skysight-inc/HackerNews huggingface dataset:
Right, the critique is evaluating algorithms based solely on asymptotic time / space characteristics is insufficient. Constants can be significant if they are big enough.
Eh, if they apply today, the wait time for Indians is between 75 to 150 years.
The O-1 is hard to get for mere PhDs. We are a dime a dozen in many fields.
Blockchain has many useful applications: art, insurance, property inference. imo the problem is the systemic changes are not worth the gains (inertia is strong, therefore not that useful?).
>Pip freeze does not resolve transitive dependencies

How? Doesn't pip freeze literally list all packages that's installed in the current environment besides basic toolings such as setuptools (and you could even instruct it to list those as well)?
I would say that in practice LeBron James (celebrity) is effectively a separate entity from LeBron James (human), with overlapping but distinct goals and interests. LeBron may be the "CEO" of and largest stakeholder in the celebrity entity, but the final product presented to the world (basketball games, interviews, social media, movies, video games, trading cards, etc.) is going to be an amalgamation of numerous people's contributions.

In this sense, it's worthwhile for him to make a distinction between the celebrity entity's image/profitablity and his own personal happiness, as well as a distinction between his own personal thoughts/actions and those of the collective "LeBron James" celebrity.

This idea isn't specific to celebrities (except insofar as most people would be smaller operations or "sole proprietorships"); one's mind and the legal entity of one's self are clearly different things — the latter of which may incorporate contributions by accountants, lawyers, relatives with power of attorney, etc. At a more basic level, anyone can at least make a distinction between itself and its body's interactions with the rest of the world.
Someone I know made the observation that Python doesn't scale well with code complexity and team size. Statically tyed languages like Java give you a lot of guardrails, and IDEs make it easy to navigate around code, so it's easier for larger teams with larger projects to safely reason about things.
Perhaps you missed the bit where authorities said that "YouTube advertising instruments" were used to "disseminate information about unsanctioned (unlawful) mass gatherings”?
And this is why I like Boeing's new manned capsule better than the one from SpaceX:

Boeing: https://www.nasaspaceflight.com/2018/08/boeing-starliner-cre...

SpaceX: https://i.kinja-img.com/gawker-media/image/upload/atk7lokher...
(I despise Gizmodo, so it's a deep link for this one)
That sounds nice and all but the DMV analogy does not hold up. Think about if there were no limits by country population, India has more people and therefore the most applicants, so we would be mainly giving limited numbers of work visas to Indians while others would have no chance.

Imagine if there was a company with a white CEO who was only hiring/putting other whites into high level positions because they happen to be in a majority white area. If that makes you cringe, you should have the same reaction regarding this.

Diversity = various countries/peoples around the world getting a fair chance

Not diversity = Only Indians get work visas
I agree. I'm optimistic about tools like Poetry https://poetry.eustace.io/docs/basic-usage/ for solving this. Unfortunately Python predates the realization that good packaging tools were a thing that needs to be solved in the core language and not externally (Go, Rust, Node, etc. postdate this realization; C, Perl, Java, etc. also predate it).

The flip side is that decoupling the interpreter/compiler from the build system makes it more possible to write tools like Poetry (and, indeed, virtualenv) that explore new approaches to the problem. At my day job where we do hermetic in-house builds with no internet access and (ideally) everything built from checked-in sources, building C and Java and Python is straightforward, because we can just tell them to use our source tree for dependency discovery and nothing else, and we can set up CFLAGS / CLASSPATH / PYTHONPATH / etc. as needed. Building Go and Rust and Node is much more challenging, because idiomatic use of those languages requires using their build tools, which often want to do things like copy all their dependencies to a subdirectory or grab resources from the internet.

