tariqali34

The next step is to generate the article itself.

>I really do think that there is a very important distinction to be made between what intrinsically makes people who they are and what is just their opinion, a matter of choice.

I really don't think people actually choose their opinions. Humans' opinions are affected by a wide variety of different conscious and unconscious stimuli, such as culture, socio-economic background, and even genetics. Humans are illogical, and will likely post-hoc rationalize their biases rather than logically thinking up an ideology.

For example, you may be religious because you sincerely believe in it, or because you just happen to grow up in a religious family. Or you may adhere to a political affiliation because you sincerely think it was a good idea...or because you live in an area that shares that same political affiliation and associate with friends with that political affiliation. Or because some celebrity endorses a political affiliation and so you follow that celebrity and so on and so forth.

Assuming humans are fully rational beings is problematic (and damageable), and it's better to provide protections than to take them away just because your own bias makes it seem okay to do so.

Nah, it can handle the Internet just fine. It just can't speak on the Internet.

And I think that's a pretty good compromise that I'll accept. I could also suggest a manual deletion process as well in case you accidentally released security credentials or something very private that really shouldn't be open source. (Manual in the sense that you have to send an email to tech support and wait for them to respond...)

"If the software is open sourced, we can legally continue to redistribute the software even though author may not want us to."

Right, you can legally redistribute the software, but can you ethically do so? Some people have complained about the bad precedent set for allowing left-pad to be reuploaded again after it was deleted, and the reason they complained is because the developer has lost control over the fate of his own package.

These people can't complain too loudly, as the author in question did indicate that he was willing to give ownership of his npm packages over to someone else. But you could easily see a situation where a developer would want his stuff deleted and not be accessed, period. Why should this request be refused?

The idea that the developer has lost all moral rights whatsoever to his/her work just because they attached a LICENSE text document feels wrong to me. Just because a license says you can 'do whatever you want' doesn't mean you should do whatever you want.

Actually, since Red Hat is a public company, its "market cap" valuation is actually at $13.28 billion. The article merely claims says Red Hat has made $2 billion in revenue. That being said, the company does seems overvalued (P/E ratio is 70.62).

It has a positive EPS of 1.03, which is another point in its favor (it means it's actually turning a profit).

Source: http://fortune.com/company/rht/

I don't believe in "education for its own sake", though that may be because I still associate it with the "publish or perish"/mindless research attitude. I still like learning stuff for fun though, and I may eventually come around to supporting "education for its own sake", but I have to first believe it, and I cannot do so now. Practical knowledge is still better than theoretical knowledge.

I still think the solution lies outside "old" academia, though on a different track that can also run parallel to the "vocational" track of apprenticeships/bootcamps. Academics can simply publish their findings online, via comments, blogs, and open-access academic journals...and can also attempt to teach their ideas (also online). Even research grants could be replaced by Pateron and crowdfunding. A system where academics and educators slowly promote their ideas and gain followers/supporters is one that has the potential of being slightly more just than the old system.

But "should" does not at all mean "will". We live in an imperfect world, and must deal with reality..or find some way to change that reality. Maybe the real solution is for us to create a "new academia" to compete against the "old academia".

>>" Freed from the pressure to teach industry-ready but highly transient skills, universities could be preserved as places to learn deep, ready for students who have a knack for academic work, or have become interested in the theoretical aspects of their practical work."

As a person who was immersed in academia (even to the extent of writing a peer-reviewed article and serving as an adjunct college instructor for a period of time), I had a slightly negative view of academia for that reason alone. It appeared to be a self-referential entity, where the only people reading your research papers are other researchers who are only interested in writing their own research papers. The 'outside world' doesn't quite respect your theoretical research fully (as you are not a productive member of society actually helping out other people), and the academic world itself doesn't quite care enough about you either (too obsessed with promoting their own theoretical research).

I think universities need to be more leaning towards vocational skills, or to make their research more "vocationally" relevant. That way, laymen will actually see a use for academics, instead of seeing them as prestigious eggheads. Theory has its place, but it has its place as a part of a vocational curriculum. Nothing more. I also support even more measurement of the quality of education, because without any level of accountability, you do not know whether what you're doing is actually working. I can write and teach all I want, but if I'm not sure if what I'm doing actually have any impact in the long term...then what's the point?

I left academia because I knew that adjuncting would be a dead-end job and that the administration prefers to hire them over that of full-time faculty, but it doesn't take a genius to suggest that low-paid teachers are definitely going to have a negative impact on a future curriculum, even on the measurable metrics. In fact, it is possible that adjunct instructors provide the "breathing room" that allows for the full-time faculty to continue to churn out research papers (although their replacements may wind up being more adjuncts). The fact that academia itself doesn't want to hire its own children suggest even further that academia needs to focus on vocational skills, so that academics can transfer out into a "post-academic" career.

As for me, I am still interested in the "theoretical aspects of [my] practical work". Maybe I may one day find a use for it. But I am unlikely to find an outlet for it within the the insular and corporate nature of present-day academia. For now, theory is just a hobby.

