skysight-inc/HackerNews huggingface dataset:
Bag of words is an encoding method for converting some sequence of words into a long, sparse vector of word counts. The vector has one component for each possible word of the vocabulary, and if the count of word i is N, then you store N in conponent i of the bag of words vector.

If you think of these as sparse row vectors (the columns correspond to all vocabulary entries), then you store them as a matrix where you stack on another row for each “document” in your data set.

Later on when you get a new “document” at query time, you transform it into the same bag of words vector format, and then an inner product between the matrix and the query vector corresponds to a type of relevance / similarity useful for sorting into a ranked order of results.

In practical situations you have to work harder, because you need more units of text than just words (such as n-grams), and the raw term counts usually need to be weighted (e.g. matching a 3-gram probably means more than matching a single word) or normalized (e.g. longer documents happen to have more words, but that doesn’t mean they are more similar), and you need to account for results that are historically more popular or results that are newer.

It’s a very simple approach to document search, but it works well and there are extensions that utilize word embeddings or models that predict rankings of results.

Once you get a system running with the term-document matrix, it is a nice platform for more advanced experimentation and machine learning feature development.
I use Sublime Text to take all my notes. I then publish the markdown files I edit with GitBook as an online wiki.

wiki: https://wiki.nikitavoloboev.xyz

files: https://github.com/nikitavoloboev/knowledge
You make some good points. Concerning whether works should or should not be free, I'm not sure. I think people should get paid somehow. How to solve that problem is not clear to me.

What I've been observing, though, is people acting as if the software is free because copying is practically free. This happens all the time and nobody even thinks about it. Friends share programs, music, movies, pictures, documents and all kinds of data among themselves and they may not even realize the fact they're infringing copyright. I see my colleagues sending each other copyrighted scientific articles via messaging applications every week. Nobody really thinks about some journal's copyright, it's just "those people need this file and I have it, so I'll send it to them". Companies have been trying in vain to police this behavior for years. I don't think they're ever going to succeed. I think that's a sign this system is incompatible with current technology. What good is a law if you can't enforce it?

>It's like saying "gasoline should be free because it costs next to nothing to run the pump motor at the gas station".

I don't think this is the same thing. A more apt comparison to software would be "gasoline should be free because the pump is magical and can somehow duplicate existing gasoline, creating new matter in the process, and the cost is so infinitesimal we don't have coins worthless enough to pay for it unless we purchase a whole tanker's worth of fuel". I'm willing to bet that such a magical pump would drastically change how people perceive the value of gasoline. Even though creating that first volume of gasoline required a substantial amount of money, the magical pump can simply duplicate it endlessly.
> Can you write more about this here? What were your simple experiments.

It suffices to say I am not the listening party in my experiments. The subject doesn't even know he is the subject, initially. That, I presume, makes the experiment reproducible. It is also easy to find new subjects. See also the reply above.

> why haven't people looking for it found it out already, if they are simple?

Really, what people are looking?? The main purpose of my post is to get to know the field. Among common people ESP seems well known, but they have no wish to live under a scientific blessing/curse.

Second, ESP is literally part of how people, including scientists, work. Telepathy in particular seems to be science performed at life speed, with the model seeing a theory-space collapsing under evidence. Science is the result of this process.

Third, cultural violence decides who can (be permitted to) have a voice and who can't. Evidence by non-scientists is commonly discredited.
This projection is based on bad methodology that ignores mortality (and abandonment); the article obliquely references this by mentioning that people waiting will either give up or due before reaching the 151 year delay, but the fact that they will (and thus remove themselves from the queue) is why the delay will never get anywhere close to that long. Any model for the growth of the waiting period has to consider how people increase in likelihood to fall off the list by abandonment or death as the wait time increases, since that will affect the actual increase, and be an increasingly significant factor as the wait time increases.
Google could also buy the patent from Jarek. At minimum, they should have talked with him.
void * your_custom_allocator(size_t size)
{
// Handle your locks.
// Sanity checks, assertions, bounds checks, etc...

void * result = g_your_buffer + g_position;

// "Commit Memory" from your buffer.
g_position += size;

// Some more code...

return result;
}

Now, you can happily use:

BASE64DECODE_DecodeEx(..., your_custom_allocator, your_custom_deallocator);

What else do you need? You seem very disturbed by the use of the word "allocator" here, feel free to rename to whatever works for you.
Ask HN: Building a powerful ML workstation vs. consuming it via cloud providers?
I can't decide between buying hardware, assembling and building a "gaming" rig for deep learning applications, and consuming compute resources via a cloud provider? Which is a more economical method?

I'd prefer the latter since I won't have to worry about maintaining hardware, but I heard the prices are pretty high and there's slowdown on some AWS GPU instances? Thoughts?
Do you have a link to a previous submission with significant discussion? I don't see any at first glance.
Sublime Text, Google Keep, and I take a lot of screenshots.

