skysight-inc/HackerNews huggingface dataset:
> In 2018, you can quickly tap Zomato and use its tremendous compendium of information to browse through what the top 500 restaurants are, filter it down to 20 by how much time you’re willing to travel, the money you’re willing to spend, and what other people like you say about a place ...

> In 1990, you wouldn’t have heard about it unless you stumbled by during a drive, or someone went out of his or her way to tell you

On the other hand, in 1990, people actually frequently hung out physically with other people who were like them. If the restaurant was good, they would eventually hear about it from one of those people--but not by anyone going out of their way to mention it, but rather simply in the casual conversations people had with friends back then.

I think it is the shift many have made to interacting more online and less in person that makes things like Zomato almost necessary.

I personally realized how much of my socializing is online when my car dealer called to urge me to get an airbag recall handled. I got the driver side airbag recall dealt with promptly when it was announced, but this one is just for the passenger airbag. I told them I was waiting until the next scheduled maintenance, because it has been 10 years since I've had a passenger in my car, so it is not really urgent.
Both passwords are just as practically secure against online attacks with the former being less secure against modern password cracking attacks.

A passphrase without any substitutions has words as atomics while languages have a very large number of words commonly used words offer a much more limited search space.

So say a 4 word passphrase of 4-8 letter words in the English language when limited to the top 5000 common words isn’t secure against offline attacks by any stretch of the imagination nor does it actually provide its level of entropy because you are no longer using individual characters as your atoms.

The latter password is essentially much more secure as it’s atoms are individual characters.

The former has an advantage which makes it easier to remember and faster to type.

So yes XKCD doesn’t get it always right.
Developing a data informed product culture
No, those things are in a different section of your Facebook profile.
To be fair, the early-adopter audience for this SDK product is definitely one who already knows what Magic Leap is, and what this would be for.

I would assume once the project is generally available, more time/effort will be spent marketing the creator tools to a wider developer audience.
You are right. But sometimes the data access technology does make a qualitative difference. That’s because a lot of our protection has always been a sort of “security by obscurity”. It wasn’t just the 4th amendment protecting you from unreasonable searches. The government was also restricted by their manpower, and by the fact that searching a house is easily visible and people would notice if you’re targeting everyone.

These restrictions don’t apply to digital eavesdropping, which is why it has become a major point of debate once the technology made it possible to do on a large scale.

Another example are license plate scanners: that data has always been there, and anyone could legally write down all the license plates they saw. But add image recognition and a database, and you’ve created a monster.

The tech community usually turns to technology to fight such technology: encryption for communication, Bitcoin to undermine (pun intended) what they see as the failings of the FED. BitTorrent for their qualms with copyright enforcement.

But laws and the court of public opinion are arguably our first line of defense. Underground printers didn’t stop the nazis or the Sowjets, and it’s not clear that technology has significantly moved power to the people in China, Turkey, or North Korea.

So we need better privacy laws. We need politicians to be scared before they use the services of Cambridge Analytica. And we need to convince our peers that they will have joined the dark side if they accept a job at Palantr. These sort of actions have the added benefit of respecting the processes of a civil society ruled by law, and not a techno-jungle where might is right.
Given that I am not an Oracle for large opensource Go projects, the answer is I don't know.

However it plays a role which programming languages I will advise our customers to use.

Currently I only advise the use of Go for those customers that need to work with Docker or K8s.
In addition: You need reasonably trustworthy entities if you want them to self-regulate and self-certify.

Facebook, with their behavior over the years, have lost any benefit of a doubt.

This may not be a popular opinion here, but given their behavior, their evasions and their lies it's time for the law to crack down on them; hard!
>I don't want to see them look like a villain. They are excited engineers.

I suspect the idea that these two categories are mutually exclusive is at the root of most of the questionable applications of technology today.
Add another class to make your element more specific. You can have many classes in one element! Then you never have to use !important again.

.rabbit.drivingACar.onIce.withRocketBoosters {
color: pink; /* pretty specific */
}
The Amiga version of STOS, AMOS, was nice and quite popular. Wasn't as fast as Blitz Basic II though.

There were some interesting "multimedia authoring systems" on the Amiga which might warrant inclusion, such as Amiga Vision (https://www.youtube.com/watch?v=u7KIZQzYSls) and Scala (https://www.youtube.com/watch?v=k20Wvlqb96g)
I haven't dealt with Java in the last ... 12 years (and only very little back then), but I liked the convention of naming Interfaces after adjectives. In Java, it would be named Sortable, and element types of a sortable collection would implement Comparable<T>.
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I understand that it's a bit impolite not to tip, but surely it's much more impolite to hold a grudge against someone for not tipping.

