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lamename

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On The Architectural Complexity of Neural Networks

arxiv.org
5 points·by lamename·25일 전·0 comments

Reproducibility and robustness of economics and political science research

nature.com
5 points·by lamename·3개월 전·0 comments

comments

lamename
·2개월 전·discuss
I mostly agree with everything you said. Do you feel the same way about code written by an LLM?
lamename
·2개월 전·discuss
Exactly. HN darling Paul Graham writes this way.

I find the constant critique of punchy style a bit tiring. It would be more productive for the grandparent to think about the content and state an opinion.
lamename
·2개월 전·discuss
The link in the article that is right near the words you're talking about links to a wikipedia page that says the book is from 2005. So I conclude it was 2005 or soon after
lamename
·2개월 전·discuss
Do you disagree with the point made?
lamename
·4개월 전·discuss
Not quite, but these help

https://poloclub.github.io/transformer-explainer/

https://youtu.be/wjZofJX0v4M?si=gT8Zlz1IY14KV_ju
lamename
·4개월 전·discuss
So far i really like what it does for the example articles shown. I want to test it on 1 or 2 articles I know well, and if it passes that test it's a product I'd totally pay for.
lamename
·4개월 전·discuss
I tried to upload a 239 KB pdf and it said "Daily processing limit reached".
lamename
·5개월 전·discuss
I generally agree with the broader point you're making, but I also think there's nothing wrong with pointing out how messed up it is that that's the reality of the choice. The whole point of improving society is to eliminate this kind of dilemma
lamename
·5개월 전·discuss
Maybe. Those could be the case. But ignoring all confounding factors, this phenomenon is possible with numerical experiments alone. One of the meanings of "the Law of Small Numbers".

Basically, the possibility that the small study was underpowered, and just lucky...then the large studies with more power are closer to the truth. https://en.wikipedia.org/wiki/Faulty_generalization
lamename
·9개월 전·discuss
I agree with most everything you said. The problem has always been the short-term job loss, particularly today where society as a whole has resources for safety nets, but hasnt implemented them.

Anger at companies who hold power in multiple places to prevent and worsen this situation for people is valid anger.
lamename
·9개월 전·discuss
As much as I like the article, I begrudgingly agree with you, which is why I think the author mentions the physical constraints of energy as the future wall that companies will have to deal with.

The question is do we think that will actually happen?

Personally I would love if it did, then this post would have the last laugh (as would I), but I think companies realize this energy problem already. Just search for the headlines of big tech funding or otherwise supporting nuclear reactors, power grid upgrades, etc.
lamename
·10개월 전·discuss
In my experience in neuroscience it even differs widely across programs/universities. Some good professors care about giving good talks, and if you're lucky it becomes contagious in the program. Others think less of you if it's clear, some are too naive to realize obscurity is not a virtue.
lamename
·10개월 전·discuss
Yeah, but still "scary" because you have to be really careful to not fool yourself and pay attention even with those algorithms. For example, a good demonstration with tsne https://distill.pub/2016/misread-tsne/?hl=cs
lamename
·작년·discuss
Wow a sane person among all the hype. Great to see you!
lamename
·8년 전·discuss
Agreed. But I interpreted part of his point to be: seek out the perspectives of others to help you notice new details.
lamename
·8년 전·discuss
Excellent points and very true to my experience. I like this. I like it so much I'm wary of it being the last word. Accounting for details & getting perspective elsewhere is incredibly important for solving problems.

But with details alone in mind it's easy to fall into the trap of "there must be 1 more detail I'm missing" ad infinitum.

If you do anything where you have to solve problems in a fixed period of time, it's important to decide when to pivot to a new, more productive problem (depending on the scale of your problem and freedom to change).

Take this advice or learn it the hard way.