Sublime Text - I use it to take notes when I can type on the laptop. Usually I write a lot of text (for example during a meeting). It's just text, no markdown or something like that, and no plugins.

Google Keep - For when I don't have the laptop with me. Since the data goes to the cloud, I often copy these notes over to a text file on the laptop, especially when I want to add more details.

Screenshots - I have noticed that for many things, like watching online courses, I take a screenshot of the part I want to take notes about, and then just organize the screenshots into folders. Works quite well because it saves a lot of time, and I don't have to watch out for typos.
I've always found that I get exceedingly warm when I sleep. Whenever I fall asleep on a bus or plane, I eventually wake up drenched in sweat. It's not from bad dreams or night-terrors; my body temperature just increases. I now wonder if it's specific to REM.
Haha, I laughed. But it can't be elitism if I'm literally asking to cater to the first sigma. It's more exclusionary than elitist.
The issue is that even if he managed to find a good developer to pay to improve some FLOSS software, it would come out very expensive in the end, first because the UI frameworks & libraries you get in the Linux world are nowhere near what you get on macOS, so the developer will require more time, and also because you won’t be selling that software later on to make any kind of money back since it’s FLOSS, and even when it’s proprietary and not FLOSS, the potential market for Linux software (let alone paid Linux software) is very small.
Womens' soccer gets the US' best athletes. There are plenty of stadiums open on Friday nights with 10-30K fans watching boys play American football. You would be lucky get get 100 to watch soccer.
Is δεν-είναι-διασκεδαστικό supposed to mean “defun”? That’s a different kind of “fun” right there (“fun” as in “I had fun at the park” instead of “fun” as in ”function”).
This paper is definitely quite interesting, but before this thread turns into a bunch of NN hate, here is another take:

"Do CIFAR-10 Classifiers Generalize to CIFAR-10?" - https://arxiv.org/abs/1806.00451

They use the same procedure used to construct CIFAR-10 to construct a new test set and test a bunch of state of the art results on the new test set.

They see a generalization gap, but the relative order of SoTA results remains (roughly) the same.

So, yes, test set validation is an overestimate of real-world performance of these systems, but progress on test sets is indicative of progress in real-world settings.

And to remember this in context, no-one is asking "do traditional computer vision systems understand images", because they were explicitly just looking at image statistics.
How many players on this year's English team play in foreign leagues? compare to other competitive national teams. In recent years the only other European national team with players who don't (can't?) play outside their own country is Russia.

Hypothesis: having some of a country's top players participating in leagues with different styles of play is helpful -- so as not to be stuck in and limited by an ever-repeating style and system of offense/defense.
"Solve the problem with what's in the room."—Edwin Land
One of the challenges here in the US is competition with other sports. My son played soccer but as soon as he was old enough, he wanted to switch to American Football. I've seen the same thing with other kids, to baseball, to basketball, etc. Girls have relatively fewer sports options and can start soccer at a young age, so there's a good feeder program to advanced levels there.

Perhaps it's the microcosm I live in, but I have hope for the future of US soccer. When I was a kid 30+ years ago, soccer was viewed with skepticism as a "foreign" game. Today soccer is thriving everywhere. In my community of > 30% Spanish speaking people, soccer is religion, and they are raising the profile and quality of the game from an early age. I see the US as simply in its infancy still in terms of players, coaching, and general interest in the game relative to the rest of the world, but, with things like MLS and the influx of predominantly Mexican immigrants throughout the West increasing the profile of the game on a localized level, we'll get there.
I’d say, women’s football has not been a well funded or highly persued sport in most countries until relatively recently, for instance in Britain women used to play different sports, hockey, netball, tennis far more. Likewise men’s hockey used to be quite rare here, but is more popular now.
> It also shows that you have no problem with learning a new code base and delivering code according to that project's quality standards.

If you can tell your employer you'll spend the next sprint or two fixing a bug upstream, good for you!

From my experience working with complex libraries, when you hit a bug or a corner case, it is probably not going to be an easy fix. There's a reason many open source projects are triaging low-hanging fruits for first-time contributors.
I think it's best if the client can handle the load balancing by connecting to a random server, and have some servers built into the source for bootstrapping. The client can know what to do if the connection closes and handle interruptions.
How does copyright handle that problem since copyright is automatic?
Sadly, genetics like height/physique can no longer be an excuse in the Men's game since there are players like Messi (even as an outlier). This contrasts sports like basketball and American football.