Of course, given that it's Python, there should be one - and preferably only one - obvious way to do it....
Python's dependency hell is what made me first look at Julia. I develop on Windows (someone has to :) ), and it was just impossible to get all of the numerical libraries like pydstool, scipy, FEniCS, Daedalus, etc. playing nicely together... so I gave Julia a try. And now the only time I have issues getting a package to run are Julia packages which have a Python dependency. Python is a good language, but having everything in one language and binary-free is just a blessing for getting code to run on someone else's computer.
There ware a time when I wondered if I should learn Ruby or Python. These days, unless I'm going to be a Rails dev, hands-down Python.
Isn’t any job for life basically gone now? It’s the clarion call of the millennial generation - don’t expect loyalty from any company you work with or for.

My understanding is that those with law degrees see a ton of competition in the market, because it’s such a prestigious professional calling on the order of doctors but with better work environments. Why wouldn’t it affect those at the partner level?
>I would not accept following two random people around based on skin color and waiting for them to make a trivial mistake that justifies deeper investigation

And I agree with you. But guess what a robot would do? It would follow everyone, all the time, everywhere. By being overly outraged about a small minority of racist cops (I really don't believe it's the majority) we will get something worse that will never ever be able to protest our way out of.

Sometimes, I think the answer to a problem is to accept there will always be some problems. If we continue to try and make a perfect system we end up at a wall and then irrationality pushes us into a bad place, worse than what we had before.
Consumer fintech definitely feels like a bubble. There are a few promising entries in the space, but the overarching trend is price wars in various sectors (trading/investing, loan underwriting, wage advances, bank accounts) competing for the same (scarce) millenial dollars. The TAM is certainly large, but margins will quickly go to zero, and with the sheer amount of contenders in each space, I don't see the majority making it out alive.
>Indeed, people rarely purchase magazines larger than the standard 30 rounds.

30 rounds is standard? That's terrifying.

Anecdata but the NZ shooter had large clips (many dual large clips taped together in fact), and Las Vegas shooter had some crazy "niche" shit.

If it's so niche that nobody cares then what's the harm in restricting things like that? People don't need 40 round magazines to shoot targets.

They don't even need semi-auto to shoot targets, but that's crazy talk.
I agree that Apple is not the only culprit and their competitors should be equally derided, and in fact they often are. The Surface Laptop is the only laptop on ifixit with a repairability score of 0, after all.

But it's still pretty clear that Apple should get a lot of flak because they are frequently the first one to market with anti-repair features, they're pioneers in pushing design features that make repair harder, they sell products at a premium price but their first party support is often pretty bad and expensive and they have a lot of mind-share and they use that mind-share to push the "electronics are hard to repair" myth.

When it comes to bad repairability, Apple leads the way and the rest of the manufacturers follow after seeing what Apple can get away with. In general this is true for a lot of user-hostile design. On the flip-side, their position as leader does allow them to push some aspects of the industry forward, but they haven't been doing much of that lately, and when they do it's usually flawed in some way (their early push for USB-C comes to mind).

So I don't think its unfair for Apple to be the punching bag in this case. They put themselves in that position by grabbing so much mind-share and positioning themselves as leaders to be emulated by their competitors.
This chart looks like it's only through 2018. My hunch would be that Blockchain is down or flat thus far this year.
Recently was trying to convert Python to C#... there are few things that are as absolutely incomprehensible as a Python programmer being clever with numpy. I gave up on the conversion. Perhaps this is a point for Python’s flexibility, but I’d say it’s just a waste.

Here’s the code. Try to convert this to any C style language.

mins = X.min(axis=0)
maxs = X.max(axis=0)
idxs = np.random.choice(range(self.dim), self.dim-self.exlevel-1, replace=False) # Pick the indices for which the normal vector elements should be set to zero acccording to the extension level.
self.n = np.random.normal(0,1,self.dim) # A random normal vector picked form a uniform n-sphere. Note that in order to pick uniformly from n-sphere, we need to pick a random normal for each component of this vector.
self.n[idxs] = 0
self.p = np.random.uniform(mins,maxs) # Picking a random intercept point for the hyperplane splitting data.
w = (X-self.p).dot(self.n) < 0 # Criteria that determines if a data point should go to the left or right child node.
return Node(X, self.n, self.p, e,\
left=self.make_tree(X[w],e+1,l),\
right=self.make_tree(X[~w],e+1,l),\
node_type = 'inNode' )
> AMP’s main benefit has been making it harder to do expensive things.