I think most people would probably not like your approach, and think of it as way too sci-fi and idealistic given the limitations of current tools. They would suggest studying AI a lot more before you attempt to really think of anything. Things that seem easy can be hard, things that seem hard can be easy. And it's not clear that we will ever really recognize superintelligences...if we program something, then we know how it works, and if we know how it works, we'll just say "Oh, it's an algorithm" and not ever appreciate the extent of machine capabilities.

I do like how you handled "consciousness" though by redefining it to mean 'examine your memory and then learn from it'; artificial intelligence is really just one big word game and if you can change your definitions properly to something achievable, then you might actually achieve them. Then again, you actually have to do it and that seems more difficult than talking about it. Most people will likely disagree with your "consciousness" definition and will prefer a more vaguer version that would be impossible to be built...

My suggestion is two-fold:

1) Learn AI first and find out its tools and limitations. Struggle through those boring AI lectures, or see if you can find any GitHub Machine Learning libraries so that you can start working. Also, try some side projects where you use AI to solve real-world practical problems, before you attempt to figure out how to induce the existence of an AGI. I'd even suggest dropping the existence of an AGI (there's no guarantee it can even exist anyway) and focus on a specific part of AGI: inducing emotion or consciousness by itself might be "pretty cool", and if you can do that without needing an AGI, and be able to apply them to real-world problems, then people might even accept those algorithms as being valid (though they may avoid the pseudo-scientific terms we're applying to them right now).

2) Look at the "Mario Lives" videos[1], where programmers were able to successfully represent emotional states and conversations in an AI that plays Mario. May not match your ideas about emotion and learning, but it is a sign that you can do anything you want so long as you change the definitions of words to be what's practical.

[1]Video 1: Mario Having Emotional States - https://www.youtube.com/watch?v=AplG6KnOr2Q

Video 2: Mario Becoming Social As Well - https://www.youtube.com/watch?v=ltPj3RlN4Nw

Larry Tesler (source: http://www.nomodes.com/Larry_Tesler_Consulting/Adages_and_Co...)

"Tesler's Theorem (ca. 1970). My formulation of what others have since called the “AI Effect”. As commonly quoted: “Artificial Intelligence is whatever hasn't been done yet”. What I actually said was: “Intelligence is whatever machines haven't done yet”."

Any sufficiently advanced technology is indistinguishable from magic.

And while risking another AI Winter is no fun, it's possible that AI researchers are probably going to be sorely tempted to participate in the hype cycle as well. In fact, considering how much money is being poured into AI research, what is it to say that the hype has already just begun?

Many of these businesses may make better sense as "non-profits", out to improve the welfare of the general community and funded purely by donations. I'm not sure whether donors would appreciate writing fat checks for programmers/managers/etc., but it's clear that a "hockey stick" growth could lead to a immediate path to monetization (if people know your name, you can capitalize on it when you're doing fundraising drives).

Entirely so. Non-linear regression sounds like a tool that can be used without any ethical repercussions or philosophical angst about human obsolescence in the face of machine capabilities. It also sounds like a tool that anyone can use...either learn math or find a library that will do the (non)linear regression for you. I mean, you already heard about linear regression in high school, right? It doesn't sound as exotic as AI/DL either...

If the barriers to entry are low, then that means anyone can take advantage of the Power of Math to do Great Things(tm). Said "Great Things(tm)" might include humans trusting their models way too much and end up doing stupid stuff as a result of them, but people have been misusing statistics for generations and we haven't killed ourselves (yet).

Legacy software is successful software. What's the point of building a program that will be discarded after a few months because its users fled to the next big thing? That just means more lines of code being written overall, needlessly.

...until the computers shut down because of a simple power outage or an DDoS attack. Then the Luddists and their looms will definitely win. When you rely on technology, you rely on a single point of failure.

There's also the question of speed/efficiency as well. Memorizing a fact and utilizing muscle memory can be much quicker than Googling for Stack Overflow answers every day ("memory caching"). And the faster you solve one problem, the faster you can move onto the next problem.

Do remember to actually delete paragraphs though. I've seen long-form articles that were really just several short-form articles that are linked together by a listicle format. If I'm lucky, there may even be a few transition phrases or a narrative that would justify the listicle format.

All these articles may have been good if the writer wasn't so wedded to the long-form format and started deleting paragraphs. But since he was wedded to the format, all the reader sees is a rather meandering and dull piece. It's an example of the sum of pieces being greater than the whole.

>A site that mixes ads in content won't be popular for long (it's bad content).

But what if the site is the ad? For example, a lawyer's blog would have lots of blog posts about law, but the whole purpose of the blog is to advertise the expertise of the lawyer and encourage you to buy the lawyer's service. Or maybe an artist wants to showcase his portfolio of his work online, in the hopes of later securing juicy contracts or donations.

Or what if the site is simply a forum for people to "network" and self-promote themselves (i.e, LinkedIn, HN's Show Me, etc.) Those sites can indeed be popular (as people may go there to willingly consume ads), but they're all basically vehicles for advertising.

