skysight-inc/HackerNews huggingface dataset:
I'm genuinely curious why you are asking third parties to put words into my mouth. Why not just ask me?

If you want a summary, I don't share your religious faith that God ensured an identical statistical distribution of genes across all subpopulations when he created man. But Kalium's argument is not dependent on this - there are more things in the world than simply teachers, curriculum, facilities and genetics. For example, poor people might be disproportionately bad parents (perhaps they exhibit many bad behaviors which also make them poor) and this might cause their children to be disruptive in school.

That's a concrete theory that's directly compatible with your secular faith in statistically identical genetic distributions, but still supports Kalium's claim.
I would handle it publicly if I felt I was treated unfairly in a way that suggests the company is inherently biased.

I don't understand your use of 'clawed back.' Commonly stock options don't vest until the first year - were your options really clawed back or were they unvested at termination?

Why were you fired?

It's plausible you can make a statement anonymously, while your employer would know who it is, most hiring managers in the future wouldn't know it was you, or of the issue.

There's nothing wrong with going on unemployment when you're terminated. You directly or indirectly pay for that unemployment insurance.
>What I'm concerned about is the government stifling innovation such as driverless trucks to retain those jobs...What is the alternative?

More likely the Government comes up with "innovative" ways to hide these people from the official unemployment numbers. Somehow unemployment is calculated at only 4.9% today...add 3.5 million newly unemployed commercial drivers tomorrow (>10% of US total population) and the new unemployment rate = 4.9%.
We've been running a hybrid on-prem solution for nearly 3 years now. It's been challenging, but Kubernetes has drastically simplified it for us. It now means we can spin up a client site in 1-2 business days, provided we have a server on-site ready to go.
I would also suggest Buffett is very focused on his reputation, and doesn't want to be seen tolerating behavior like this. From one of his letters to his managers:

We can't be perfect but we can try to be. As I've said in these memos for
more than 25 years: "We can afford to lose money — even a lot of money. But
we can't afford to lose reputation — even a shred of reputation."

We must continue to measure every act against not only what is legal but
also what we would be happy to have written about on the front page of a
national newspaper in an article written by an unfriendly but intelligent
reporter.

http://blogs.wsj.com/deals/2011/03/31/warren-buffett-on-ethi...
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Any examples of devices that don't??
Laws are not in anything that can be called in natural language; they are in a code called "legalese".

Legalese doesn't have to be formalized into program-like code. Rather, perhaps into mathematical language, with some of the notations that go with it. It needs to use clear logic, and set theoretic descriptions and reasoning. Law is all about logic and sets: what rule applies under what conditions, and what is included and excluded and so forth.
I want "I am unwilling to make u-turns." They are illegal by default in the city of Chicago, but if you miss a turn, Google will try to get you to make a dangerous and illegal u-turn. If you ignore that, it'll suggest you another one further down the road. No thanks, I'm not turning around on Michigan Ave at rush hour.

I've looked into this. Apparently you set turn restrictions per-intersection in the maps data editor. No one has the patience to go check "u-turn not permitted" on all the Chicago intersections that don't have it currently, so we're stuck without major architectural changes from Google.

"Avoid u-turns" should be next to "avoid highways."
Time is money. The actual monetary cost of training is irrelevant if you don't have the time to actually do it (learning new skills has never paid the bills in the right now timeframe).
Sure, and just to be clear that wasn't me straight griping. Completely understand you guys have priorities. Just doesnt change the fact that it's an existing pain point for heavy Gitlab users.
Is this a spoof? it is 100% WRONG for me on Vivaldi browser.

Says im logged to FB and nothing more. I dont even have a bookface account, but I do have gmail/YT/github/reddit and few other open in the adjacent tabs and fully logged in.
This is a quote from the source, the 2015 San Francisco Housing Count Report:

"Seventy-one percent (71%) of respondents reported they were living in San Francisco at the time they most
recently became homeless, an increase from 61% in 2013. Of those, nearly half (49%) had lived in San Francisco
for 10 years or more. Eleven percent (11%) had lived in San Francisco for less than one year. "

http://sfgov.org/lhcb/sites/default/files/2015%20San%20Franc...

So, no it's not "fast and loose," they actually did make a distinction between short- and long-term residents.
Unlike 30, 20, or even 10 years ago, we have heaps upon heaps of labeled datasets now. So much human life happens through technology that we are doing an astounding job of producing labeled datasets.

And computers are fast now. And RAM is infinite. And GPUs are fast and plentiful. And all of this is cheap.

AI stuff is already real more than most of us realize on a day-to-day basis. While machines might not be "intelligent" per se, their cleverness has definitely started impacting desk jobs.