Its sole purpose is to enable safe prerendering. If you think it's supposed to make things hard, you don't understand it at all.
It says through 2018
Bing has its own AMP cache.
Pipenv has felt to me like a pretty solid solution. It's not perfect but it's a lot better than the other options.
I would say it's more closer to fandoms than pop culture.
You're both a) cherry-picking and b) overlooking the second half of my post.
It does now: http://omz-software.com/pythonista/ (just below the blue bar).
I find rust with cargo and go with go-modules to be pretty nice to work with.
Hofstadter – On Number Numbness (1982) [pdf]
>Compare number of applicants per year from India (250K H1 + some amount L1) to the green card caps (140K). And their population growth is still positive (>1% year).

This is not correct. The 250k includes people who got their first H1B in 2006 till date but have to renew every 3 years. Those are work visa renewals while they wait. The yearly demand is much lower. There is a 85K cap on all new H1Bs. Only 70% go to tech sector. However some governments and nonprofits are excluded from the cap, but the nowhere as high as 250k. Which is why the rest of your comment is wrong.

>Even if Congress kicks out all the rest of nationalities and gives 100% cap to Indians, the wait times will drop only once but then keep growing indefinitely. (And this does not yet account to how many more will be inspired by that, as right now long wait times presumably deter a lot from even trying.)

>There is no fix for this that does not involve a huge lot of Indians failing at their immigration attempt. The core problem is that they are just trying too hard: India applies 8.5x more people per %population than France, 14x more than Germany etc. No Congress can fix that.

Not true again. After 8 to 10 years it will fix itself because the system is first come first served. i.e If a French or German person apply on January 1 2029, they will get their GC before everyone from India that applied after Jan 1 2029.

Actually that would be true even today if the law passes. The French citizen who applies on Jan 1 2020 will get his gc before the Indian citizen who applies on Jan 2, 2020. It's just that if the law passes, they won't get to cut ahead to directly in front of the line, before people waiting since 2009.

It's like going to a DMV. Regardless of how bad the crowd is or where you drove from, you get a token number and no one that came after you gets a GC before you can. The initial wait for some will be high initially because there are people waiting for a long time.
Rapid Coral Decay Is Associated with Marine Heatwave Mortality Events on Reefs
Does it have to be?

I have found that I would rather code my own versions of some libraries so I have control over it. Even if there is some extra long term maintenance and some up front dev costs, it's paid off already a number of times.
Super interesting, thank you for the very informed and insightful comment.

In the same line, from my perspective, randomness appears where the "limit of our measurement resolution" is. In other words, when your only way to measure something is to sample it, then the maximum resolution of your measurements is going to depend on the maximum speed/frequency at which you can sample the thing you are measuring. So in the end all our measurements will always be limited by whatever thing is the fastest that we can handle/operate/understand. Anything faster than that will appear to be random to us. And this is also pretty much the same as what the Nyquist-Shannon sampling theorem says about any wave/information.

Relating to the Kolgomorov randomness under the above, something would be random when we can't sample it fast enough to rebuild its waveform with perfect fidelity within the time frame that it appears to be random.
The description of the tools seems to be to vendor‘s marketing tag line, which I find not very helpful to understand what the tool actually does.
I'm curious, do you not find wheels + manylinux reasonable? I agree that until recently, Conda definitely had that advantage, but now that you can `pip install scipy` and have that get you a working library and not try to compile things on your machine what does Conda offer beyond that?

