Kind of reminds of the cellular automaton, about how reducing the number of components can lead to complex worlds and rules. Maybe tangentially related. Conway game of life is another example.
Too much efficiency makes everything worse (2022)
321–330 of 377 posts
Re: Too much efficiency makes everything worse (2022)
#322This is more a meta comment about the blog itself (as is customary for HN): I like the blog, there has been a lot of work put into it, so it makes me sad that it's hosted on GitHub pages using a subdomain of GitHub.io. When the day comes that GitHub inevitably kills/ruins Pages, because it _will_ happen, there is no question, the links to this blog will be stuck forever pointing to this dead subdomain that the author…
If he hosts his site on his own server, it will go down a few months after his death.
Assuming he's not 70, I guarantee GitHub pages will turn to shit before he dies.
But also fair point. I think we should all have a contingency plan I'm case of death, regardless of where our stuff is hosted. Self-hosted stuff indeed becomes a ticking time bomb after death. Even on 3rd party services, it's apparently a nightmare trying to get access to a deceased person's Google account, where Google Sites may live, etc.
Re: Too much efficiency makes everything worse (2022)
#323Earlier quoted context omitted.
Isn't this already part of F?
Your sound system has a volume dial to turn up and down the gain of the track even though you could get the same effect by re-recording the track at a higher volume; isn’t that curious?
But I don't optimise my track to have an ideal volume. I do optimise my AI like that.
Re: Too much efficiency makes everything worse (2022)
#324Kinda surprised to not see anyone mention Jacques Ellul and his The Technological Society which highly revolve around this. Technological here does not refer to technology.
What do you think about Ellul's arguments in that book?
Re: Too much efficiency makes everything worse (2022)
#325The author identifies problems with a system measuring targets, but then all the proposals are about increasing the power and control of the system. Perhaps the answer—as hippy sounding as it is—is to reduce the control of the system outright. Instead of adding more measures, more controls, which are susceptible to the prejudices of control, we let the system fall where it may. This, to me, is a classic post of an ac…
For an example of this, I recall reading a proposal that acts of Congress be strictly limited to be at most (say) 5 pages in length. This would be a natural form of regularization of the legislative power.
Re: Too much efficiency makes everything worse (2022)
#326Too much efficiency countering too much efficiency makes everything worse.
This whole thesis easily tips over into a semantic gobbledygook, as efficiency is not a property of the larger world, but an utter contrivance of thought.
Focus on anything to the exclusion of everything use and things are going wrong. How has the obviousness of this observation has turned into a breakthrough? AI is the perfect nexus for such a discovery: trying to optimize a system when you don't understand how it works naturally has pitfalls.
So what can it mean to try to mathematically formalize a misunderstanding? Maybe there's a true breakthrough lurking near this topic: that all understanding is incomplete, so look for guiding principles of approximation?
The author is right to call out the forest for the trees.
—
Web Design: The First 100 Years
https://idlewords.com/talks/web_design_first_100_years.htm
How the SR71 Blackbird Works
Re: Too much efficiency makes everything worse (2022)
#327Maybe I'm misunderstanding this but this doesn't seem like an accurate explanation of overfitting: > In machine learning (ML), overfitting is a pervasive phenomenon. We want to train an ML model to achieve some goal. We can't directly fit the model to the goal, so we instead train the model using some proxy which is similar to the goal One of the pernicious aspects of overfitting is it occurs even if you can perfectl…
No, because your training data is only an appropriation of the actual workload.
Re: Too much efficiency makes everything worse (2022)
#328Earlier quoted context omitted.
That solution is how it already works for the vast majority of companies in the US. “Too big to fail” is a meme that only applied to a tiny handful of companies during the financial crisis. Take a look at SVB for how fast a stalwart huge bank can implode with zero fucks given by the government.
By "zero fucks given by the government" do you mean the government got involved, effectively bought the bank, and took responsibility for 100% of deposits (most of which were the balances of startups, ie venture capital investments)?
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Re: Too much efficiency makes everything worse (2022)
#329I would claim in a completely informal way that the optimal degree of utilization is ln(2)=0.693, around 70%. This stems from the optimal load of self-balancing trees. A little bit of slack is always useful to deal with the unforeseen. And even a lot of slack is useful (though not always as it is costly) as it enables to do things that a dedicated resource cannot do. On the other hand, no slack at all (so running at…
Where e^-X and 1-e^-X intersect is 0.69. Mumbo? perhaps. Jumbo? perhaps not.
Re: Too much efficiency makes everything worse (2022)
#330Those are great points! Another related law is from queuing theory: waiting time goes to infinity when utilization approaches 100%. You need your processes/machines/engineers to have some slack otherwise some tasks will wait forever.
Interesting. My gut reaction is that this is true in reverse: infinite wait time leads to 100% utilization. However, I feel like you can also have 100% utilization with any queue length if input=output. Is that theory just a result of a first order approximation or am I missing something?
That's right, this is true no matter the queue length. If input=output on average, there is no limit on how long your queue will grow, and therefore no limit on how long queued task will wait.
I don't know what you mean by reverse.