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.
When was the last time you read a positive story on Putin in the NYtimes?
All those outlets are compromised expect maybe NPR. Eric Weinstein calls it the gated institutional narrative, it is on you you still consider the mainstream anything more than shadow of what they represented in the past.
Theres nothing positive about Putin because he is a murderous dictator. There’s nothing positive about Kim Jong Un or Orban or MBS either. The NYTimes’ journalistic integrity is not measured by positive coverage of dictators in fact if anything it’s the opposite.
* allegedly CNN removing the Larry King episode from Google Play with a call from Tara Reade’s mother
* implicitly or explicitly suggesting unrelated archive footage represents the story being reported (Italian hospital footage in a story about New York hospitals, firing range footage presented as foreign conflict)
* the my pillow guy, who retooled to support health workers being railroaded simply for standing next to Trump
* the sudden and nearly universal admiration for GWB
* NYT editing an article, without notice that originally claimed HRC implied the Russians were grooming Tulsi Gabbard.
I have a terrible memory for specific details, so those just the ones I can think of recently. I primarily listen to NPR in the car. Their bias is staggering. They present opinion as fact frequently, often misrepresenting parties in opposition.
"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.
He literally was the getaway driver for a synagogue shooting by a kkk member. I’m not sure it’s possible to be more directly connected to the kkk than that.
> "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.
"Claiming?" Maybe you didn't read this sentence properly with a pair of glasses:
In the article:
> Patton revealed that, as a 17-year-old, he was involved with the Dixie Knights of the Ku Klux Klan.
That is a solid indisputable fact written in history. If that doesn't sound like a "direct connection" to the KKK, then I don't know what is. Some may say he was still responsible for his own actions at the time during the Navy in his early adulthood even when he was still involved with white supremacists. With his statement on this, he has just taken responsibility for his previous actions and 'apologised'.
> 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.
Well I just stated a fact and didn't imply anything. Mind you, I think Option 3 is likely to happen because of his apology, but there are those out there that can be less forgiving... What do you think?
No because this is an introduction to programming using JavaScript. A quick look at the table of contents shows Part 1 teaches basic OOP, Part 2 teaches basic client side web development, and Part 3 teaches basic server side development using Node. Having read the 2nd edition of this book, I can assure that if you can explain what any of the 3 main topics described in this book are in a few sentences, then you have advanced well beyond this book being useful.
The chapters from 13 on are great for anyone as an intro to how JS interacts with the browser.
I agree with the other commenters that the early chapters would probably move a little slow for an experience programmer, though it is beautifully written and the interactive snippets are great, so you might still enjoy it if you don't mind skimming. Or if you know some languages but only have a few years of experience I would say beginner intros to new languages are still good. Eloquent JavaScript is a really nice overview of clean programming style in JS as well as the language itself.
Definitely NOT recommended for absolute beginners. I tried reading this as one of my first programming books and it confused the hell out of me. There are much better introductory books/courses - my recommendation is "Watch and Code - Practical Javascript" if you are an absolute beginner and want to learn javascript.
Eloquent Javascript is a good book now that I know more about Javascript, but please NEVER EVER recommend it as the first book for an absolute beginner.
Have to agree with this. I was just reading through to try to figure out its pitch, and was struck by this (early on): "To create a value, you must merely invoke its name. This is convenient. You don’t have to gather building material for your values or pay for them. You just call for one, and whoosh, you have it"
I mean, that's totally correct, but that's paragraph 7. It's way too abstract for a beginner to understand - and usually, if a beginner is getting lost in the first few pages, they're unlikely to make progress in the book (even though they probably could in this case, by skipping ahead a bit).
I skimmed through head first, it seems pretty good but similar to a lot of other books. The watch and code course is different and I just think it’s so on point for the absolute beginner, or at least how I like to learn.