If you want more money, put your prices up.
The incremental approach can work for large projects if the teams aren't afraid of large scale refactorings a couple of times a year.
To be fair, Google Docs' core offering is live collaborative editing, not 'being a CDN'. Sure, there are ways they can support each at different times if they really wanted to, but it seems perfectly reasonable for them to say that when it gets to an N that they'd have to put significant engineering effort into supporting, that that's not what it was designed for, and that if someone wants CDN behaviour do that they can always export the document and put it on an actual CDN
Hi Robert! I thought (perhaps incorrectly) that Lively was largely the same programming experience as Squeak, just in the browser. Do you have any screenshots showing new programming experiences in lively.next or cloxp?
Even if they have the chops they still have a long way to go, based on what I see online about them.

I've used AWS quite a bit, and they have amazing breadth and depth. After a few minutes of research for Alibaba Cloud, they seem to have the breadth but I'm not entirely convinced about their depth. The documentation is quite clear but quite narrow (they only seem to have a Python SDK?) and there doesn't seem to be much buzz online for their platform, though (i.e. blog posts about them, forum comments; most of the Google results for searches about them return only alibabacloud.com pages).

In any case, more competition is better, so they're definitely worth keeping an eye on.
Yes, so far the statistics we have about the safety of AI cars are mostly meaningless to say anything useful about how they would scale if applied universally.

Another thing that bothers me is how often the argument 'human drivers are terrible, far worse than computers for situations A, B, C, etc' is used to suggest that AI systems will improve road safety. I will be the first to admit that many people are terrible drivers, they make mistakes, don't pay enough attention, don't obey traffic laws, have bad reaction times, etc, no argument there. But so far I have never seen any statistics about how many of the accidents caused by these kinds of human failures actually lead to fatalities. Taking the human out of the equation could in theory improve all kinds of car accidents, but how many would be just fender-benders as opposed to road fatalities? It's not like it is super-easy to accidentally cause a fatal road accident, and everyone knows one or more people who were involved in one. Who can prove that AI cars will not decrease the total number of accidents of any kind, but increase the kinds of accidents with fatalities, like this one with the Uber car? Maybe human drivers, with all their faults, would have avoided this particular accident by driving more defensively or using social cues to be more prepared for this woman crossing the street?

I'm not trying to make an argument about the viability of AI cars that are safer than humans here by the way. I personally don't believe AI cars will ever be safer overall than humans in all possible situations that people drive in, but that's a different discussion. What bugs me is that suddenly it seems as if the whole world is willing to bend over backwards to interpret statistics about the presumed safety of AI cars in the most favorable way possible, and at the same time ignore all these relatively simple things that could actually improve safety right now, at much lower costs than developing fully autonomous cars.
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Opel got bought back to europe by PSA the owners of Citröen and Peugeot in 2017 so they have a chance to turn it around.
Autonomous cars need to share the road with human drivers, so they should not behave in a way that is surprising to humans, to the extent possible.
Currently have two cars; one Mazda '14 3 with AEB, Lane Departure alert, radar cruise, BLIS, rear cross alert - and the other an '11 Outback with none of that (but DSC and ABS, as well as AWD).

The assists are certainly helping more than anything, so I feel that the Mazda is much safer to drive in heavy traffic than the older Outback.

The cruise has autonomy over controlling the speed only, and applying brakes, but it is still autonomy. Of course since my hands never leave the wheel it may not fit with what you have in mind.

Having said that, Mazda (or Bosch?) really nailed their radar, having never failed to pick up motorbike riders even though the manual warns us to not expect it to work.

I feel more confident in a system where the ambition is smaller, yet execution more solid.

Fwiw I also tested the AEB against cardboard boxes driving through them at 30km/h not moving accelerator at all, and came away very impressed by the system. It intervened so last second I felt for sure it wasn't going to work, but it did - first time was a very slight impact, next two were complete stops with small margins.

This stuff is guaranteed to save lives and prevent costly crashes (I generally refuse to use the word "accident") on a grander scale.
I agree on the bigly-level stuff (it's very similar to the facile jokes about George W. Bush being dumb) but this quote specifically is clear cut. Of course Trump is not calling Mexico/Mexicans rapists (though he does disparage Mexico shortly before it) but he was calling most Mexican-Americans criminals and rapists: since the ones Mexico sends into the US are "their rapists" and Mexico isn't "sending their best", it stands to reason that the resulting Mexican-American population, for Trump, is overwhelmingly comprised of criminals and rapists.
You basically summed up SV arrogance in a single paragraph.

Seriously, one would argue that SV knows more about farming than farmers?

Knowing how to build pianos doesn’t mean you also know how to compose music.
Wow, sad! And here I thought free market would have prevented it…
/s
MVC is not MVP see also https://stackoverflow.com/questions/2056/what-are-mvp-and-mv...

