skysight-inc/HackerNews huggingface dataset:
Oh I thought you meant CS academics. With that I (semi-)agree with you, physics professors can't code for shit.

I only semi agree because this seems to be a phenomenon of an older generation. Newly minted PhDs are often much more proficient in programming, since they usually have received a much stronger education in that regard.
Yes, light is all important.

I've participated in online photo review communities that almost always seem to end up bickering about composition and other rules as if they were absolutes. Such discussions can often miss the underlying art, or photographer's message
Nothing is reduced just shifted away from your perspective. You pay for the server running your serverless code. You just share that cost.

Sharing the cost brings benefits but it also brings pain. First time you hit an AWS hard limit you will realize how much pain
NativeScript 4.2 is Here
Very few companies are big enough that they can make the devops overhead worth the price difference, but most of those plan on eventually being so. So there's an argument to be made that the knowledge should be grown in house while you can still tolerate the small outages you get when you have stuff misconfigured or unbalanced.

Probably not a good argument though. If you're successful enough to be saturating servers you're probably successful enough to be hiring experienced competent help for the transition.
yeah i'm sure. How is it any different than working with papers on a physical desk? Or working with a large corkboard or whiteboard where you place many items while working on something big?

Because that's the idea i'm envisioning. Being able to put papers or applications on a virtual whiteboard that completely encircles you. Move them to where you want, make them "fullscreen" (full-view?), maybe even be able to move them forward and backwards in focus and "position". Hell, with some extra work, we could even put them on surfaces around the room. Throw a monitoring program on the wall next to my window, "project" keybindings on top of my keyboard's keys when i'm pressing parts of a combo, etc...

Hell, even if you hate the idea of an "augmented reality desktop", you could just project "fake" screens and use them the same as you normally do.

I mean it's not like our current tools just go away and I'd start craning my neck to look up and to the left as far as possible for 9 hours a day... You could still have tools like "multiple desktops", and change/move them. But now I have the option of putting my task manager above me at like a 60 degree angle straight ahead and can glance up at it when needed.
I'm not sure about 'always.' Google's search was just one feature of AOL's homepage.

In fact, a lot of startups have grown specifically because they focus on one thing and their competitors have varied goals.
I do that by breaking the boring task into chunks of size one - one page, one text file, one paragraph - and doing that one chunk in between tasks I enjoy. Enjoyable task for half hour, 5 minutes on next chunk, enjoyable task for half hour, 5 minutes on next chunk...

"One" is the magic number for me, make it anything greater and my brain seems incapable of understanding 2/3/4 != infinity, collapsing itself into the procrastination pit.
I use word processors to work with other people. I can't tell you how many times I've been sent .doc, .ppt, .xls, or other Microsoft file formats that have become ubiquitous in the modern workplace.
MagicLeap definitely has been overhyped, but for HN readers, there are still reasons to be cautiously optimistic that this is real progress.

1. There's a neat hardware size progression for ML that was posted on Twitter: MagicLeap's gone from a device like you stare through at the optometrists office down to something comparable to a scuba mask.

https://twitter.com/karanganesan/status/1024970520205307904?...

2. There are a few different ways to achieve AR style displays and what Magic Leap has chosen is the hard way -> lightfields and eye tracking (two technologies that haven't really been attempted to ship at scale).

3. This is still a developers' release - and not truly a "paradigm shift" or whatever overhyped term you want to use.

Separate from all that, I still think the end game of AR (in the next 10ish years) is to be the thing that comes "next" after smartphones. The proper way to view this ML Dev kit is that it's the equivalent to a PalmPilot or other barely functional PDA that had some good ideas, but didn't quite hit the right inflection point of portability, screen, battery life, form factor, etc. but that paves the way to get there.
That should be done as well, the flashcards are just a supplement. I find there's often a weird transition where if I'm just reading docs as if it were pleasure reading, I'll be nodding my head, "yeah, that makes sense", "yeah, that's easy", "yeah, I understand", then all of a sudden, "wait a minute, I'm totally lost and don't remember a thing from the last five pages!"

