In this view, maybe an ultra radical solution to privacy issues is : no privacy at all, for no-one. Complete and total transparency of everyone to everyone. Now the question is how to implement that ? That's obviously impossible, because someone in power will always have something to hide. So maybe if true democracy where everyone holds exactly the same amount of power that could work ? Same issue, because it is impossible to implement too. Oh well.

Was there an improvement in things ? Obviously, computers are more powerful for example. But with less powerful computers, people could also be happy I believe.

I remember 15 years ago, tech has obviously evolved a lot since then, and I have learned to use more and more tech tools. But am I more efficient than then ? Happier than back then ? More skilled than back then ?

- More efficient for some things, less efficient for others. - Happier ? no. Not sadder either, similar. If anything, it's not related. - More Skilled ? No. Skilled at other things. For example my handwriting is still ok but I believe I won't be able to write so much or so quickly or so well as I used to (I should try though).

Am I saying that progress is not real ? No, of course not. Progress happens. But is it what "people" want or need ? Taking my own perspective : if it happens (and it does), I adapt - no problem. If it does not happen somehow - then I would adapt too. That's what we do.

Well, so far we have been automating many things, and we are still busy working and living as always. It's of course impossible to automate everything - we always have things to do, by necessity by also by choice ; do we really want to be idle and contribute nothing to society ? I don't, and I am sure nobody does. Being useful is an essential need.

Is it pointless then, to automate more and more ? No. It's a way to move forward, and not necessarily a "bad" way. Just not the only way.

Comments URL: https://news.ycombinator.com/item?id=47349856

Points: 2

# Comments: 0

A few hours later, this (static) web app was born. It's a glorified calculator that allows you to answer two questions:

- how much interest will I pay in addition to the principal (the amount being borrowed).

- Whether I should buy my home or keep renting.

Comments URL: https://news.ycombinator.com/item?id=46003804

Points: 3

# Comments: 2

[0]: https://github.com/tomnomnom/gron

fun showit( s : string )

  s.encode(3).count.println

[0] https://koka-lang.github.io/koka/doc/book.html#sec-dot

I spent some time making it work with interpolation so that the transitions are smooth.

Then I expanded to another version, including a small neural network (nn) [1].

And finally, for the two functions that have a 2d parameter space, I included a viz of the loss [2]. You can click on the 2d space and get a new initial point for the descent, and see the trajectory.

Never really finished it, though I wrote a blog post about it [3]

[0] https://gradfront.pages.dev/

[1] https://f36dfeb7.gradfront.pages.dev/

[2] https://deploy-preview-1--gradient-descent.netlify.app/

[3] https://blog.horaceg.xyz/posts/need-for-speed/

See e.g. the study [0] conducted by Public Health England that concludes vaping is at least 95% (!) less harmful than smoking.

See also this video [1] that shows graphically the different impact it has on the lungs.

[0] https://www.gov.uk/government/news/e-cigarettes-around-95-le...

[1] https://youtu.be/0Pwj6BuS8Ds

You may be interested in Observable Framework [0]

[0] https://observablehq.com/framework/

You are probably thinking about `df.apply(lambda row: ..., axis=1)` which operates on each row at a time and is indeed very slow since it's not vectorized. Here this is different and vectorized.

bqplot [1] for example is great for 2D dataviz, very responsive and updates real-time. Based on D3 I believe. Usually I can do what I want with base widgets and bqplot and the result is pretty.

ipyleaflet is another popular library for maps.

I especially enjoy using them with voila [2] to create an app, or voici [3] for a pure-frontend (wasm) version.

If you want to develop a widget, the new-ish anywidget library can reveal handy [4].

For an example, see this demo [5] I made with bqplot and voici, that visualizes a log-normal distribution.

[0] https://ipywidgets.readthedocs.io/en/stable/

[1] https://github.com/bqplot/bqplot

[2] https://voila.readthedocs.io/en/stable/

[3] https://voici.readthedocs.io/en/latest/

[4] https://anywidget.dev/

[5] https://horaceg.github.io/long-tail/voici/render/long_tail.h...

Before it was made with Zola [2], which is also nice.

[0] https://quarto.org/

[1] https://blog.horaceg.xyz/

[2] https://www.getzola.org/

Also wrote about it in my blog [1].

[0] https://gradfront.pages.dev/

[1] https://blog.horaceg.xyz/posts/need-for-speed/

https://youtu.be/oBcFLmu_tlc

Comments URL: https://news.ycombinator.com/item?id=40177962

Points: 4

# Comments: 0

However, when I used it a couples years back it struggled with large vizs, I think due to Vega(-lite)'s way of embedding the data in the viz artifact.

Also, interactive is nice but often I just need a quick static plot, and matplotlib is more convenient for this, you can easily see the png in any environment etc.

These days I'm eager to see an Observable Plot [1] wrapper for Python ! See [2] for a comparison to vega-lite

[0] https://github.com/livebook-dev/vega_lite

[1] https://github.com/observablehq/plot

[2] https://observablehq.com/@observablehq/plot-vega-lite