Objects vs Structs - a struct is just a collection of data, while an object is a collection of data AND behavior (methods).

Callback vs Continuation - I wouldn't expect a continuation to be called more than once, while I callback can.

Pub/Sub vs Observer - with the observer pattern you register for updates directly on the object that is responsible for them, while with pub/sub there is a central component involved and you don't even need to know who originally published it.

So no, for none of the examples you gave you can just replace one term with the other.
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On the other hand, I've run multi-hundred-node HPC stateless HPC clusters long term off an (rpm-based) NFS root with little trouble once I could get the cluster vendors out of the picture. Places like the Tri-Labs appear to -- or have done? -- with larger systems, even if they need something like https://computation.llnl.gov/projects/spindle at scale. What flattened NFS wasn't executables but i/o of data files, BLAST being the worst offender; staging those in array jobs was definitely worthwhile.

I strongly prefer the trades-off of stateless systems in that context, though I might prefer to do it off a parallel filesystem, and clearly your kilometreage varies. [From experience ~10 years ago, I'd say avoid GPFS more than NFS, but doubtless it's improved, and I hold no brief for NFS.]
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I read "Dragnet Nation" shortly after it came out.

http://juliaangwin.com/dragnet-nation-available-now/

And a couple years later "Chaos Monkeys."

https://mobile.nytimes.com/2016/06/29/business/dealbook/revi...

Obviously there are others, as well as articles in between.

In terms of FB et al, we are the product. They know this. We know this. And the prevailing (USA) cultural wind is "Privacy? Who needs it?"

If there's a surprise, it's that its taken this long for this issue to get any significant attention. Let's see how long it lasts. If it lasts.
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Takes up to 24 hours to prepare the archive, then you can choose whether or not to keep the network.

Other interesting privacy settings include sharing your work experience with a resume feature in Word, default-on collection of usage behaviour for ad targeting. I don't recall explicitly opting in to this, only perhaps by continuing to use the site after new terms were created.

I'll most likely leave LinkedIn after backing up my archive of contacts and messages as the value never materialised, despite years of use. The only reason I might stay one more month is to use the free trial for the Premium account, just to check it out. Even then I'm not convinced I'm not wasting my time.
Windows programming was message passing. WM_CREATE Oh the glory.
Ah buyout history. if memory serves me correctly... EV1Server (Cobalt RaQ3s with 300gb data transfer / month - $99 back in early 2000s) -> ThePlanet ($39pm athlons with 1000gb data transfer mid 2000s) -> Softlayer (it started getting pricey) -> IBM (lets double prices and half the data transfer to 500gb). Unfortunately despite great automation devs they missed the software play in a massive way on the cloud front, kind of like Rackspace, kids nowadays will go OVH/Hetzner if they dare for bare metal.
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Abandoned and little known airfields
Quick braking can also be dangerous. Perhaps even LiDAR has to deal with false positives every now and then.
Of coirse it's sad, but I'm more amazed by the fact that man can manage to wipe out a whole species for traditional medicice (which I assume doesn't work in this case?) and dagger handles.
There's a Babel plugin that transforms your code to do runtime typechecks based on your Flow type annotations: https://codemix.github.io/flow-runtime
Actually, tech may be a fine solution in such failed government situations. But, it might take actual decentralized networks to make it really usable.
I just don't see how anyone can give any credibility to Facebook at this point. For a while now, the newsfeed has been overhauled so much that it doesn't make any sense. It's a mindless stream of worthless content that doesn't have any real and tangible effect on people's lives.

More than anything, Facebook seems to have turned into a trigger-happy platform where people can quickly express their emotional state of being in exchange for some comments and likes.

There doesn't seem to be any 'protein' to the platform in terms of everyone using the platform equally. Should you comment something wrong, or something that the other person doesn't agree with -- all hell breaks loose because people want to have their voices heard.

Maybe that's just my opinion. Messenger as an app is definitely still useful and comes in handy to talk with close friends and family when away from them physically.

I am sure that some Groups generate decent content, specifically for sales, and crafty subjects, but business pages look more like billboards where a company changes their advertising message every other day. There's no sustenance to content, which makes the platform mindlessly boring.
> The Democrats are in full political warfare with the Trump regime

but they are not using those weapons

What's so special about Iran or North Korea working on a nuclear bomb, when many other countries already have it?

Well... you know...
"As a pilot, a particular interest of mine has always been the abandoned airfields that dot the landscape of much of this country. Both for their potential safety value to a pilot in an emergency, and also for their sometimes fascinating history, this particular topic has always held my curiosity. When I'm a passenger on commercial flights, I've always found myself looking out the window, constantly looking for airfields below. When I fly as a pilot myself, I've always tried to land at as many airports as possible, to learn a little about each one."—Paul Freeman, website creator
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I believe that's correct. People gave concent to X but Y used the data. Perhaps that's a violation of FB's ToS for apps?