Also, it's easy to get the bird's eye view of a language (say, React, for example), but when you're down in the trenches, you need to KNOW about the pedantic little details (like "class" vs. "className", "for" vs. "htmlFor", minutiae of React lifecycle, etc.)
That doesn't help if the implementation is bad (as many are) and drops tracking cookies until out-out - your main session still get the tracking nuggets.

> in Firefox at least no cookies are shared between public/private

That is also the case for incognito/private/what-ever-they-brand-it mode in Chrom{e|ium}, IE, Edge, and I assume (though I haven't tested this myself at all) Safari and others too.

Though there are some clues that can leak from normal to private due to known bugs & edge cases in the browsers and common add-ons (like flash), search for "evercookie" to find some references about that, and there are other ways to fingerprint or track you which might be less reliable but still apparently work well enough for people to use them.
> ...and you thought you were heating with renewable energy.

No we didn't. As a mathematical modeller and software developer for their inhouse production optimization software, I was perfectly aware of what was happening.

> Much of the "surplus" power on the grid comes from coal plants (especially in Denmark!)

Most of the power plants owned by Ørsted are bio-converted and runs primarily on wood chips and pellets. Unless you are talking about surplus energy imported from Germany, what you say simply isn't true.

Besides, the huge amounts of surplus energy that often came from germany were caused by their massive open sea wind farms, making the energy pretty green.

Ørsed operated almost exclusively combined heat and power plants, meaning that they can produce heat and power concurrently. The utilization of energy was well above 90%, when we ran the plants this way, because we cooled the plant with the district heating water, instead of sea water. The theoretical maximum is ~98%.

We also never planned for pure power production, only to turn it into heat again. That would be monumentally stupid.

We had many, highly skilled engineers and power traders, and they absolutely knew what they were doing.
Web 3.0 Will Be Powered by Blockchain Technology Stack
I am sure :)

Our customers are concentrated around N. America, with minimal activity at night and weekends. We have a complex product with a wide surface area. Some of our services don't see usage constantly throughout the day.

Our usage is unpredictable and spiky, worsening our ability to cost optimize EC2 autoscaling.

Then there's staging environments...
Baidu actually does recognize 銅鑼灣 as a location and even suggests other places in Hong Kong (旺角、南丫岛 etc, incidentally in Simplified Chinese instead.)

The results just weren't good.

Actually I didn't get a map even with your link. Perhaps it's because I'm not in mainland China?

It shows up like this: https://imgur.com/vCa07JM

My search's Google results look like this: https://imgur.com/di147uj
Note: The slides are in English, but the talk is in Danish. Click through to get to the video, then register to download the slides in PDF.

Toit is Lars Bak and Kasper Lund's brand new programming language and software platform for small IoT devices. There's very little else I can find about it online; it was publicly unveiled in this session: https://di.ku.dk/english/event-calendar-2018/dsfd-talk-lars-...

I can't find an online recording of that, if there is one.

Other links I've found:

* toit like a tiger: https://www.toitware.com/ (check out that font!)

* news article: original danish: https://www.version2.dk/artikel/aarhus-eksperter-chromes-jav...

* translated to english: https://translate.google.com/translate?sl=auto&tl=en&js=y&pr...

* github organization: https://github.com/toitware (no repos or public accounts)

* twitter account: https://twitter.com/toitware (no tweets)

Toit's features:

* object-oriented

* indentation-based syntax

* looks a bit like self/smalltalk (not surprising)

* virtual machine and compiler written in C++

* lightweight processes/tasks, not async

* will use raft

* IoT target platform right now: ESP32: http://www.m5stack.com/

* garbage-collected

* project started in February 2018

* will open source the vm, language, core library

Example, seen in the news article and in the slides:

class TreeNode:
left := null
right := null

TreeNode

TreeNode left right

size
result := 1
if left: result += left.size
if right: result += right.size
^result

build_tree depth
if depth == 0: ^TreeNode
^TreeNode
build_tree depth - 1
build_tree depth - 1

main
tree := build_tree 5
assert tree.size == 63

TreeNode and TreeNode left right appear to be constructors.

i know what you're thinking: "nulls?! in a language in 2018?!"
Stupid F#: Taking JSON to the SPA, Part 1
> Paraphrasing Qc Na: Subclasses are a poor man's sum type. Also, sum types are a poor man's subclasses.

