no matter how many caps you use.
If you don’t require deterministic hashes (and deterministic hashes are bad for anonymization anyway) just hash data+randomBytes(16) (obviously, don't save randomBytes(16) anywhere). There you are, nobody can bruteforce your hashes.

Even better, just replace your data with H(randomBytes(16)). Or a random UUID.
It depends on how serious this question is.

If you're dead serious, I'll allocate a certain % of the current revenue to buy puts/calls on a public company, and hope I'm right.

Why? Because if I knew a way to 10X the profit, I'd already done so.