That said, (personal) data gets brokered all the time. And, btw, sometimes the buyers are gov agencies. Who needs surveillance when people willing hand it all over, often in public.

Perhaps not the public will finally begin to understand why the phone meta data "intrusion" was so bad.
Can you explain, what indexing library are you using & how it compares with lucene/trinity and solr/elastic/vespa.ai sharding/replication/performance/efficiency ? Even vespa claims that you need memory mostly storage to have nice SLA, while google is said to have written special index just for ssd-storage (they have a big one).

Usually columnar store is used for aggregations and not for search (inverted-index for that)?

Does it support realtime index or just near-real-time ?
Here in Germany online privacy is a social value, and Facebook is gonna have a even harder time from now on.
I don't see it happen in the rest of the world. I give this three months: when the news cycle will have died out, for Facebook it's gonna be business as usual.
Zuckerberg is in such a denial about the real mission of his creature, that I don't see how it will ever be able to steer the boat, even if he wanted to.
Does he ever lie in bed at night, staring at the ceiling, asking himself "what the fuck did I create"? Will he ever?
Guess I was right then.
Not just security nerds. Take for example Eben moglen, professor in law and history of law.

"So I was talking to a senior government official of this government (2012) about that outcome and he said well you know we've come to realize that we need a robust social graph of the United States. That's how we're going to connect new information to old information."

I suspect that the only reason we are hearing about the Trump campaign being the buyer is that the democrats already had the information. It is also why Facebook can not put the cards on the table since then they would not have any political allies left. Just like with the Snowden leak, privacy is not a issue for which the parties differentiates on. One can only hope that will change in the next election.
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Privacy issues emerge as major business risk for Facebook
It's a fair point. But licenses could be the right direction to go in future. Consider GDPR for doing business in Europe: that seems to be a good thing for data privacy. Cloud services that are licensed to provide GDPR assistance in Europe would be good for both clients and European consumers.
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I don't really know why hundreds (I typically see 200-400) of dimensions are "better" than thousands, but there are a few justifications I can think of. You definitely get diminishing returns as you increase dimensionality, and size is a big concern. As an example, FastText's English word2vec is 300-d with 1 million word vectors, giving it a size of around 1 million * 300 floats * 4 bytes/float = 12GB (I haven't loaded it in a while so I forget if they do anything to compress it or if it gets bloated by something). Considering this often has to reside in-memory you really have to question whether marginal gains are worth a single model occupying on the order of 10x that much memory monetarily (and at sizes like that you even have on-disk storage, boot times, etc. as considerations)

Intuitively I can suggest the following: One of the problems is that even relatively huge corpuses like wikipedia can't deal with high dimensionality that well because even they likely lack the sheer size and diversity of content to "flesh it out", so to speak. My intuition tells me that this is due to the training process overfitting "clusters" of information together due to the size of the model. If you have too many dimensions, there's a lot of space for clusters to form, and with that will come some loss of semantic differentiability between clusters - or at least my hunch tells me so. You definitely want "computer" to be more associated with "mail" than "taupe" but if the frequencies of their associations are small they'll essentially be interpreted as noise or overfit. One thing to note is that word2vec embeddings are trained using a shallow neural net, and it's entirely possible for it to be a generic ML problem of too-many-parameters/bad network topology given the input when dimensions get too high.

With dimensions in this context it can be easy to forget that each additional dimension added can (potentially) add an order of complexity to the model - a smaller model lies on a hyperplane in the new vector space. What may happen is that an added dimension (by added, I mean before training, not after) might add some beneficial complexity for a specific subset of the model; e.g. if we were originally in very low dimensions, adding one dimension may allow king/queen and boy/girl to separate in the vector space based on gender( although in reality you can't create correspondences to individual dimensions and properties like this usually) but simply lead to noise or overfitting in other subsets. I think in very high dimensions this overfitting is likely to manifest itself in either too much clustering or strangely high similarity words resulting from outliers/noise in the data.

I've never really seen thousands of dimensions used in the wild, but I don't know of any papers that explicitly compare performance among different dimensions (word2vec is hard to evaluate with a single metric, though). Perhaps once you get to internal Google or Facebook levels of big data you could use distributed computing to make it work, but again, I haven't seen references to that.
This is great! How would accelerometer + algorithm power usage compare to GPS?

Is there any reason this isn't already used?
Or you could just use Erlang/Elixir and be done with it. Presented approach to message bus has its own share of problems, like mentioned in the article message-type explosion.