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Ask HN: What's the best paper you've read in 2020?

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Re: Ask HN: What's the best paper you've read in 2020?

#151

Post by checkyoursudo »

sillysaurusx wrote: post #147
checkyoursudo wrote: post #146

I think one of the most interesting papers I read this year was Hartshorne & Germine, 2015, "When does cognitive functioning peak? The asynchronous rise and fall of different cognitive abilities across the life span": https://doi.org/10.1177/0956797614567339 There are lots of good bits, such as: 'On the practical side, not only is there no age at which humans are performing at peak on all cognitive tasks, there may n…

Apologies for pasting all of this, but the excerpt has always stuck with me. It seem correct. Are there alternative explanations other than mental processing speed and so on? (For example, later in life, you're less likely to be in a position to do the same sort of work. But that seems to have been tested by e.g. the institute of advanced study.) As far as I can tell, this section might be one of those facts that peo…

First, a note: math is one of the specific areas where humans generally peak really quite young. Math (quantitative reasoning/logic) is not the only area of psychometric intelligence testing (e.g., IQ) and not even a majority of it. So, it may be that it really is a bit harder for older mathematicians to make breakthroughs? I don't know. At any rate, citing mathematics as an indicator is probably not ideal, because math ability does indeed generally peak early.

However, as of 2011[1] the mean age of physics Nobel winners at the time of their achievements across the entire period of the award was 37.2 and since 1985 the mean age was 50.3.

According to the same paper, by the year 2000, Nobel-level achievement in physics before age 40 was only 19% of cases. It also appears that awards in chemistry and medicine are similarly increasing in mean age.

Is this dispositive? Certainly not. Maybe the Nobel committee prefers to award old scientists because of some unknown bias?

However, it does indicate that high achievement is both possible and normal in middle age and beyond.

[1] https://www.pnas.org/content/108/47/18910.full

Re: Ask HN: What's the best paper you've read in 2020?

#152

Post by sillysaurusx »

checkyoursudo wrote: post #151
sillysaurusx wrote: post #147

Earlier quoted context omitted.

Apologies for pasting all of this, but the excerpt has always stuck with me. It seem correct. Are there alternative explanations other than mental processing speed and so on? (For example, later in life, you're less likely to be in a position to do the same sort of work. But that seems to have been tested by e.g. the institute of advanced study.) As far as I can tell, this section might be one of those facts that peo…

First, a note: math is one of the specific areas where humans generally peak really quite young. Math (quantitative reasoning/logic) is not the only area of psychometric intelligence testing (e.g., IQ) and not even a majority of it. So, it may be that it really is a bit harder for older mathematicians to make breakthroughs? I don't know. At any rate, citing mathematics as an indicator is probably not ideal, because m…

This is a phenomenal answer to something I've wondered about for so long. Thank you for presenting data!

Re: Ask HN: What's the best paper you've read in 2020?

#153

Post by Naracion »

checkyoursudo wrote: post #151
sillysaurusx wrote: post #147

Earlier quoted context omitted.

Apologies for pasting all of this, but the excerpt has always stuck with me. It seem correct. Are there alternative explanations other than mental processing speed and so on? (For example, later in life, you're less likely to be in a position to do the same sort of work. But that seems to have been tested by e.g. the institute of advanced study.) As far as I can tell, this section might be one of those facts that peo…

First, a note: math is one of the specific areas where humans generally peak really quite young. Math (quantitative reasoning/logic) is not the only area of psychometric intelligence testing (e.g., IQ) and not even a majority of it. So, it may be that it really is a bit harder for older mathematicians to make breakthroughs? I don't know. At any rate, citing mathematics as an indicator is probably not ideal, because m…

Specifically responding to the increasing average age of Nobel prize winners: this is in part due to the increasing complexity of problems to solve. With our current ways of solving problems, the new problems become harder and harder. The existing human knowledge is also becoming harder and harder to understand, requiring somebody working in a field to spend much longer studying and catching up to the state of the art before being able to make a significant contribution to the field.

This is one of the reasons that I'm personally so excited about (and working on) the potential of spatially immersive media like VR to understand complex concepts. Taking a step back, tools like a graph plot enabled humans to understand complex concepts like differentials and projectile motion at a much younger age. Could a breakthrough with new ways of understanding human knowledge effectively do the same with knowledge that is today considered complex (eg, quantum mechanics)? If such a breakthrough happens, could we bring the average age of significant contribution in subjects like physics back down?

I don't know, but I hope so. :)

Edit. I also remember reading thoughts by either Michael Nielsen on the increasing age of Nobel-worthy contributions in physics, but I can't find it in my current sleep deprived state. I shall tomorrow if somebody else hasn't pointed to that article by then.