One of the great things about disjointed unions is (usually) exhaustiveness checking. Not to mention usually some form of pattern matching. Case classes would do the trick. It would be interesting to see those features in Dart, congrats on the release.
Rich data grids with React
I suspect visible presence would be a bit higher for the NYPD, just because NYC has more officers in an area that's half the size of London.
The Magic Leap doesn't just dangle one image in front of your eyes, like Microsoft's Hololens. Rather, the Magic Leap projects physically projects several visual layers at different focus distances. If you are looking at something near in the real world, your eye will change focus to look at it, and the "near" projection in the Magic Leap will be in focus, while the "far" projection will go blurry, right along with the "far" in the real world.

However, I think Magic Leap has reduced the number of layers down to something like three [edit: two], from the many more layers they were showing before.
Also, API Gateway is incredibly slow. We often have lambdas that run for 20-30 ms, but API Gateway adds another 200 ms extra. We ended up running our own HTTP service in Beanstalk that forwards calls to Lambdas. It's stupid that we can create a better gateway than Amazon using their own services.
Trams get the highest priority on Amsterdam roads, and that is because they are on rails. It means their options to avoid accidents are extremely limited: they cannot avoid obstacles, only adjust their speed.

You are right about taxis, I'm pretty sure they don't actually have breaks. I would also add bicycles to this list, they mostly ignore traffic laws in Amsterdam.
Sadly, it's considerably more than most of them would have earned in five months on the outside.
It was way worse.

The the 80s NYC of my youth almost every aspect of traffic engineering was worse and more dangerous. You may not have observed cars blocking crosswalks because the crosswalks were missing.
Why wouldn't you be able to switch between "desktops" with a key press any more? Have some imagination.
How Your Screen Knows to Spin
And just because something is common knowledge doesn't mean it's true, especially when you start taking about common knowledge within a group.

You don't have to link to a source on the internet either, citing a book or newspaper article would be sufficient.
Machine Learning Library, written in J (APL dialect)
The asterisk was formatted out. Read the book, they are types.
It's people who aren't paying attention to WTF they're doing that cause the danger, not cars or bikes or pedestrians. The rules of the road (including the rules for cyclists and pedestrians) include tons of redundancy so one party not doing what it should almost never causes accidents.

Take for example a pedestrian and a car turning right arrive at an intersection. The pedestrian has a walk signal and the car wants to make a right on red. Both those actions are triggered by the same condition, no cross traffic. In a naive simulation they'd hit each other. In the real world they see each other and one yields to the other in a manner that depends on the situation.

I walk through a "highly walkable" city to/from work every day. As someone who used to have to drive a delivery vehicle I try not to be an idiot pedestrian, when I cross on a don't cross signal I time it with the lights, I don't cross when someone might want to race through the intersection just before the light change, etc.

The behavior I see from other pedestrians and often cyclists is just moronic (and drivers too but there's so much traffic they rarely have opportunity to do stupid things). I don't expect people to wait for the ok to cross every single time but people should at least make sure their actions don't directly conflict with other traffic (like the difference between a car taking a right on red and straight up running a red). Presumably many of these same people who don't pay more than minimal attention to what they're doing when they're on foot or two wheels will continue to not pay attention to what they're doing when they're driving a car (hopefully they at least take their headphones out).

Making a city walkable is just a politically correct way of saying they're gonna make it harder for idiots to meet at high speed.

