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Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by mrfusion on Thursday January 14, 2016 @04:53PM (#10904856)
That really sucks. I hate the whole attitude that you need to be a Ph.D. To do research.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by criley2 on Thursday January 14, 2016 @05:04PM (#10904983)
I mean that's what Ph.D's do in most fields, the whole point of getting a Ph.D is so that you can do research in that field. Learning how to write well researched white papers that can withstand peer review.

Prior to that, you can do some research as perhaps with a Master's or as a graduate student, but usually you're assisting on a Ph.D's project.

The process of getting a Ph.D in many fields is basically the process of learning how to research and report your research.

So the idea of limiting high level research tools to those who've proven to be capable of high level research isn't that ridiculous to me.

If you want to research for a living and report it, is it so ridiculous to ask that you train traditionally in researching and reporting?

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by ACow_Adonis on Thursday January 14, 2016 @06:33PM (#10905673)
I will only speak for myself and people like me.

Many of us have deliberately chosen not to go the Masters/PhD/Academic route because of how broken/backward we believe the academic system to be, and that we can have better access to both research, learnings, materials, methods, and just a general quality of life, both materially and intellectually, outside of it.

That doesn't mean we're not interested in, or aren't doing, research. Indeed, we believe we're often doing it better.

These edu/PhD requirements are incredibly frustrating, and there's no technical or intellectual reason they should exist: Only social, political and economic reasons.

I know you did not mean any offence by posting your comment, and i do not mean any by mine, but to answer your question:

"If you want to research for a living and report it, is it so ridiculous to ask that you train traditionally in researching and reporting?"

Yes, yes it is. Research should not be for a closed shop of inward looking, often archaic and relatively backward academic institutions.

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by criley2 on Thursday January 14, 2016 @07:33PM (#10906098)
>" and there's no technical or intellectual reason they should exist"

I disagree with this completely, and I described the objective and intellectual reasons behind it in my other post!

Very, very few people are capable of taking a post-graduate course-load and producing journal-quality research without any formal training.

It's become a trope to dislike academia and to make the assumption that it is incapable of producing a result that is worthwhile (all while most of us in programming make intense, constant fundamental use of functions, ideas, algorithms, systems, etc that are the results of PhD in Computer Science or academia in general)

The objective reason is that academia produces better researchers who are far better prepared to publish their results. The intellectual reason is that a system of learning statistics, experimental design, and a subject matter under the tutelage of a proven expert which requires the person to literally succeed in their job of researching and publishing before even being given the title PhD produces a very high rate of high level success.

>Yes, yes it is. Research should not be for a closed shop of inward looking, often archaic and relatively backward academic institutions.

IT ISN'T! Just because you're not a part of centralized, systemized education and can't access this tool doesn't mean you can't research.

You also don't have access to a NMR, or an fMRI, or any number of hundreds of others of tools that cost $100k - 1m+, but you can still as a layperson educate yourself and attempt to contribute.

But I think to assert that randos-at-home are the literal equivalent of the academic process and PhD's is beyond absurd, and that every man should have identical access to what earning an PhD earns you, is also absurd to me.

But when it comes to the best tools that cost the most and the best opportunities, those who are a part of the system will get those options. If you want to study medicine you can do that anywhere but if you're not apart of a med school getting access to medical cadavers will be difficult.

There is so much disrespect for institutions and what we as a people are capable of when we systemize. I understand the appreciation for decentralization and the FOSS model behind technology but there is so often a complete unwillingness to show any respect to any centralization at all, it's very strange.

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by hellameta on Thursday January 14, 2016 @08:46PM (#10906494)
Your PhD is obviously not in history. Academia itself would not exist if what you said was fundamentally true. The assertion to placate the layman with the response "still enough to educate yourself and attempt to contribute" is simply laughable. If you fear getting shitty research from people -- that's fine -- but I believe that the current journal system addresses that fear, or at least attempts to.

There was not really an assertion that "randos-at-home" are the equivalent of academics - only an assertion that they could and do provide great value again and again and again. Every goddamn century people come out of the fucking woodwork and shock the world; Ramanujan anyone?

With all that being said - I believe in the right of the data owners/distributors in choosing whatever 'licensing' they want.

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by Others on Friday January 15, 2016 @01:28AM (#10907604)
If I'm not mistaken Ramanujan received a PhD at the age of 29. Sure, he came from a non-traditional background, and did some amazing math before his PhD. However, it was only after he studied at University that his writing was clear enough to be published. That of course makes the parent post's point fairly well.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by nl on Friday January 15, 2016 @03:56AM (#10908056)
A better example might be Subramanyan Chandrasekhar, who won the 1983 Nobel Prize for work he did at 19 (prior to the commencement of his PhD program). Ironically apparently he was quite upset about this.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by hellameta on Friday January 15, 2016 @03:12AM (#10907915)
No. It doesn't. It was my error. I just need to switch out Ramanujan so you don't trip up on the small stuff. The point stands.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by knughit on Friday January 15, 2016 @10:11PM (#10914044)
What if ramanijam was a CS scholar? you would refuse Ramanujan access to this data until after he got into a school program which he would not be able to do without access to this data.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by ACow_Adonis on Friday January 15, 2016 @03:34AM (#10907993)
I will not try to debate the relative merits of academia, because good or not, the question is whether we should allow data to be available to people outside of those institutions or place restrictions on the data we are releasing that limit it specifically to academic institutions even when we've already deemed it suitable for release.