Uber has huge revenue. They have failed to generate a single cent of profit though.

I've ran a Paranoia campaign where the players were all High Programmers. Technically, the players could reprogram The Computer, but they usually refrain from doing so, partly out of fear of offending all the other High Programmers and partly because trying to reprogram The Computer require a skill check (with failure causing more bugs to be introduced into the system). Any programming that they do is rather subtle, to avoid raising alarm.

The end result is a rather byzantine situation where everyone (including The Computer) is plotting against everyone else, all being sufficiently paranoid.

Machines do not have to think or see in the same way as humans. To dismiss machine capablities simply because they do not resemble human intelligence seems hopelessly naive.

This library was originally created in 2015 by Mark Rickerby (maetl) and was used to generate gamebooks. I forked the project and enabled Calyx to write "data-driven narratives" (robojournalism). I hope to have my changes merge into the main Calyx branch, but in the meantime, I hope to get any feedback for this project...and maybe even have it be used by other people.

"I've said this to tons of people privately and publicly: entrepreneurship has become the new "I'm working on a novel". "

An interesting statement to mention. In the distant past, writing a novel would be seen as a rather impressive and lofty goal. But as the barriers to writing novels decrease, so too does the actual impressiveness of a novel.

As technology makes startups easier to create, startups themselves should begin to lose their luster as well.

But if a computer is able to do the same thing as a human does (answer a simple question with pattern recognition and sentence parsing), then the internal mechanism of how a computer does it seems like mere trivia/jargon rather than anything fundamentally important to intelligence. A computer may have reading comprehension without having it in exactly the same way that a human does.

But it's true that we do have a underlying world model by which we understand passages. And that world model is pretty essential if we are to answer more complicated questions. So since it's pretty clear computers can handle the "informational retrieval" side of reading, we should now be focused on generating a "world model" based on text.

>I think it is too much to call this "capable of basic reading comprehension". Surely, "simple sentence parser can answer reading comprehension questions" would be more correct?

We test whether a human have "basic reading comprehension" by asking them reading comprehension questions. If they answer the questions successfully, then we assume that they have this "reading comprehension" skill. Therefore, if an AI can answer these questions, then it must also have "reading comprehension".

Maybe these "reading comprehension questions" don't actually test reading comprehension, just pattern matching and sentence parsing. In which case, we shouldn't be asking these questions to anyone (human or AI). So what we need are new questions.

While the article is informative, it's also an ad for a recruiting agency, and the advice has to be interpreted in that light. Still, if this is the future of "native advertising", I like it.

Ideally, you will learn from a bootcamp how to self-teach yourself, so you would not need to spend more money on a second bootcamp.

This is how I would imagine the 'fierce shark' being programmed:

1) The "fierce" plugin is installed and immediately run. It is targeted on the shark sprite.

2) "Fierce" is an evolutionary algorithm. It will create several hundred generations of a shark, mutating the shark sprite in some small way. The shark's fitness is based on how 'scary' the shark is, and the 'scariness' of the shark is calculated based on a dataset compiled by children that rated how scary colored pictures were from a scale of 1 to 10. The evolutionary algorithm's goal is to maximize the fitness of the shark.

3) The final shark (with the highest fitness) is outputted to the user. It will look very similar to a normal shark, with some minor variations in color to increase the scariness of the shark.

What these people are doing is not impossible. However, the potential for so-called "leaky abstractions"[0] messing up the development process is very high. Programmers will likely be necessary, if only to ensure the abstractions are functioning well enough for non-programmers to use.

[0]http://www.joelonsoftware.com/articles/LeakyAbstractions.htm...

I accept your apology about being aggressive, especially since I may have been a bit too empathic myself (about work). The "lie" is about you saying that when work is done, people move on. I think the truth is that people say work is done so that they can move on, but work can never be done.

We do seem to agree on that point though, so I should probably retract your comment "lies". You're fine with people leaving 'projects' incomplete if they hate it...and I'm fine with that too. But work is indeed left incomplete, and that's why I made my comment.

If it makes you feel better, replace "employers" with "the open source community", and redefine pay to mean code/maintenance instead of money. I think my point still holds.

Honestly, I do agree that reinventing the wheel is rather meaningless and silly. But the problem is that other programmers and engineers don't. And I'm pretty sure there are some open-source Slack clones out there, so money isn't a motivation. People just want to work on reinventing the wheel. Hence, work that has to be done. I'm not going to dismiss people's hard work just because I find personally it worthless.

And no, I don't see problems ever being solved, simply because they just expand. I've worked on a couple of free open source projects, showed them off to people, and have got feedback from users of "Hey, it would be cool if [insert-feature-here]". And if I implement that feature, "Ah, thanks...oh, and add this feature too." More and more 'suggestions' pile up, which means more work.

>Just because you've only worked with engineers at startups making shitty products or bloated companies doesn't mean there aren't people doing work right.

You make assumptions about me that you probably shouldn't.