The desk job stuff is what most of those alarmist news items are worried about. Nobody seems to worry [too much] about reducing blue collar jobs through automation. Can you imagine how many people you'd need to unload a modern container ship without computers tracking stuff and optimizing storage? Or how much work it would take to harvest modern crops where automated harvesters are used?
And how is the port supposed the stay functional upon removal of the key? The point of this attack is stealth.
Like they say in the article, there's general AI (think sci-fi computers with minds) and specialized AI (think good old fashioned statistical models, but applied to more things and super effective).

Specialized AI (and I hate calling it AI) is coming along really quickly. We're getting better at it in existing fields and learning to apply it to new fields. More than anything, we just have so much data on everything now, and computers are pretty powerful now, so even old school models are finding tons of new applications.

Generalized AI is a different story. We are a few really major breakthroughs away. We aren't even 100% sure if they are possible, much less understanding how to do them. These aren't the normal slowly-chip-away-at-it breakthroughs, these are things we have no clue about. With something like that, who can really say how far we are? It could be 5 years, it could be never.
Same as FDR's inversion of Sumner's Forgotten Man

https://en.wikipedia.org/wiki/Forgotten_man
"There can be no Justice so long as Laws are absolute".
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This is probably the most important research direction in modern neural network research.

Neural networks are great at pattern recognition. Things like LSTMs allow pattern recognition through time, so they can develop "memories". This is useful in things like understanding text (the meaning of one word often depends on the previous few words).

But how can a neural network know "facts"?

Humans have things like books, or the ability to ask others for things they don't know. How would we build something analogous to that for neural network-powered "AIs"?

There's been a strand of research mostly coming out of Jason Weston's Memory Networks research[1]. This extends on that by using a new form of memory, and shows how it can perform at some pretty difficult tasks. These included graph tasks like London underground traversal.

One good quote showing how well it works:

In this case, the best LSTM network we found in an extensive hyper-parameter search failed to complete the first level of its training curriculum of even the easiest task (traversal), reaching an average of only 37% accuracy after almost two million training examples; DNCs reached an average of 98.8% accuracy on the final lesson of the same curriculum after around one million training examples.

[1] https://arxiv.org/pdf/1410.3916v11.pdf
My point was that, assuming most people are unfamiliar with Chinese history under Mao, the expression will have positive connotations.
You can actually have privacy badger black all of this if you play around with the settings.

I mean I think its too much to ask for a tool to be able to block everything right without a little human assistance.
I can't help but completely disagree with both the idea and the probability that this will ever happen.

Modern law is supposed to be open, so that anyone can read it. Reencoding laws, for whatever reason, strikes me as being fundamentally undemocratic.

The argument can be made that if legal "code" is taught in schools, then it's no more undemocratic than writing down law, but the chances of that happening seem slim to none.

Another argument is that law is already written in "special" English that most people can't figure out, but I think that having it in English alone is a big step toward having it being readable by almost anyone.

It would be neat to have law written as code and to have AI be able to parse it for you in lay language -- that is, you could ask it questions or pose situations to get a legally-binding answer. But then the question for me is, why don't we just have said AI read the current legalese and parse it?
I work for Pivotal, which has a slightly different horse in this race: Pivotal Cloud Foundry. It's based on the OSS Cloud Foundry, to which Pivotal is the majority donor of engineering.

Lots of customers want multi-cloud capability: they want to be able, relatively easily, to push their apps to a Cloud Foundry instance that's in a public IaaS or a private IaaS. They want to be able to choose which apps go where, or have the flexibility to keep baseload computing on-prem and spin up extra capacity in a public IaaS when necessary.

It also happens that lots of CIOs have painful lockins to commercial RDBMSes, and they don't want to repeat the experience. They want to avoid being locked into AWS, or Azure, or GCP, or vSphere, or even OpenStack.

CF is designed to achieve all of these. The official GCP writeup for Cloud Foundry[1] literally says "Developers will not be able to differentiate which infrastructure provider their applications are running in..." (can't say I completely agree, GCP's networking is pretty fast, which is I guess what happens when you have your own transoceanic fibre).

If I push an app to PCFDev -- a Cloud Foundry on my laptop -- it will run the same way on a Cloud Foundry running on AWS, GCP, Azure, vSphere, OpenStack and RackHD.

[1] https://cloud.google.com/solutions/cloud-foundry-on-gcp
More properly, both the CPython 3.6 and PyPy compact dicts are based on this proposal: https://mail.python.org/pipermail/python-dev/2012-December/1...
and this proof of concept: http://code.activestate.com/recipes/578375
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Oh, please. An induction coil charger probably emits more power.