At least for the US, would it be possible to learn from their success(dominance over other countries) in baseball/basketball and apply the same structure to Men's football(soccer)? Is it possible that the genetic variance that the US has could be an advantage in the future? Or is it impossible due to culture? (Higher chance of making money in football/basketball, etc)
Paragraph 1 reminds me of a Yuval Harari quote from an article discussed here https://news.ycombinator.com/item?id=13905249

>The other major contribution, I think, is that the entire exercise of Vipassana meditation is to learn the difference between fiction and reality, what is real and what is just stories that we invent and construct in our own minds. Almost 99 percent you realize is just stories in our minds. This is also true of history. Most people, they just get overwhelmed by the religious stories, by the nationalist stories, by the economic stories of the day, and they take these stories to be the reality.
True at the local level, but go attend a PDX Timbers or Seattle Sounders match - eventually that excitement will trickle down.
The main cause of the generic brittleness of Neural Networks is probably in the way they are utilized. Biological neural nets never really stop learning. They slow down, even "forget" in order to restructure, but they change constantly. A static neural net in basically a snapshot of it's environment (training data).

Very interesting consequences for the ML field if my hunch has anything remotely resembling a kernel of truth to it.
Huh. If and when we see established, reliable transportation to the red planet, I wonder if we'll see a renaissance in fossil fuel industries.
Look to Iceland. The place is no bigger than a large city, yet they have now qualified twice for major finals. And they even beat England last time.

How is this possible? Well basically it's because football talent isn't just some randomly distributed gold-dust. People there decided they would make a bunch of indoor halls to train in, and they got themselves coaching badges. They supply a lot of youth players to different leagues in Europe.

Size and wealth are just poor correlates for the number of centres of excellence: places that by luck, tradition, or directed investment have the kind of people who pour their lives into training kids in football.

One other thing to note is that size can also work against a country. You can only have one national team at each age level, so only so many players can gather experience at that level.
Version control in academia
I'm finishing my first year in an empirically-based doctoral program (lots of applied statistics).

One thing I've noticed is none of my colleagues use version control nor strive to create reproducible research, say with Makefiles.

Coming from industry before my program, I assumed everyone writing code would use these tools.

For those of you with PhDs or experience in research-based graduate programs, is this the norm?
This is not an apt comparison. There’s a big difference between choosing a certain direction in a free market and complying with government requirements in a limited market. Apple has set the bar at a certain height for privacy in whatever markets they participate in, and that is clearly higher than their competitors in those same markets. The Chinese government has forced them to lower the bar in that specific market not by choice.

Why not just opt out of that market? Well, obviously it’s a huge market and that would be stupid, but also you can’t make changes if you don’t have a seat at the table. It’s a better strategy to maintain a presence there, be able to at least have a chance at influence, and already have a foothold if things change.
I may not know what makes a country good at football but for sure, I can tell a thing or two about what makes Pakistan amazing at making footballs! :-)
Actually, 3G will be shut down first because so much relies on 2G networks.

> Disabling 4G these days can often be counter productive for signal strength and battery life.

You can always have peace of mind with airplane mode or whole data disabled.
I use Joplin (https://joplin.cozic.net/). Allows me to have Markdown notes and a few embedded pictures synced across multiple platforms. Notes are encrypted and I can self-host them on a Webdav server. Fits my needs perfectly.

I tried a few others before and I think git and Typora or TiddlyWiki would do the job as well. Both solutions lack a bit on mobile platforms though.
What does your CV have on it? Are you highlighting technologies or are you showcasing business needs followed by solutions?

My resume style used to highlight the former because I thought I had to prove that I used technology x to solve problem y. I do mention technology where applicable but it's to highlight the business need and solution. I'm trying to show that I can pick up anything at full speed to solve real problems. That's what both of us do day in and day out or else we wouldn't have been employed at all until now. Having to prove that we're not imposters when someone clearly believes we aren't is really the most annoying part about all of it.

I'm in the same boat though around needing a solid GitHub profile even with what I feel is a very concise CV. At some point we do have to mark things as 'done' and just keep shopping out job opportunities until someone else believes us like our current employer.
What is the connection between swimming and heat? How did they even arrive at this hypothesis? Why would rats need to catch up on heating their brains, days after missing REM sleep?

The facts are interesting, the conclusion doesn't make any sense at all to me.
Also see all the work from Ingo Swann [1]

[1] https://en.wikipedia.org/wiki/Ingo_Swann
Implementations are ideas too.

The distinction does not make sense.
If more of the developers who work on the software I use had Patreons or similar, I would pay monthly. Until that day I'm happier with a lot of the free software that I can't even pay for, than I am with a lot of the software I could pay for.
The power to reason is limited in complex languages.
REM cannot be strictly necessary because I don't get any REM sleep (or so little it's difficult to detect) due to severe sleep apnea (AHI=148). Three different sleep studies (using two unrelated labs+doctors) produced very similar results. The hypnogram was always a narrow rectangle of rapid oscillations (λ ~= 25-35 seconds) between NREM stages 1 and 2.

