skysight-inc/HackerNews huggingface dataset:
Here you assume that both engineering and politics are purely objective sciences, where one's cultural background is irrelevant, but that is true in neither case. The fact that silicon valley is mostly white men of a certain age and economic status has a big effect on what gets built, and what doesn't get built -- think about elon musk's obsession with tunnels and car transportation and disdain for public transit. Regardless how you feel, tht isn't just an objective rational problem, the fact that Elon isn't someone who has ever taken or relied upon public transit matters.

The same is true if social policy -- it's easy to look at the voting decisions of people without college degrees as "stupid" and "uninformed", but I would challenge you to think about how their actions are just as informed and reasoned as people in your demographic, they just come to a different conclusion because of their economic and cultural background. "Education" is often a proxy for race or class in political discussions. I would argue that policy (and engineering) is much more about values than knowledge -- is housing a human right? Is healthcare a human right? Should the United States acknowledge and repair the damages of slavery and systemic racism? Should we accept asylum seekers? Everyone may have compelling, reasoned arguments to these questions, but it is naive to say only college educated specialists have the correct ones.
>today our oil reserves are running low

This argument is not quite up to snuff because, as it turns out, only a tiny fraction of the oil ever can be made to come out. The truth is that even after the wells have been abandoned most of the oil remains stuck in the rocks that it started in. I found this out while wondering whether or not it would be possible to burn all of the oxygen in the air (it's not, sadly ;) )

Also the oil reserves are not really running low, if they were that would be a lucky answer to carbon control.
People misunderstand Microsoft. They look at how it dominates both home and business computing, and so naturally they assume that it must be equally competent at both. Now it is true that, from the beginning MS has been brilliant at figuring out how to make software useful to businesses.

However, when it comes to home users, that is not at all the case. What happened was when home computers started to take off, they were new and so potential users had no idea which of the many brands that were available were really good.

But then IBM came along and got into home computing and it had this reputation of being the king of computing, so everyone just assumed its home computer was best. and in addition people who had learned to use a PC at work decided to buy a similar computer for home use.

And so the PC became the overwhelming choice and dragged MS along with it, even though DOS and the PC architecture were quite inferior to some of the other choices. And then the GUI was invented by Apple, which is truly expert at making computing easy for ordinary people.

But then the smart phone came along, and MS stumbled there, so now MS has intelligently decided to focus on its real strength, business computing.
Poorly worded. And shouldn't have backed down. If it were me, I'd say something like:

> We're sorry. Due to pending legislation in the European Union Parliament, we will soon be unable to maintain this website for European users. Today, we are testing our block and giving a users a preview of what it's going to look like. We're sorry that this is interrupting your usage- we don't want that to happen either.

> There is still time to prevent this from becoming permanent. Click here to learn more about why this is happening, and click here to contact your MEP to ask them to please help prevent this from happening.

> Again, we are so sorry that we've had to block you today. We hope you'll help us fight to keep the internet open.

But then, I'm Canadian so most of my sentences start with "Sorry".
Not all software developers have been through a CS curriculum. Not all CS curriculums teach rigorous math.
I watched some of it.

So in France they took the most famous youtubers out there, and tasked them with creating 2 series.

Both were pretty uninspired derivative work.
You could see that there was way more budget than on these people regular videos, but that the whole thing was mostly a paycheck, not a passion project.

I don't think Youtube even has to produce any content to be honest.
No ads and Play Music ? That's already a great value proposal.

If on top of that you add a video streaming service which actually has a library that only grows (instead of a rolling one like netflix) and that actually contains different cuts of each films, bonuses, cut scenes, etc, I might be willing to just let go of Netflix and go with them.
Anyone who doubts this should read the book Legacy of Ashes
I’ve found myself unable to do even elementary maths recently just because I’m sorely out of practice. Hasn’t really affected my performance as a programmer. Wondering, what kind of math I could learn that would benefit me in my job?
> Other languages occupy still other places on the linguistic axis of “busyness,” from prolix to laconic, and it’s surprising what a language can do without. In Mandarin Chinese, a way of saying “The father said ‘Come here!’” is “Fùqīn shuō ‘Guò lái zhè lǐ!’”