We are also not talking about whether the average joe is equal to the average PhD, but whether it is right to actively exclude those who are willing and able to contribute to research because they are not part of the academic institutions.

Let us be clear in this case that we are talking of several TB's of data, well within the remit of a setup an intelligent employed professional on a decent salary is able to set up in his own home with a bit of money, time and work. Odds are if someone is able to obtain this data and store it properly, they have already passed a basic competency barrier that suggests they are able to contribute.

Now, it is a common academic myth that universities have access to the best resources and abilities, and that those outside do not. But I, for example, have now been employed with several bodies...arguably/theoretically with more/as much money, data and resources as many universities.

I'm not going to comment on fMRI or NMR, thats not my field, but i'm not going to discount intellectually curious people's ability to gain access to tools/machines outside the academy, and i'm not even touching upon grey/black methods of doing so, which in computing can mean often that those outside academia can often bring more power/insight to problems than those inside.

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by jsprogrammer on Thursday January 14, 2016 @08:16PM (#10906358)
You aren't providing any reasons why anyone not blessed with the appropriate three letters should be barred from accessing this data.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by NhanH on Thursday January 14, 2016 @08:23PM (#10906398)
The dislike of academia - specifically of higher education post B.S - partly stems from the archaic admission process that strictly limit the opportunity for the majority of people to participate in it. You have to be doing the correct things no later than, let's say your junior year in college to be able to have a chance for a PhD at a top tier research university (less than top tier PhD and you hit the massive road block for tenure after your PhD, so it's almost the same thing).

There are people did the correct things early in their life. The majority of us make mistakes. How would even a mid-late 20s (young, by any account) good software engineer get through the gatekeepers and get his PhD? There was even a thread on HN a few days ago asking about the exact question.

To put it another way, it's not that we don't want the training. We don't have the option to do so (at least in the traditional way).

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by cinquemb on Thursday January 14, 2016 @11:35PM (#10907227)
As someone who doesn't have a degree that gets contracted to work with/help build (hardware/software) such tools like EEG devices and fMRI's to make them usable for people with PhD's where most don't really understand the physics behinds such systems and having seen first hand how bastardized the academic process™ has become, its laughable to think that just because things may have been one way in the past, means that it will continue to be the way in the future. So much waste, which means so much opportunity…

>You also don't have access to a NMR, or an fMRI, or any number of hundreds of others of tools that cost $100k - 1m+

I call bullshit, because if you think outside of the box and have a friend who has access (which many people on HN probably do know someone who does), you can always jump in on their pilots in exchange for whatever works for you both. But outside the box thinking is definitely not apart curriculum for most researchers… unless such was prescribed in the literature lol

>There is so much disrespect for institutions

Damn right, but doesn't stop them from trying to co-opt a generation after having loaded them up on debt to feed the gravy train, and I don't see why individuals can't do the same to institutions.

>…and what we as a people are capable of when we systemize.…

People are not limited to existing institutions, we can seek beyond.

>I understand the appreciation for decentralization and the FOSS model behind technology but there is so often a complete unwillingness to show any respect to any centralization at all, it's very strange.

Here's a hardware/software FOSS project[0] of a bunch of different people from many orgs and some without for electrophysiology research, and this stuff is just the beginning once all the contributors (and others like them) realize they can pursue their other interests in life with out constraining themselves to the academic process™.

If anyone in the boston/prov area is interested potentially doing some software/hardware work or want to connect more to stuff like this and has a software + mathematics + physics background or side interests and not involved now, you can contact me at my username at NSA's favorite email provider (gmail) :P

[0]https://github.com/open-ephys

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by stfu on Thursday January 14, 2016 @06:57PM (#10905870)
But if you understand how the system works and it seems not surprising that you will face tougher challenges. I am not sure in how far this is different from rejecting the notion that a driving license is necessary to operate a car. You can certainly learn how to operate one yourself and be really good at it. But if your are a car rental company and want to reduce your liabilities it seems reasonable (but probably not fair) to let only people with a driving license rent one.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by satyajeet23 on Friday January 15, 2016 @02:35AM (#10907809)
I second that.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by nl on Thursday January 14, 2016 @11:21PM (#10907167)
I mean that's what Ph.D's do in most fields, the whole point of getting a Ph.D is so that you can do research in that field.

Um. Are you arguing that one can't do research without a PhD? I'm fairly sure that isn't true[1].

The famous Paleoanthropologist Richard Leakey doesn't even have a college degree.

I believe that Fabrice Bellard doesn't have a PhD either.

[1] http://lemire.me/blog/2009/02/05/skip-the-phd-go-straight-to...

Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by barry-cotter on Thursday January 14, 2016 @06:56PM (#10905853)
Yes, because only people who want to do research for a living should be allowed to do any research at all.
Re:Yahoo Releases the Largest-Ever Machine Learning Dataset ... by kingkawn on Thursday January 14, 2016 @05:25PM (#10905192)
Yes but then we only find what we've been taught to see for the sake of institutional structure and wonder why life isn't more inspiring.