I guess one thing Conda has that the pip ecosystem doesn't is that it supports installing non-Python shared libraries like libcurl on their own. Is that an advantage? (We absolutely could replicate that in the pip ecosystem if that was worth doing, and it's even not totally unprecedented to have non-Python binaries on PyPI.)
The science of creating a dream team
Those interested in netsuke may enjoy the book "The Hare With Amber Eyes" which weaves the story of a netsuke collection though generations and different continents.
I don't think dumping is really the right word here. As it says in the article, importers are illegally accepting the waste and making a good chunk of money from it. The private companies who are disposing of waste from Western countries are happy to pay these guys to get rid of it. Still they could try to check what happens to the waste, rather than just turning a blind eye. But when the mafia can dump nuclear waste in your own back yard, I guess it's hard to see what happens on the other side of the world to some plastic bottles...

https://gizmodo.com/the-mob-is-secretly-dumping-nuclear-wast...
maven for java
Man that looks fantastic. It looks so useful that it ought to be an official part of Python.
Rust's cargo, JS's yarn and the grand daddy of them all Ruby's bundler address all these issues. Even newer versions of Gradle support a workflow where you specify the versions you know you want and just on everything else, including transitive dependencies, down.
That's exactly how Elixir and Julia do it (with quote and unquote operators), for example in Julia:

clause = :(3 > 0)

expr = :($(clause) ? 0 : 1 + 3)

eval(expr) # 0

Though Julia goes further than Elixir, and not only the quoted element is a struct (Julia's base data type) but also everything in the language is an expression that's represented by it, which lead to people arguing that Julia is homoiconic:

expr.head # :if

expr.args # [:(3 > 0), 0, :(1 + 3)]

Though if you're strict on the "homo"-"iconic" term definition it certainly isn't, it's "dual"-iconic with the surface syntax and the surface AST having different formats with one to one mapping and the AST being valid code (or even "tri"-iconic since Julia SSA IR is also accessible as a data type on the language).
Try converting typical Matlab code to a C-style language and you'll run into similar problems. That's just what you get when your base language isn't all that fast but you have a fast numerics library that allows you to do clever things with arrays and matrices.
Yes!

You’re talking about something different from algorithmic randomness, which would be a property of (infinite...) sequences. When I throw a coin in the air and say “heads or tails”, you have to make a prediction as to where it will land based on the information you have. Not someone else’s information— _your_ information. If you feel like you have as good a chance of winning as losing, you’ll tell us you think it’s a fair — a “random” — coin toss.

You’re talking about betting behavior. It’s not a wild tangent the way some would think — from this we get the structure of probability theory, we get derived preferences, we get the entire mechanics of Bayesian inference that underlies all systems which learn.

From studying this math — the math of the coin flip with a dollar on the table, the math of the universe — we learn that there _cannot be_ “chances” or “odds” out there in the world that we can see if we look hard enough— what we see if we look closely enough will be the structure of our perception, which is a perception itself constituted by subjective probabilities.

We learn that belief states must be subjective, must be local. There can’t be a fact of the matter in any way that makes sense to anyone. And yet we also can prove that we cannot truly reserve judgment, that we cannot be true skeptics— unless we are also not anything recognizable as scientists.

So, yes, absolutely. In the consensus reality we all agree to occupy, how you decide to answer the question “heads or tails” matters — in the deepest possible sense — just as much as anything else. And folks can get _so_ wrapped up in the idea of what an imaginary computer might do, they forget to notice what they are doing with every waking moment.
A lot of folks are -- often justly -- saying that we should be training more Americans for some of these jobs.

I worked for some time in a professional masters program that mostly has non-US enrollment, despite being in flyover land. To complete it costs a fair bit, though it's lower-priced than similar such programs on the coasts, and when you get out especially if you're an American student you're often looking at $90k+ for starting salary (depends on a few factors). It's a very remunerative field.

But we just can't get many US students in! We've been trying to figure it out. US students mainly come in when they've reached a point at their company where they have a manager who says, You need these additional skills -- go to school to get them, and we'll pay. I'm not talking "learn JavaScript library blah", I'm talking stochastic calculus. The school part really is helpful because there's a ton of theory that you don't learn by doing the practical applications.