The writer seems to have copy pasted the phrase into Google translate. The phrase ‘Guò lái zhè lǐ!’ is simply incorrect grammar in mandarin. I'm unsure of how accurate the rest of the piece is.
This is totally obvious submarine astroturfing. Christine is a paid shill of rilkef, whose VC fund lead investors drink the same brand of organic kombucha as Zuckerberg. Don't be fooled: flopnax, not rilkef, is the consensus way to do containerized federated blockchain service hybrid ML at web scale.
Storing 8k media is going to be very expensive for a common man.
My point is that we know for a fact that our brain doesn't work anything like a Turing machine. Can a Turing machine simulate a brain - as in, create intelligence like the one our brains expose? That's very much an open question, but you wrote as if it was an obvious conclusion.
Misleading title, should be changed to 'Why we moved from flopnax to rilkef and you should too'.
our brain is not doing brute force search
I use cc instead of make, and javac instead of Gradle fairly often for various purposes like debugging or experimenting. Is the js world different?
As a general rule, it's relatively unusual for methamphetamine users to get into fentanyl/heroin and vice versa. Two different scenes.

Now, there are always a few "garbagehead" addicts that'll use whatever you got, but that's not common in my experience, since opiate addicts chase calm, sleepy euphoria and meth/cocaine addicts chase stimulating, energetic euphoria. Different scenes, different personality types. Probably different genetics as well.
I hope the octopus went after the cameraman after that.
Words. On webpages. You have to trust.
Last week we tried to book a ticket for a visit next month. (They have a strict schedule). Unfortunately seems tours suspended until March 2019.
>modern civil rights issues

That is the most positive way I have seen somebody frame them. I guess they would even call themselves social activists...
Fair enough. All that I can say is that the people I've met have certainly been devout, but not to a degree as extreme as a scientologist.
Agree with everything you said. And I wish LeCun said exactly what you suggested.

On second thought, I wish I myself was always very thoughtful and respectful in responding to questionable statements :)
This looks really nice, from the preview content---I really like the approach of explaining the background assumptions of reading mathematical definitions and such. Ordered!
"Make Your Questions As Good As Your Answers" sounds like exactly the opposite of Spolsky:

> Some interviewees try to judge if the candidate asks “intelligent” questions. Personally, I don’t care what questions they ask; by this point I’ve already made my decision.

I maintain my belief that nobody in software has a clue how to do technical interviews.
> Hungry people tend to go get food

Sure, we tend to want to eat once we're hungry but when we go just a stop above hunger, meaning the desire or non-desire for sexual reproduction, then things get really, really complicated really, really fast. For example just the other day I was reading about a 92-year old guy who was choosing daily sex over him allowing his body to get physically better, while on the other hand we've got asexual 20-year olds from places like Japan who don't really think about sex at all. There's no way for a lab-made psychology experiment to make sense of our libido (or lack of).
Good point. And they do with native advertising. As a YouTube premium subscriber I still have to sit through (or fast forward through) sponser messages or put up with obviously paid for videos.
Putting on my conspiracy helmet and tightening it all the way, how can you prove that that's not the same as polling the Department of Constructive Mathematics about the law of the excluded middle? Every field self-selects for people who believe that whatever the field studies is actually possible to figure out, all the way from physics to Paranormal Studies. Someone who didn't believe that climate models could predict anything wouldn't make any.

Appealing to the authority of climatologists is not going to convince anybody because everyone who thinks they are authoritative already agrees that global warming is caused by humans...
I think the point here is that the satellites are not owned by the gov, but by a contractor, hence the quote about capital expense to operational expense. Everyone wants to be a service these days, you don't own it, you borrow it, etc...
Down an order of magnitude... from last year!

> Surveyors at 97 sites found only 20,456 monarchs compared to 148,000 at the same sites last year, an 86% decline.

