drongoking

That's an insanely broad brush. The mainstream press includes the NY Times, The Washington Post, The Economist, The Atlantic, and NPR. Please explain how they fabricate narratives, how they destroy the lives of those who accidentally enter their crosshairs, and how they retroactively alter their archives to change history.

I'd expect your summary dismissal of the mainstream media from a Trump supporter. I'm surprised to see it on HN. So please elaborate.

"Direct connections to the KKK" ? Did you read the article or his statement? He was 17 and fell in with white supremacists after/during an abusive childhood. If you want to dispute this account, fine, let's hear it. If you want to claim Banjo is otherwise an evil company, OK, it may be, but that's a separate point. But claiming that this episode as reported constitutes a direct connection to the KKK, and implying it's ongoing, is off the mark.

Is this worth buying/borrowing if you already know programming languages but not Javascript? Or is there a better approach?

Chemistry, biology, botany, and geology are dead?

This whole article, and your agreement, rests on a false dichotomy. "Fallacy" implies learning about mental models is useless. No one said mental models replace experience any more than good notetaking can replace thought; but both are useful in thinking and learning.

I don't agree. Paisley is a well-known pattern type and some people really dislike it. "Shirt without paisley" is not a common request but its meaning is clear (if you do an image search for paisley you get lots of fabric images, so it's not like search engines don't know it.) I'd say the same for "shirt without red buttons." In general the pattern <article of clothing> without <feature> shouldn't be that difficult for search engines---especially since many are tuned for consumers.

"He developed a philosophy that assumed that the sun was the venerable source of all life, and since the coconut was the fruit that grows nearest the sun, it must be the most perfect food for people."

That may sound comical, but I think the reasoning behind some modern diets (e.g. Paleo Diet) isn't too different.

Mendeley and Zotero are both free, but both have storage limits beyond which you have to pay (Zotero is 300M, Mendeley is 2G). If you only store references and annotations you'll likely never exceed those limits, but if you use them as a paper archive you may. (I have a 3G archive)

Knowledge discovery used to be a big part of ML, and the KDD conference included papers on association rules, clustering, rule learning, interpretable classifiers, etc. In my experience, even with predictive analytics the knowledge discovered along the way was often as valuable as the final application --- although it's easier to sell a predictive capability than "we're going to find something interesting in your data."

My reaction too. They've reinvented genetic/evolutionary programming. They should probably read some of the decades of work that have already been done on it.

The word is commonly misused. What they probably mean is sympathy, but that isn't really right either. The correct word would be compassion or altruism.

But /altruism/ is a word that sometimes sets people off.

As opposed to corporate bureaucracies? If you think the free market magically makes everything efficient and free of politics and bureaucracy, try spending some time in a big company.

Remember this folks when voting for people who advocate for privatizing or de-regulating industries.

There's an odd jump in this narrative. PCA is indeed a great technique, but the essay goes from PCA to neural nets without explaining why. PCA was around for a long time before NNs and there are fast incremental ways to do it. Why bother with a million-weight NN if PCA will do the job?

At one point Microsoft would refuse to interview you unless you were their first and only choice. If you ever hinted you were considering other companies---interview over.

Probably all the 900-pound gorilla companies go through that period of extreme arrogance when everyone's knocking on their door. Until they're not.

I'm surprised it's taken this long. There is no peer review to arXiv. If you've ever reviewed for a conference or a journal (10-30% acceptance rates) you've seen the "raw feed" of submitted papers and you realize the average isn't very good. Many get rejected because they simply have a few flaws, but some are badly flawed (or just plain wrong) and shouldn't be published anywhere. ArXiv has no peer review so it's virtually the raw feed. I cringe whenever I see arXiv papers cited as if they were published work --- doing an end-run around peer review can't be good for science.

Any idea on how this compares with the other deep learning intro courses available?

> I actually do appreciate many forms of art, but I feel that many artist (that I know) are just a mixture of regurgitators and expert salesmen. They make something random, then come up with a backstory that makes it somewhat interesting.

I wouldn't call your relationship with art "appreciation". Sounds more like undisguised disdain.

Good answers.

(And I hadn't realized Apple was planning on getting rid of Python, Perl, and Ruby from default installs! Wow.)