With 20/20 hindsight, what I wish I had done is read through or watch one or two courses without any pressure, just get familiar with the topic, and don’t worry if I don’t understand things.
things start clicking into place after you’re exposed to this stuff a few times. My mistake was that I wanted to understand everything and didn’t want to skip ahead if I didn’t.
From my personal experience, I was not ready for this book when I was a beginner at took a stab at reading it. I had written in JavaScript before and stumbled upon this book through the Internet, and it demotivated the life out of me.
I am now about a year and a half of being deeper into the language, and I have finally picked the book back up again.
i think the point they're making is that many learners in a given field (e.g., undergrads) don't typically critique the textbooks for those subjects. it's as if all the knowledge therein is complete and accurate, and research happens at some amorphous fringe beyond the textbook knowledge. it's intellectually "dead" to those learners, not that the subjects themselves are dead.
That may (how shall we know?) have been the point they intended to make, but the statement we have to work with is: "Any field of knowledge that has been dissected into a taxonomy must be dead."
Is there some nuance of uncertainty in there I'm not picking up on?
The word "dissected" is doing a lot of work there. "Any" makes it, arguably, hyperbolic. Obviously we can't take too literally any statement about a field being alive or dead. Research is alive in these fields but pedagogy is mostly not.
Well,we can put a man on the moon with less computing power than we carry in our pocket, and that's far from the most impressive thing we've accomplished in a long long list.
> hn is probably not where we solve epistemic dilemmas.
The repulsion to things like logic and epistemology on a programming website isn't the type of thing I believe we should strive for or celebrate, but I certainly can't disagree with your assessment.
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.
fully agree with this position. Mental models are just that, models. they are abstractions of a particular classification of a thing, they convey information. they carry no guarantee of understanding and (in the odd cases given in the article) no guarantee that understanding winner take all markets means you would instantly be an expert at gaming them. You would hopefully understand the essentials of them and therefore recognise them when you saw them. It seems to be me that some are conflating these abstractions as in some way claiming to convey expertise.
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.
If he really believed that which grew closest to the sun must be the most perfect, he should have eaten plants growing on some mountain top, not low-altitude coconuts.
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)
To clarify, Zotero's storage limit is only for syncing of attached files. You can use Zotero entirely offline if you choose, storing as much as you want, and we also support WebDAV or linked files (which can be in Dropbox, etc.) for syncing files in your personal library.
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 paper [1] cites Koza among a total of 102 citations.
"An early example of a symbolically discovered optimizer
is that of Bengio et al. [8], who represent F as a tree: the
leaves are the possible inputs to the optimizer (i.e. the xi
above) and the nodes are one of {+, −, ×, ÷}. F is then
evolved, making this an example of genetic programming
[36]. Our search method is similar to genetic programming
but we choose to represent the program as a sequence of
instructions—like a programmer would type it—rather than
a tree. "
"[36]" is "Koza, J. R. and Koza, J. R. Genetic programming: on
the programming of computers by means of natural
selection. MIT press, 1992."
Same here. When I studied genetic programming, I was hoping that's where problem solving evolve from as it was flawless. But recent events prove otherwise which made me believe we are using the wrong tool for the wrong problem. Here is why.
When AI gets to 100% accuracy, the equation to find the answer becomes 100% accurate. We no longer have to run the AI with heavy resources and equation can be converted to an executable program. This modal of AI will save computing power, and uses resources smartly.
Example.
AI tries to find right equation to add two numbers.
You might not be familiar with how neural networks work. When training they do use a lot of computing power. But when running they don't. Yes, they still require some external boilerplate code to multiply the matrices, but you already have it and it's not heavy. So yes there is some convenience in program synthesis in a human programming language, but it is a small convenience, not a game changer.
If the solution program is sufficiently complex (as one would imagine it to be in non-trivial cases where we use AI, e.g. computer vision, speech synthesis, etc.), what makes you think the solution program is going to be more lightweight than running inference on an "AI model"? Futhermore, what guarantee do you have that the discovered solution is going to be efficient w.r.t. computation at all?
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.