What I would like to see is an easier version of this same format.

https://www.youtube.com/watch?v=S2xHZPH5Sng

The correct comparison should be comparing for each area and situation, which type of transport investment results in the greatest utility. The objective is not to minimise traffic, but to maximise peoples ability to get where they need to be.

EDIT; I may have misunderstood the reviewers acceptance. The post should probably be deleted.

Comments URL: https://news.ycombinator.com/item?id=35134162

Points: 4

# Comments: 1

Given a perfect blurred image, reconstruction is possible - however due to the attenuation, these high frequency components are ~sensitive~.

Apart from quantisation effects [you mentioned which limits perfect de-convolution], adding a little AW Gaussian noise(such as taking a photo of the image from across the room) after the kernel is applied obliterates high frequency features.

Recovery when noise is low (plus known glyphs) is why you should not use Gaussian blur followed by print screen to redact documents. Inability to recover when there are artifacts and noise is [part of] why cameras cannot just set a fixed focus [at whatever distance] and deconvolve with the aperture [estimated width at each pixel] to deblur everything that was out of focus.

TLDR for readers, It is unlikely to recover sufficient detail via de-convolution here.

I am curious if this article has been scanned by a machine that attempts to use OCR to improve quality - at the expense of occasional mistakes. "dress" in place of "chess" looks close in font appearance, but far to mistype on a keyboard.

Copyright working in a supported/non hated way: You develop a package to do X by cribbing off someone else's package X. They sue you for stealing their work, not to make money off you. Situation at hand is case 2, hence the lack of interest in financial gain.

Why is this case 2, when it does not always reproduce the copyrighted works exactly? Situation: You realise that rather than cribbing off of one persons package X, you can crib off two other package X's and mix/average their contents. Scale this to 100's of packages.

Eventually, ML should avoid this by developing to work from first principles, writing in it's own style, with public code used only for validation of it's ability to understand and write code.

In this video https://www.youtube.com/watch?v=T8q3zrCYMRw, they managed to differentiate most high end violins (4/5 tests - 10 Violins).

Incidentally, the only mistake was with one of the two Stradivari examples.

    people = {
        "Diane": 70,
        "Bob": 78,
        "Emma": 84
    }

    people.get("Bob")
    # 78

    for key in people.keys():
        people.get(key)

    keys = people.keys()
    # dict_keys(['Diane', 'Bob', 'Emma'])

    for key in keys:
        keys.mapping[key]

Two simulations of chaotic systems (starting identically) with different step sizes will always diverge (The difference in eventual positions does not stabilise as steps are made smaller). For this reason, I am not even sure if infinitesimal steps would avoid divergence from (ideal) reality. Plus y'know, the whole issue of a simulation with infinitesimal steps never making ANY progress, regardless of how fast it runs.

Therefore, I conclude that infinite degrees of precision is not the issue or solution for numerical explanation of chaotic behavior.