Sure, but you can invoke nearly all languages (and write one-liners) at the command line, e.g.:

python -c 'import sys; f=open(sys.argv[1]);print(len(f.readlines()))' .zshrc

But I wouldn't recommend python as a good one-liner language. So the question remains, what is awk particularly good at?

As a long-time user of Prolog I didn't find the explanation so horrible. Unification is indeed like variable assignment in the constraint-satisfaction sense: bindings are not stateful. As for equality, I believe the author meant == rather than =, or more accurately the 'is' operator in Python and Perl. But maybe regular expression matching would be a better analog for Prolog's theorem proving.

Your statement 2==1+1 is (I'd claim) a weird case in Prolog. Unless you want to code the Peano postulates you need some way to do numerical calculations, and "2 is 1+1" does indeed work in the body of a clause.

Your mathematical explanation of Prolog's theorem proving is precise and correct but almost impenetrable to the average software engineer trying to "get" Prolog. Such explanations only make sense once someone already mostly understands what's going on, and hence aren't useful for beginners. As a first approximation I thought the OP's work wasn't bad.

This isn't "evolution in action" in any inevitable sense. This only happens if the consumer values up-front price over TCO. Admittedly, with emphasis on quarterly earnings, this is the path many companies have chosen, but it's not universal.

You mean like the .excel command?

"... causes them to accumulate output as Comma-Separated-Values (CSV) in a temporary file, then invoke the default system utility for viewing CSV files (usually a spreadsheet program) on the result. This is a quick way of sending the result of a query to a spreadsheet for easy viewing"

Arguing that physics students don't understand equations very well is a poor way to make a point about GPT-2. GPT-2 fails at a much more basic level, and that's Marcus's point.

Talk to a five year old for a while. The five-year-old's language may be crude but it shows basic concepts of a conversation, continuity, referents, basic causality, etc. GPT-2 has none of these. It regurgitates smooth language fragments because that's what it was trained on, but it exhibits no awareness that it's involved in a communication event with another being. Except possibly at cocktail parties, humans don't simply regurgitate words.

> it is astonishingly good at recognizing the _kind_ of answer that should be produced. The fact that it usually answers with a language here is a reflection of what it understands. And it behaves similarly for a whole range of different tasks. If you write a sentence that should obviously end with the name of a person it will give you the name of a person.

I think you're anthropomorphizing a fair amount. GPT-2 has memorized huge amounts of text and can, yes, generalize the characteristics of words that fill certain slots. To say that it recognizes the kind of answer that should be produced is implying agency where there is none.

The original author is right. GPT-2 has no idea what it's talking about. Play with it any amount of time and you'll realize this. It's more than "Eliza on steroids," but the impressiveness of GPT-2 comes from the style of its language, not the substance.

Isn't this sort of what Glib is getting at? Bringing higher level data structures and capabilities (extendable arrays, hash tables, heaps, etc.) into C.

https://developer.gnome.org/glib/stable/glib-data-types.html

You don't get Cello's macros, and it uses reference counting instead of invisible garbage collection, but you get a lot of fun high-level capabilities.

> So what really mattered was self-promotion, good timing, and luck.

Yes. He seems like someone who is good at self-promotion and networking. Well, good for him, but I think he underplays the role these have in his success.

> Why does the author have to present his life like one would in a fucking college essay?

I guess that's the self-promotion. And humble-bragging. Like this bit:

"I started working as a teacher in the countryside, but after invoking the spirit of their dead chief, they later annotated me the king of their village."

Sounds very interesting, but is there a more recent book covering similar material? This dates from 1957 and I suspect there is more to say about it now.

Sure, just not the abbreviation. "Having a read-eval-print loop running on the spacecraft proved invaluable in finding and fixing the problem."

I shared the reaction, "wow, must've been glacially slow"

I think this statement satisfies a working definition of irony: about half the audience is in on the joke, and the other half earnestly believes it. I guess that's also true of trolling. Kudos, I suppose.

Whenever I see AI used for something like this, right after thinking "our dystopia is here," I wonder how it could be gamed. An experienced interviewer can tell when they're being told what they want to hear; I suspect an AI could not. The AI ends up rewarding preparation and acting skills. And when you make too many hoops for people to jump through, eventually you find you're just selecting for those who are good at hoop-jumping.