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Re:Machine Learning Can't Handle Long-Term Time-Series Data by nabla9 on Sunday January 05, 2020 @08:22AM (#21961135)
This is clever crackpottery type brainstorming from a smart person.

The author has extremely grand set of connections he developed. It ties down Buddha, enlightenment, vipassana meditation, artificial intelligence, cybernetics, fractals and neuroscience. Nothing wrong with that, of course.

Creative thinker should have these kind of crazy ideas and connections every day or at least once a week. I carry with me a notebook that is full of them.

Most ideas die as 'premature babies'. They may be interesting to think and write down, but they are not fully developed and never fit together as well as you initially thought. Filtering and piking some of them to work with is important. Giving them up is the difference between crackpot and non-crackpot.

Forcing grand connections prematurely makes this crackpottery type. Sharing the creative brainstorm in an essay that does not try make up connections would be easier to read.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by scottlocklin on Sunday January 05, 2020 @09:52AM (#21961464)
>This is clever crackpottery type brainstorming from a smart person.

I think you're being too kind here. It's just crackpottery as far as I can tell. I agree with you though that it is the type of dumb idea that should die in a private notebook.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by scottlegrand2 on Sunday January 05, 2020 @11:55AM (#21962173)
Like so many of these rants, he doesn't actually demonstrate his ideas fix the problem, he just insists that they do so without proof.

Less thought-leadering, more actual results please.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by anst on Sunday January 05, 2020 @10:34AM (#21961652)
Yeah, stir some mysterious ideas, maybe someone sees there a meaning. Quite surprised with this kind of vague magical thinking coming from lesswrong (thought they were rationalists or something).
Re:Machine Learning Can't Handle Long-Term Time-Series Data by IC4RUS on Sunday January 05, 2020 @12:46PM (#21962610)
I was surprised too, but it appears that the post has negatives votes, so I take it that it wasn't quite rational enough for the rest of the community.
Re:Machine Learning Can't Handle Long-Term Time-Series Data by mcguire on Sunday January 05, 2020 @12:11PM (#21962290)
Are you reading the same article?
Re:Machine Learning Can't Handle Long-Term Time-Series Data by tgflynn on Sunday January 05, 2020 @09:34AM (#21961375)
The line between crackpottery and genius is a fine one. If blogs had existed in 1900 and a certain patent clerk had written a post on his ideas about clock synchronization somehow being related to electromagnetism, many would have dismissed him as a crackpot as well.

The questions this article relates to are among the most profound and difficult that human reason has ever attempted to confront. I think one should be careful in labeling such ambitious speculation as crackpottery just because it doesn't yet amount to a fully coherent and formally testable theory.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by throwawaymath on Sunday January 05, 2020 @12:11PM (#21962293)
Okay...but Einstein didn't write a blog. He published a paper for peer review. Some of his ideas remained controversial for decades, but he had a sufficiently mature, cogent and well-specified theory that he could at least work through hypotheses and publish results.
Re:Machine Learning Can't Handle Long-Term Time-Series Data by tgflynn on Sunday January 05, 2020 @12:56PM (#21962697)
He published that paper in 1905. Is it absurd to think that if the Internet existed in his time he might have blogged about his preliminary ideas before publishing a formal paper ?
Re:Machine Learning Can't Handle Long-Term Time-Series Data by throwawaymath on Sunday January 05, 2020 @02:06PM (#21963186)
Absurd is a really strong word. I will say that I really doubt he'd blog about his ideas instead of just publishing them, even on arXiv, because all the examples of groundbreaking new work in the modern era have been blogged about contemporaneous with, or after peer review of formal papers.

I'll also go further and say that, while there's a kernel of validity to your analogy, it's not the right analogy with which to deliver your overarching point. I don't think the publishing method for one of the most significant scientific advancements of the previous century is a particularly good lens for analyzing this blog post.