Re: Ask HN: What's the best paper you've read in 2020?

#154

Post by cmukka »

luizfelberti wrote: post #2

For me, it was "Erasure Coding in Windows Azure Storage" from Microsoft Research (2016) [0] The idea that you can achieve the same practical effect of a 3x replication factor in a distributed system, but only increasing the cost of data storage by 1.6x, by leveraging some clever information theory tricks is mind bending to me. If you're operating a large Ceph cluster, or you're Google/Amazon/Microsoft and you're runn…

On this same note I would also suggest some papers which show you can do so much better than simple erasure coding -

[1] Clay Codes - https://www.usenix.org/conference/fast18/presentation/vajha . This paper was also implemented on Ceph and the results are shown in the paper.

and, [2] HeART: improving storage efficiency by exploiting disk-reliability heterogeneity - https://www.usenix.org/conference/fast19/presentation/kadeko... . This paper talks about how just one erasure code is not enough and employing code conversions over the disk-reliability we can get up to 30% savings!

Re: Ask HN: What's the best paper you've read in 2020?

#155

Post by ratmice »

ryukafalz wrote: post #123

A Security Kernel Based on the Lambda Calculus from 1996 ( http://mumble.net/~jar/pubs/secureos/secureos.html ) I've been reading up on the object capability security model a lot recently, and was pointed to this paper... I was hooked. A really compelling security model almost from first principles.

From this year I really liked the paper, Recovering Purity with Comonads and Capabilities, Vikraman Chaudhury and Neel Krishnaswami,

https://arxiv.org/abs/1907.07283

Re: Ask HN: What's the best paper you've read in 2020?

#156

Post by macleginn »

DreamCoder: Growing generalizable, interpretable knowledge with wake-sleep Bayesian program learning https://arxiv.org/abs/2006.08381

A killer paper presenting an algorithm capable of inductive learning. ("DreamCoder solves both classic inductive programming tasks and creative tasks such as drawing pictures and building scenes. It rediscovers the basics of modern functional programming, vector algebra and classical physics, including Newton's and Coulomb's laws.")

Re: Ask HN: What's the best paper you've read in 2020?

#157

Post by sriku »

lostsock wrote: post #134
sriku wrote: post #128

Not a paper, but a fantastic talk by Samy Bengio "Towards better understanding generalisation in deep learning" at ASRU2019. Some pretty mind blowing insights - ex: if you replace one layer's weights in a trained classification network with the initialisation weights for the layer (or some intermediate checkpoint as well), many networks show relatively unaffected performance for certain layers ... which is seen as a…

Do you know if a video of the talk is available anywhere? I was able to find the slides here: https://www.dropbox.com/sh/4sat5w5exw288zf/AABTC_j9GkRVEChpn...

Unfortunately no .. and my searches haven't been productive. I was referred to this talk by my professor who attended the conference and I got to see only the slide deck as well. .. but the slide deck is very good and easy to follow.

Re: Ask HN: What's the best paper you've read in 2020?

#158

Post by janekm »

tgb wrote: post #72
specialist wrote: post #67

Earlier quoted context omitted.

Nice. My math-fu is very weak. I dimly recall a notion for estimating the number of unfound bugs for a code base. Is this similar?

Yeah, exactly. If you wanted to know that your code was bug free, how could you do it? Set a team of experts to each independently scour for bugs. But when do you stop? The quick answer is that you should keep going until every bug you've found, has been found at least twice. I think of this as being that you "just barely" found a bug if only one person identified it, so there are probably still bugs you have "just b…

Does that not assume equal probability of finding bugs? Seems to me that both teams would find the same easily identified bugs (say '=' instead of '==' or revealed by compiler warnings).

Re: Ask HN: What's the best paper you've read in 2020?

#159

Post by youser »

Balgair wrote: post #112

https://web.stanford.edu/group/dlab/media/papers/chenNBT2020... Deep brain optogenetics without intracranial surgery "Achieving temporally precise, noninvasive control over specific neural cell types in the deep brain would advance the study of nervous system function. Here we use the potent channelrhodopsin ChRmine to achieve transcranial photoactivation of defined neural circuits, including midbrain and brainstem s…

Very interesting but only on/off stimulation is possible, there is no spatial resolution.

Re: Ask HN: What's the best paper you've read in 2020?

#160

Post by NieDzejkob »

I haven't exactly read many this year, but I really liked "An Answer to the Bose-Nelson Sorting Problem for 11 and 12 Channels" [1]. It describes many interesting algorithmic tricks to establish a lower bound for an easy to understand problem. Not exactly immediately practical, but still very interesting.

Note that it has been published on arXiv just yesterday; I helped review an earlier draft.

[1]: https://arxiv.org/abs/2012.04400

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