In addition, this emits a VERY wide bandwidth noise pulse (look at the frequency output of a spark gap transmitter) which of necessity puts very little power in any specific band.
You are right; I stand corrected.
or ContentBlockHelper
Isn't this a Wolfram blog? Why is it here?
If you're into that kind of stuff, read Mark Lawrence's books. It's set in post-modern times where our civilization is known as The Builders. Complete with ghosts coming out of unintelligible machines and talking about how stupid everyone is these days.
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To be completely honest - probably nothing. This is a legacy issue on our end, not yours. I haven't even taken the time to explore migrating our GH/Codeship builds to GL CI. We essentially mirror our repos amongst both offerings at the moment, running builds via Codeship until either they support GL and we can drop GH, or we get the time to spend on a proper Codeship => GH CI migration and we can drop Codeship. Anyone's guess what will win out at this point :)

Appreciate the response either way.
>At what point did I assume the responsibility of giving back to those travel agents?

You won't have to. If it gets bad enough, they'll come take it.
PayPal? No way
I think machine learning has a real ability to do certain things (image recognition especially) and do them in a way that isn't hype by itself.

I suspect that you'll encounter limits to the techniques before they do everything a person can do.

If there's a potential problem with machine learning that could sink the enthusiasm over time, I suspect it would come because machine learning applications are these black-boxes system which are the product of training with huge datasets and which use the very tuned-level of expertise of their creators (a common joke is talking of the "graduate school descent" algorithm, getting enough grad students to tune your app till it work). It may be that the deployers of these applications may find that when they have to train them again, in a year's time, that the geniuses have moved on to other things or that the geniuses now charge rates that look excessive for an application that works for just a year.

But that's just spinning possibilities. Currently things seem to be going great.
1. I've had some experience with counselling and psychotherapy. Truth is I really don't see my depression as a bad thing. I see it as something that in my case is entirely logically routed and I don't understand why other people are so happy all the time. I don't see myself as someone who needs help or curing, but the only sane person in the room. I guess I just want to know how to live my life as a person who's different mentally in certain ways rather than feel like I need to thinking positively like the people around me just to survive.

2. Ah, that's cool. I'll look into it although I'm not sure I would personally classify as disabled, or even want to. I certainly don't see myself as disabled in anyway.

3. That's a really cool service. I wish I could sign up, apparently it's in private beta and I can't see an email form anywhere. =(

And yeah, some people relate of course. But in my experience it's probably around 1 in 25 who relate, with probably around 5 out of every 25 who strongly dislike people who are depressed. And I'm not hating on these people, I almost hate people who are unrealistically optimistic all the time, but society often tells us that kind of disorder is good. Which is crazy to me.
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Interesting: I've submitted this story over a day ago (https://news.ycombinator.com/item?id=12684118) with a clean URL, yet this submission got noticed?

Yes, good luck and good timing, but still - ha!
Note: This may not generalize to your use case. We mainly serve big data customers including banks, telco, and have also seen other environments similar to the "air gapped environments" listed below.

That being said:
Would just like to add some coloring to this.

>> However, not every customer that wants on-premise is a government agency with air gapped servers.

This is the bulk of our customer base and also a very large portion of the market still. I deliver software via dvd (flash drives nor wifi not allowed)

A few notes from these kinds of customers:
They won't let you just install anything.

Docker is great but doesn't have a lot of enterprise adoption (despite the self perpetuating hype cycle) outside the companies that already have mature software engineering teams as a core competency.

They are often running centos 6.5 or less yet.

A lot of these environments still require deb/rpm based installation.

Admins at companies that run on prem installations tend to be very reserved about their tech stack. Docker looks like the wild west to folks like that.

Our core demographic:
We do a lot of hadoop related work. We have a dockerized version of[1] that we deploy for customers.

We have also been forced to go the more traditional ssh based yum/deb route. We have automation for both.

They are right that many "on prem" accounts are now "someone else's AWS account".

We also have to run stuff on windows server as well. Docker won't fly in that kind of environment either. Microsoft still has large market share in enterprise yet and will for a long time.

K8s and co is great where I can use it, but it shouldn't be assumed that it will work everywhere let alone in most places in the wild yet. Hopefully that changes in the coming years.

Again: This is one anecdote. There are different slices of the market.

[1]: http://www.forbes.com/sites/curtissilver/2016/10/03/skyminds...
> My understanding is that its too slow and not accurate enough for pinpoint tracking of targets (...)

I find these two assertions very surpsising. Which part of the process do you expect to be slow and what do you mean by slow? Why do you expect accuracy much smaller than the size of a pixel in an image?
Your explanation of crime in endogenously black neighborhoods is reasonable, but it only explains why crime existed in the first place, not why it increased so much in the 1960s through the early 1990s.

The endogenously black neighborhoods did not experience erosion of the tax base due to white flight, because there were few, if any, whites living there in the first place. So, why did crime increase dramatically in the endogenously black neighborhoods during the time period we are talking about? Whatever the reason is, why wouldn't it be the same reason crime increased in the areas subject to white flight?