> If a driver doesn't have time to slow down and stop for a pedestrian, they are going too fast. It's that simple.

Take your circular logic and shove it up a bodily orifice where it doesn't easily or comfortably fit. If I wanted to get hit by a truck at walking speed all I have to do it time my commute to coincide with when the sun will be on the horizon and cross a particular street when all the lights are red but just before all the right turn arrows turn green. After about a week or two doing that I'd probably get hit.

Every two party accident has at least two parties that could have done something different that would have prevented the accident. Accidents are fairly diverse in their circumstances. Just assigning blame to one party by default is an exercise in bad policy.
You say that as if there are not millions of developers using multi-monitor setups already.
A few years ago I wrote an BitTorrent client in Python 3.5 to get to know asyncio better.

Maybe those blogposts are still of use to somebody:

- http://markuseliasson.se/article/introduction-to-asyncio/

- http://markuseliasson.se/article/bittorrent-in-python/
Nice keep us updated, I've got one with a dodgy battery which is dying to be used for a project like this.
How about reconstruction a high-resolution mesh from pictures/video? The best I know yet is to use patch-based reconstruction of a depth map and feed them to floating-scale surface reconstruction, or a similar patch-size-aware poisson-style mesh generator.
Is there any code handling the depth-map reconstruction using deep learning which you know of? Feeding it precise camera parameters/un-distorted views as well as precise locations of these views with some known-matching points (artifacts of previous processing steps) is not a problem. Even pre-selecting only somewhat well-matching views is not a problem, as that is likely better done out-of-core anyway, due to the size of datasets where nice things become possible (e.g., capturing a small part (100 * 100 m, 5 stories, or equivalent surface area) of a neighborhood in sufficient precision to max out the resolution of likely all VR headsets you can get for this year's Christmas).

The current outlook from what I found to reconstruct such depth maps is bleak as far as speed goes, with the alternative being a drop in density/resolution too low to be useful (capturing is cheap but not free). If there is some magic based on deep learning I'd like to forgo having to split part of these algorithms to e.g. an FPGA or so (the parts that sort and arrange the patches that should be hit with brute-force number crunching), as it seems from what I understand about them that it's near-impossible to decide these arrangements efficiently on a CPU or even GPU, seeing how sparse the math and how dense/wide the branching is. (I'm considering feeding lists of to-be-compared patches to a GPU and the results back, the technique is somewhat similar to Dijkstra's algorithm for deciding in what order to compare and what starting values to use in the iterative optimization of depth and surface normals, and that branching currently takes 80% of CPU time without the actual number crunching even using vectorization, combined with GPU speed I expect two magnitudes of improvement as a minimum, and hope for closer to three)
This isn't the case in Amsterdam, bicycles and cars will stop for you you or weave around you (depending on the case) if you're on a crosswalk.

What they aren't going to do is stop for you just because you're standing on the side of the road by a crosswalk and you vaguely look like you might possibly maybe intend to cross the street.

With the amount of tourists in the city that's only going to result in a deadlock (particularly on a bicycle) where you're waiting for them to go, and they're waiting for you.

Just start walking across the crosswalk in a predictable manner and maintain your course and heading. It works.
>Would I be willing to buy a cracked piece of software?

It doesn't matter if you would, it matters if the general public would. And all you have to do is look to China, where more cracked copies of windows are sold every day than legitimate copies. The only reason that doesn't exist here is because it's almost impossible for the average consumer to buy a cracked copy. If they were available at every corner store the average person would make that choice 9 times out of 10. And if they'll take that risk on the entire OS, they won't bat an eye at a rom.
The very minimum admissible speed of 3G is 144kbps (barely faster than a 56k dialup, this is what we're talking about). The hn site should load in less than 3 seconds even on such an unrealistically slow network.
I feel exactly the same way. Word processors are a muddle of a middle ground, where you are forced to manage styles and layouts with substandard comtrols, and get none of the dependable benefits of structured text.