I have no words..
I'm not the person you replied to but the Samsung S8 has that PPI

https://www.samsung.com/global/galaxy/galaxy-s8/specs/

> Galaxy S8 5.8" Quad HD+ Super AMOLED (2960x1440) 570 ppi
Over the last two years, I have witnessed many demonstrations of normal people totally failing to understand “group x tends to be more y” — “but”, I have seen many retort, “I’m x and not y!”, as if the statement had instead been “all x are y”.
Not sure what you mean by above, but happy to answer. First, I think you're referring most proximately to Marcus' paragraph including:

> And it’s where we should all be looking: gradient descent plus symbols, not gradient descent alone.

That's the most specifically defined proposal that I see in the article. It is a reasonable mission statement to fire up your lab or community about. It's also not something outside the ongoing deep learning discourse, and it's a direction I personally am excited about. There has been great work recently by DeepMind [1], for example, about using gradient descent to theorize about symbolic relationships.

However, the statement above is also nowhere near operationalized enough to say "agree / disagree" in any scientific sense. A specific model demonstrating advantages of the marrying symbolic and gradient-based reasoning (c.f. the one above) would open itself to productive discussion of its successes and failures. People have asked for this (including in the tweetstorm), but most weirdly Marcus seems to be responding that operationalizing a model or even a success criterion is itself a waste of time! Quoting:

> I actually think benchmarks are to some degree the wrong way forward, and have said that for two decades. People need to take a step back, and reflect on where things stand, rather than rushing into the next bakeoff.

I couldn't disagree with this statement more, and it brings to my biggest personal axe to grind about the "is this how we get to AGI" query: AGI itself hasn't been defined in a way that is compatible with empirical discourse. Machine Learning at a term in many ways exists to abandon "AI"'s association with AGI, because the community realized that focusing on success at specific, objectively measurable tasks would move them forward more effectively.

When people focused on AGI say that ML in its current form won't get there, my answer is: "It's almost tautological that we're going to need new methods to get to something called AGI, but we can't even discuss progress on it until you give a measurable definition".

I don't blame folks (including Marcus) for wanting to continue discussing AGI as an abstraction - maybe they will be the ones to find a good operational definition! But it's weird and unscientific to say people shouldn't continue work on other directions in the mean time, or to say that a specific technique is essential before either the technique or the end goal has been effectively defined.

[1] https://deepmind.com/blog/neural-approach-relational-reasoni...
because how else they would pilot their flying saucers to earth?

https://www.independent.co.uk/news/science/octopus-aliens-sc...
My wife and I are having the same discussion. We had a stretch where 8 of 10 orders were late, damaged, or clearly repackaged.

Buying from Amazon use to mean getting a legit product, quickly, and in new condition. Now it's a complete crap shoot what fake junk we're going to get.
That is something amazon really does i think. Think of the writing samples.
This article is dated 2008, it might be an idea to note this in the title
For how many femtoseconds should we worry in optimal circumstances? Can we get a metric on that?
There's ABBYY FineReader Engine CLI for Linux: https://www.ocr4linux.com/
I notice the goals when asking the rote questions posted by angel.co and others in the thread, while very sensible, differ quite a bit.

And many interviewers are less capable and just ask these questions because those are the questions you are supposed to ask. They make up a reason for them after the fact. Like so much of hiring, it seems a fair example of a cargo cult practice to which a few smarter interviewers have invented a tolerable use.

For example, in a workplace that shall remain nameless, the question "Tell Me About A Time You Failed" really was to naively see how badly the candidate messed up in the past. And for "Where Do You See Yourself In Five Years" there was one correct answer: "manager" even though there was no expected need.
I just use an ad-blocker and don't see any ads on youtube
I like this idea, although I do want to note:

> A serious bidder could bid higher than you on your own self.

At least I'd get my money back :(

But it's a great mental model.
Yeah. I've considered moving from Google Play Music to Spotify, but I don't know if I'm ready to deal with Youtube having ads on my phone and TV (I know that ad blocking is an option on my laptop).