Obviously this has caused harm, but it's difficult to isolate how much of that harm (if any) is caused by lack of REM when the dips in oxygen saturation could easily be the causing most of the problems.
While that may technically he the case, the USPTO has allowed the "application" of ideas to be so broad as to effectively be just a patent on ideas.

There are a million different ways you could implement a "one click checkout" yet the USPTO granted a "one click checkout" patent to Amazon. And countless similar parents exist today. (podcast patent, online shopping cart patent, a patent on making 'toast' and on and on)
Trump Threatens to End All Trade with Allies
> In principle, it’s all pretty straightforward. Of course, the devil’s in the details. I was quite surprised how much work was involved in getting it all working. Probably 3–4 months all up.

And that's why I built https://keygen.sh, for those that would rather not spend months building a licensing server in-house. I did this one too many times. :)
Marketing Pessoal E Produção de Conteúdo No LinkedIn
Well said. Do you think some sort of other patterning mechanism, like that used to identify songs (thinking the Shazam algorithm where there is more along the lines of making a "fingerprint" and comparing to the print) will help take us to the next level?

Neural Network architecture (sideways skyscrapers that get more focused as the network plays out) does not incorporate generalization much and this is sort of the point: a specific input data shall generate the resulting target, and any small variance would decidedly result in something different at the other end of the NN. Unless there were some way to incorporate a broad pattern on the data as it comes in... For example, run the NN, the NN shows results and also produces a fingerprint hash, now when you put slightly mal-aligned data into the NN, also provide the previous fingerprint result, and now (maybe) we can derive a device that will result in the same product and similar products within a range of the input data, to satisfy the case that the fingerprint stays true even when the data is slightly different.

Just some ideas on the topic, if we could solve pattern generalization where the viewing window did not have to line up perfectly with the perceived pattern, that would be very powerful; we would have the ability to measure unaligned states, but an algorithm that approaches this power also must exploit some natural phenomenon, such as quantum superposition, if we are to complete our iterations in reasonable time. Without some sort of preprocessing step, such as sorting (that can ensure algorithms run quickly) it seems difficult to try and make a real neural net that is significantly more than a very specific compressed archive.

What's really interesting is that as a stochastic process we could both generate two separate, functional, result-bearing neural networks (weights and layers) that achieved same or similar results while being completely different at their basis (in number of layers and the actual activation weights). And right now, there's no way to determine [elegantly] how similar our neural nets are. So, perhaps in some ways, the ability to compare neural network guts meaningfully will lead us to the ability to encode more elegant view ranges on data sets.
In OSS I tend to see the opposite. The more “passionate” developers tend to be passionate about some implementation detail (like respect for a particular standard, the Unix philosophy, Stallman-compliant licensing, etc) without giving a crap about the actual user experience in day to day usage.

I see more passion in paid software in macOS when I see a beautiful UI because it shows that the developer actually wants me to use and enjoy his creation day to day.
Lifestyle plugins for BitBar – Put anything in your Mac OS X menu bar
Angular Tutorial: How to use CSS loader in your Angular app (for beginners)
Windows goes something like this (there's no real straight line, feel free to add your own progression):

3.11, 95, 98, ME, 2000, XP, Vista, 7, 8, 10

I wouldn't call that a pattern.
Why are those two conditions mutually exclusive?
Minimalist libraries as in the op are generally done out of a fear of libraries, as if libraries take away control from the programmer and make the resulting program lesser. Minimalist libraries in npm arise out of a reverence towards libraries, as if something being implemented in a library is superior to an equivalent homebrewed implementation.

When the OP says a library should ideally have one function, they mean that the one function should do the brunt of the work, but leave any setup and takedown to the caller. When a node lib has a single function, this is because you are expected to import another lib for other purposes (eg left-pad for left padding, right-pad for right padding, rather than a single, generic pad library).
This is probably the fifth or sixth trough. The problem is we spend too much time trying to brute force engineer our way forward when we should spend more time reverse engineering the salient properties that give rise to biological intelligence. Someone will invariably say that planes don’t use bird wings, but both birds and planes relying on the laws of aerodynamics and we need some kind of similar theoretical framework for computational intelligence—reverse engineering is the shortest path forward.

There are a few moves in this direction but without a better framework for computational intelligence, which we can get to faster through reverse engineering, we’re going to keep hitting these walls. This road includes methods for artificial neurogenesis, genetic encoding of the developmental program at the level of neuron and axon driven by artificial gene regulatory networks (AGRN) evolutionary methods to evolve populations, and adversarial ecosystems for open ended evolution. Unfortunately none of these will give you a quick win....