I think word processors are just entrenched. People expect this degree of control, and don’t know how better things can be in either direction.

Fun fact: the original Google word processor wasn’t really much of a word processor. It was more akin to LyX, where users chose the type of text they were working with, and then IIRC, CSS styling was applied. But then the pressure to be a “real word processor” got the better of them, and it got rewrote as the thing it is today.

Frame Maker... now that was a nice take on document creation.
> But removing the necessity of managing scaling, individual instances, and OS / software patching is significant.

With AWS (and other cloud provider) APIs and tools like Packer, these difficulties are vastly overstated.

Building VM images is just another step in the CI/CD pipeline, and patching and deploying a zero day fix becomes "kick off the CI/CD pipeline". You can even do automated unit testing of an image with tools like Inspec.

Scaling is an API call to change a "desired instance count" value (if it's not already automated), and complex problems with any individual instance can be resolved with STONITH (terminating the instance).
Lambda is often the way to go, but there are a couple tipping points where it becomes less appealing:

- When you start having to spend a lot of time working around its limitations. (As is the case with all managed services.)

- When the sum of its parts create a distributed system whose complexity costs you more in productivity than it gives back.

Performance limits will get better with time. The complexity cost is more difficult to predict. Hopefully it will improve as best-practices emerge and tooling gets better.
I checked out the Toyota Mirai - it does indeed use hydrogen gas cylinders from what I can tell. So this research is targeting simply the ability to transport hydrogen.

Ironically, the ships that carry all that ammonia to Asia almost certainly used fossil fuels and who knows what the carbon footprint around building the membranes for the hydrogen transfer is like
This sounds really cool. I'm trying to use anki for more math oriented concepts. The 1,2,4,5 points you make are very small and simple, but I have a question regarding point 3:

Aren't proofs going to be absurdly long? You might have a one sentence question, but it demands a 5+ line proof. That takes the longest to review the card though. I almost want to say a multicloze statement is better here, to prove individual parts of the proof. But then you get way too many cards, etc. It seems to contradict best practices of what most anki practioners emphasize.

https://math.stackexchange.com/questions/2111662/prove-compa...

"Prove that a compact set in metric space is closed" seems to be 5 or so major steps involved.

I suck at proofs and find that math is a really big weakness I have. I tried using anki for mostly math, but I still haven't reached that pivotal point where everything just makes sense.
Wow, this actually sounds amazing. Not magical in any way, nor a real leap, but still... It's like looking at the first iPod. Looking back, it looks awfully retarded, but back then, it was the first primitive iteration of a paradigm-changing technology.

Personally, the only "convincing" I need is price, weight/convenience, and software. All will come in time, I'm certain. Eventually, these have a real chance of being way better than phones/laptops, e.g. they'll likely use much less battery (as the "screen" is smaller).
Purely anecdotal, but I have a friend who went to veterinary school. The school had a literal class teaching all vet students to use IBR forgiveness to get their debt discharged.

It's not quite as abusive as what could have happened when student loans were dischargeable in bankruptcy- it takes 20 years and you're taxed on the forgiveness- but I thought it was quite perverse that the institution charging towering sums of money is teaching the students in blanket fashion how to avoid paying it off.
Being held before trial is pretty much never interpreted as wrongful imprisonment, even if the suspect is acquitted.
"The law, in its majestic equality, forbids the rich as well as the poor to sleep under bridges, to beg in the streets, and to steal bread." -- Anatole France
>The best you can do is call the police and say "this mob slamming at the doors make me fear for my life. If you don't get me out of here I'll call my embassy and say there's a hostage situation".

what is the american embassy going to do? call in seal team 6 to rescue you? the worst that will come of this is some strong words from the secretary of state.
> I think too, you know people from work will see it and you also worry if it may affect the way they view you professionally.

This is sadly the case for many, depending on the company culture writing should and can be encouraged.
in this model there are only two focal planes as far as I know.