The actual "Youtube premium" is basically a non-factor in whether they would keep me, although I'll admit I did really enjoy season 1 of Cobra Kai.
It's very common for a new perspective on knowledge you already have to enable breakthroughs in deriving new knowledge from it. In particular, imagining a person rather than a statistical abstraction will tend to activate useful neural wetware that simulates other humans.
Sometimes reality can make people feel bad, that doesn't mean we should try to ignore it. Lets take the cancer research example. Using this definition:

>"Precise definitions vary,[4] but features often cited as characteristic of hard science include producing testable predictions, performing controlled experiments, relying on quantifiable data and mathematical models, a high degree of accuracy and objectivity, higher levels of consensus, faster progression of the field, greater explanatory success, cumulativeness, replicability, and generally applying a purer form of the scientific method." https://en.wikipedia.org/wiki/Hard_and_soft_science

1) Producing testable predictions

--- The predictions are almost all vague, of the form "x will be correlated to some degree with y".

2) Performing controlled experiments

--- Maybe, but I very often see that proper blinding procedures were not used.

3) Relying on quantifiable data and mathematical models

--- Mathematical models are rarely used to make precise testable predictions.

--- There was some progress on this front from Armitage and Doll way back in 1954 but interest has largely fizzled out.

4) A high degree of accuracy and objectivity

--- As mentioned in #1 and #3, making a precise prediction at all is rare. Accuracy doesnt matter much if you predict vague stuff.

5) Higher levels of consensus

--- Not sure this should be here. "Hard" vs "soft" is a matter of the procedures used, not the results.

6) Faster progression of the field

--- Not sure this should be here. "Hard" vs "soft" is a matter of the procedures used, not the results.

7) Greater explanatory success

--- Not sure this should be here. "Hard" vs "soft" is a matter of the procedures used, not the results.

8) Cumulativeness

--- The more research that has been done on cancer the more complex things have gotten, to the point where now they say "cancer is many diseases". This is the opposite of what happens when you gain a cumulative understanding and figure out "natural laws" that make things easier to understand.

9) Replicability

--- Seems to be well less than 50% of studies can be repeated (see my links here: https://news.ycombinator.com/item?id=18578282)
15000 Golden Age Comics Available for Download
Any news about the pesticides killing off bees and butterflies? Have any been banned yet?
For non-speakers, ‘Guò lái zhè lǐ!’ translates to "Come here to here", which is definitely a bit awkward. Usually `Guò lái` is sufficient since "here" is implied, similar to how you can simply say "come" in English.
This is utterly incorrect. You can disagree with people without being rude.

You cannot call an idea itself insulting unless you yourself are a biased person. Ideas in itself are just statements with no malevolence intended. Only people can express malevolence.

I don't agree with him. But I see where he's coming from. A lot of biology is just observing behavior and documenting observations. It is very different from employing the scientific method in an experiment. It is also very different from trying to quantify everything. The line between hard and soft is blurry.
Mathematics isn't a science because it doesn't provide us with empirical answers. That's precisely the difference between physics and mathematics: the former tells us what is, while the latter only tells us what must be, given certain specific assumptions.

Or more succinctly: mathematics doesn't give us truths, it gives us consequences. The statement, "2 + 2 = 4" is not an empirical fact intrinsic to the universe. It's a consequence of our definition of natural numbers. It's considered a useful definition because (among other things) of its application as a foundation for engineering and the sciences. But many other useful areas of mathematics have essentially no basis in reality.
From the ToC, is the any reason there is no chapter covering probability/statistics? It has chapters for single/multivariable calculus and linear algebra, and all CS programs I know have all three, especially when there are some nice connections between them, not to mention how useful they are in other CS/engineering subjects.
Let’s face it he should be able to authenticate his identity
That was just transaction volume on the platform - I made ~$750 on that after my costs (charging processing fees). The $40k occurred within about a 3 month range after working on it for 1.5 years, and then as my burnout kicked in, volume fizzled out for the final 3 months I put into it before quitting.
At first, I thought it was because i * i == -1.
I planted milkweed in my front yard. These plants don't come cheap, between 10-20$ at the nursery for a young plant. I never was able to grow them from seed. Anyways, the plants did attract a few monarchs late summer/early fall. I counted two. I planted nine total.