I find it very unlikely that the endogenously black neighborhoods experienced an increase in crime for one reason, and the nearby white flight neighborhoods experienced an increase in crime for a totally different reason (such as erosion of the tax base after white people left). Obviously the erosion of the tax base made things worse, but unless that caused all of the increase in crime, something else was going on.

If you are going to argue that crime increases after white flight were a self-fulfilling prophecy and would not have occurred without white flight, that's a pretty extraordinary claim.
This is also true of astrology and MBTI has as much scientific validity and predictive value.

No one's disputing that a useless tool can be misused. They're questioning the use of useless tools at all. They give the illusion of understanding to those not interested in evidence.
I actually solved this with our custom deploy script. We choose the machine that runs the migrations.

The necessity of building and maintaining a custom deploy script is the biggest wart for us (though I admit that the API is pretty good, and said script has not had that much maintenance overhead).
I'm a huge believer in colocation/on-prem in the post-Kubernetes era. I manage technical operations at a SaaS company and we migrated out of public cloud and into our own private, dedicated gear almost two years ago. Kubernetes and--especially--CoreOS has been a game changer for us. Our Kube environment achieves a density that simply isn't possible in a public cloud environment with individual app server instances. We're running 150+ service containers on each 12-core, 512 GB RAM server. Our Kubernetes farm--six servers configured like this--is barely at 10% capacity and I suspect that we will continue to grow on this gear for quite some time.

CoreOS, however, is the real game-changer for us. The automatic updates and ease of management is what took us from a mess of 400+ ill-maintained OpenStack instances to a beautiful environment where servers automatically update themselves and everything "just works". We've built automation around our CoreOS baremetal deployment, our Docker container building (Jenkins + custom Groovy), our monitoring (Datadog-based), and soon, our F5-based hardware load balancing. I'm being completely serious when I say that this software has made it fun to be a sysadmin again. It's disposed of the rote, shitty aspects of running infrastructure and replaced it with exciting engineering projects with high ROI, huge efficiency improvements and more satisfying work for the ops engineering team.
It depends. Do you consider loss of reputation part of the punishment, or just an additional natural consequence of the fraud? If you want to think like an economist about fraud, in terms of pure monetary cost/benefit (which is not how people, even CEOs, think), then the game is something like this: Every year you can get $X by being honest, or $(X+Y) by committing fraud, you have probability p of being caught every year (assume: independent) and will have to pay $Z if caught, per year you stole $Y. Additionally, because of loss of reputation, you will only be able to earn at most $W honestly afterwards, instead of $X (assume: it won't be possible/reasonable for you to get away with fraud a second time). Thus, so long as i(X+Y-Z) + W(years_of_career - i) < Xyears_of_career any time (1-p)^i > 0.5, fraud is disincentivized. Sure, you can make the model more complex by adding the extra interest of earning an additional $Y early in your career whether or not you can leverage fraud to be promoted, but you still end up with an equation in which being finned and* removed from your position is rarely worth it if: a) the probability of being caught is high, b) the fine is in the ballpark of the damages (Y+\epsilon due to moral damages and legal fees) and c) being found out comes with an extra-legal reputation cost.

Also, at the levels we are talking about here, is money anything more than a proxy for ego/reputation? Would you rather have $10 million and be well regarded or $40 million and infamous?
How is "white flight" irrational?
I don't even see a practical scheme to tax AI. What counts as AI? Are A* and Sudoku solvers AI, or are we just talking about machine learning? If the latter, am I taxed for doing a linear regression, or only for the "cool" stuff like deep networks? If so, how deep? Am I charged per computation? How are you going to keep me honest?
Nope it is not.

Going on premise might have some advantages but it comes with completely different problems that you didn't even thought about. Some of them:

* You thought of all the power redundancy, ideal cooling, humidity, etc... but then your office gets robbed and all your computers stolen.

* Network wiring... some people are lousy, create an entire spaghetti mess with them, used a crappier type of cable, cable crosstalk from other equipment, someone stepped over a cable and damaged it. Which one is it? good luck finding it out.

* Hardware fails, power supplies fail, disks fail, everything can fail.

You can pick these battles, or you can focus on your software based service. I suggest the latter.
Would be nice to have a more detailed explanation of what exactly they're opposing here, and some data to back up their claims about it.
> At what point did I assume the responsibility of giving back to those travel agents?

At the point when you started living in a peaceful and organized society, that depends on not many people having a disastrous future to keep being peaceful and organized.
Why not keep it in english and add some unit tests that demonstrate the intent of the law?
Then you could just as well bring a crowbar and throw it at something to cause a short. Or just smash stuff manually. This device has a very small range.
Why is using CloudFormation a bad thing?
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