The critical content of this post is far below the threshold usually associated with an idea sufficiently well formed to be publishable. Einstein had a minimum viable theory before he solicited feedback; and when he did solicit that feedback, it was through what we'd consider orthodox channels.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by tgflynn on Sunday January 05, 2020 @02:55PM (#21963586)
What you say is true.

The main point I was trying to make was that given a speculative post of such breadth, which touches on such difficult issues as AGI, how the brain works and perhaps even the nature of conscious experience, and which makes some claims that are at least interesting, I think it's quite presumptuous to assert that these ideas are all nonsense without a deeper exploration of them. I certainly would not want to make such an assertion, despite being troubled by what I think are some inaccuracies in the author's description of certain physical concepts.

Now a secondary issue is that it is true that as far as I'm aware major scientific discoveries have typically been initially published in much more developed form and have thus been the work of a single individual or of a relatively small group of closely affiliated individuals. I'm not convinced however that this historical model of very small scale scientific collaboration is necessarily the only one nor the best one in light of modern means of communication.

It seems at least conceivable to me that there is a possible future in which the following hold:

* There is some kernel of validity in this author's ideas.

* A small number of other people find them intriguing and choose to collaborate with the author to further elaborate them.

* This collaboration leads to major progress in our understanding of one or more of the areas mentioned above.

For me the, admittedly very small, likelihood of such an outcome, justifies the author's post and its appearance on HN.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by gumby on Sunday January 05, 2020 @04:20PM (#21964187)
> If blogs had existed in 1900 and a certain patent clerk had written a post on his ideas about clock synchronization somehow being related to electromagnetism, many would have dismissed him as a crackpot as well.

That "certain patent clerk" was hardly working in a vacuum; not only was he building upon the work of others (e.g. Lorentz just to pick someone) but he had been in school with some of them and was in constant communication with them, as he was hardly the only one working on the problem.

This is not to minimize his brilliance (Special Relativity in particular has that wonderful property of being completely obvious once explained...but that you could almost see before the explanation but yet nobody had previously characterized) and the mind blowing nature of his three-paper year. But when published his work fell on fertile ground.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by tgflynn on Sunday January 05, 2020 @05:53PM (#21964778)
> But when published his work fell on fertile ground.

I'm not sure how fertile that ground was. It was still 3 years after the year he basically laid the foundations of modern physics before he was able to get an academic job.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by rad88 on Sunday January 05, 2020 @01:47PM (#21963062)
This is a general purpose excuse for any rambling theory posted online.
Re:Machine Learning Can't Handle Long-Term Time-Series Data by shadowgovt on Sunday January 05, 2020 @01:40PM (#21962996)
It is a fine line, but it exists. Results make the difference.
Re:Machine Learning Can't Handle Long-Term Time-Series Data by scythe on Sunday January 05, 2020 @11:51AM (#21962142)
To be clear, you’re not disagreeing that the author identifies a problem—you disagree (as I do) that “organized fractally” is not a meaningful phrase that can guide the development of new AI, correct?
Re:Machine Learning Can't Handle Long-Term Time-Series Data by mlthoughts2018 on Sunday January 05, 2020 @12:15PM (#21962327)
I do disagree with the author’s claim. For example, Bayesian ARIMA is absolutely a kind of machine learning model, and can do very well in some long term time series applications.

Posts like these usually want to create a strawman narrow definition of what is allowed to count as “machine learning” and the work backwards to say that subset of models can’t handle some type of problem.

Machine learning is just statistical modeling. To the extent that any kind of statistical modeling adequately solves long term time series inference goals, then so does machine learning.

Re:Machine Learning Can't Handle Long-Term Time-Series Data by NOT_A_ROBOT on Sunday January 05, 2020 @03:15PM (#21963730)
For the past 10 years, I have been called a "crackpot" by friends and family, but It never crushed my motivation.

I moved forward with 5 hours days / 5 days a week while keeping a full time job.

Today I am sitting on a serious "wealth machine".

We have to accept that 98% of human cannot "think outside the box"