US citizen grads are placed so fast. There's no such thing as a sure bet, but this grad program is a high-expected-value bet. And yet we just... can't... get... Americans.

I think it's the math. So many Americans are just scared of math. Some of our Chinese students "know" they're "just bad at math" but they don't see that as a particular obstacle; just need to study harder. Americans tend to see it as an inborn anatomical characteristic or something. But also it's the cost of a master's after taking on the crushing load of undergrad debt. Some of our students got their bachelors degrees for free in their home countries & then just had to float the cost of this masters, which is less tuition-wise than 3 years of state college.

There are more structural problems than just "companies, you should grow your own talent". I agree companies should do more: but if we really wanted a US society that fostered technical excellence, we could make sure our schools did that. We've made sure our schools foster football excellence, for instance.

And to get back to the direct topic: we're seeing a ton of RFEs for our grads, and there is no other masters' program that does this stuff within a state and a half of us. You've got to drive 8 hours to get to the next one.
There's no random iteration, it's more like stochastic gradient descent with noise. Your number isn't correct even if only because of codon degeneracy.
Confucius:

> At fifteen my heart was set on learning; at thirty I stood firm; at forty I had no more doubts; at fifty I knew the mandate of heaven; at sixty my ear was obedient; at seventy I could follow my heart’s desire without transgressing the norm.
>a white CEO who was only hiring/putting other whites into high level positions because they happen to be in a majority white area

If 90% of a town is white and 10% is black, 9:1 is a fair ratio for executive boards on average. Anything else would mean that the probability of a person holding a board position given their race would be different for different races. Imagine if every company in Mombasa was required to have an even split between white and black: being born white would guarantee you any job you wanted because you would be competing with less than 1% of the population, while in contrast every other ethnicity would be crowded in to half the number of jobs. In fact if racial quotas were instituted in Kenya and every race was given the same percent quota, 98% of Kenyans would be forced to be unemployed.
Reading this got me thinking and I wonder if other people feel like me about this, so I'm going to share it. This is not serious, but not entirely unserious...

I try to be a good sport about it, but every time I write python I want to quit software engineering. It makes me angry how little it values my time. It does little for my soured disposition that folks then vehemently lecture me about the hours saved by future barely-trained developers who will ostensibly have to come and work with my code. Every moment working with python (and that infernal pep-8 linter insisting 80 characters is a sensible standard in 2019) increases my burnout by 100x.

I try to remind myself that we're trying to make the industry less exclusive and more welcoming to new developers and "old" isn't necessarily "good" (in fact, probably the opposite), but damn I just don't understand it.

It used to be that I could focus on other languages (Erlang, Nemerle, F#, Haskell, Ocaml, even C++) and sort of balm myself. But now, I can't even overcome the sinking feeling as I read the Julia statistics book that I'm going to be dragged back to Python kicking and screaming in the morning, so why even bother?

And frustratingly: it's one of the few languages with decent linear algebra libraries. And that means it's one of the few languages with good ML and statistics support. So it's very hard not to use it because when you want to cobble together something like a Bayesian model things like PyMC or Edward actually give you performance that's obnoxiously difficult to reproduce.

This is what the industry wants and evidently a lot of people are okay with it, but to me it's misery and I can't work out why people seem to like it so much.
Apple Care isn’t that expensive - I’ve rarely had an apple product break that hasn’t been free or under $100 to have fixed at the Apple store.

Louis Rossmann is the best, but I’ve never really encountered a reason to care about Right to Repair...
Imagine a highly efficient compressor watching Toy Story in 4k definition. If it was really intelligent, then it could abstract the 3D-models, motion, physics, lightning, and textures, and store the movie (or something imperceivably like it) in a highly compressed representation. Or even write down just the script and direct a movie so similar that it can't be distinguished from the original.