I got a code violation warning last month for not mowing my front yard and having overgrown "landscape weeds".
Looks like no:

"No solutions, sadly, but maybe that would be a good idea for a GitHub repo associated with the book…"

https://jeremykun.com/2018/12/01/a-programmers-introduction-...
Diminshed Fifth
What kind of work do you do? For some types of development, basic knowledge of mathematics will take you reasonably far. Knowing more math opens up possibilities. For example, I recently found myself wanting to add features to some flight control software for drones. I wanted a return-to-home feature, which involved implementing a PID controller for gps navigation. I studied control theory in college decades ago, and hadn't used it for anything professionally until this year. Also, autonomous navigation requires taking vectorial inputs from sensors that must be rotated to the frame of reference of the drone (e.g. the accelerometer). I could not have participated in this project if I didn't have enough knowledge of calculus and algebra.
I PUT META WORDS ON THIS WEBPAGE ABOUT THAT WEBPAGE SO YOU HAVE TO THINK NOW.
Why don't they publish a paper anonymously? Hopefully that would at least work for cases where "everyone" knows it is bullshit.
in a project I worked on, we used tsc with msbuild to build our frontend.
Which two? Mali is a few hundred troops assisting the government. Not sure if that qualifies as an invasion.

Vietnam the most recent in 1979 and lasted for two weeks in response to the Vietnamese government attempting to annex Cambodia and Laos, both of which were Chinese allies.
I PUT META WORDS IN THIS COMMENT ABOUT THAT COMMENT ABOUT THAT WEBPAGE SO YOU HAVE TO THINK NOW.
You know, this is why I more and more hate interviewing.

I have enough passive income that I don't need to work. This year I have decided that every cent (after taxes) I make is going to charity. It was a promise I made myself a while ago and want to follow up on it. Tomorrow I am going (after talking with them) spend about 5 grand buying things a local association needs.

If you ask me where I want to be in 5 years I will only say to make more money than I do now. Much more. I don't have goals in my job. I don't want to be a PM or whatever the fuck I should say. I don't need this job. I am trying to do as much good as I can. For a while I was in the top 5% earners in my country (maybe even 3% but data is hard to get by). Now the only reason I work is to give my 'sacrifice' a meaning. When I stopped working because I didn't need to, I started to drink and be a lazy slob, I was drunk pretty much every day, so I use work to keep me in track, but I give every penny away.

I don't care about work. I am a fucking amazing developer. I had offers from top companies I refused as it didn't match my lifestyle (lets say 2 or 3 of the FAANG brotherhood). I just don't care anymore. If you pay me, I do my job, amazingly well. But stop asking this bullshit question and try to infer meaning from the answers. Anyone can read a blog and say 'to grow as an X and be maybe a Team lead/management/suck CEO dick instead of lower management dick'. It is all bullshit and you and me (and the rest of the fucking HN) crowd knows it
>"ML researchers (or any researcher for that matter) don't have time to go through a long form blogpost or skim through a GitHub repo."

I don't see why this would take any more time than properly studying a paper, in fact it should be quicker since the information is presented in the proper format (not translated from code to math/prose).
> I'm honestly baffled how anyone could want any higher res.

The may be some learned preferences in here. I will choose 720p or lower given an option. 4k and high fps look just weird for movies. I'm sure the next generation won't understand me here.
This combined with TypeScript (which seems to be on their roadmap), and property-based testing ala QuickCheck would be a serious toolkit for writing more correct JavaScript.
I META^(N) AND META^(N) IMPLIES META^(N+1) SO YOU HAVE TO THINK.... FOREVER.