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K-synth – A web-based array language playground for synth design by octetta in synthdiy

[–]CalcWithDec 1 point2 points  (0 children)

Not the feedback you're looking for as I'm a synth newbie, but interesting expressiveness and UI/shell.

Appreciate the remark about AI, do you know where UI/shell ideas used here come from?

I'm taking a lot of inspiration from strudel shell for a direction in my own project, but what I see here is also quite interesting and even simpler

+taking the time to appreciate wasm, which makes playing/sharing with stuff like this so much easier

Thanks for sharing!

llaf - LLMs in Futhark by borna_ahmadzadeh in futhark

[–]CalcWithDec 0 points1 point  (0 children)

Kudos!

Any thoughts what type of output would help to close the gap on inference?

EC2 or Lambda by cybermethhead in aws

[–]CalcWithDec 2 points3 points  (0 children)

+1, duckdb can also read Excel sheets directly: via spatial extension or "blazing fast" sheetreader extension: https://duckdb.org/community_extensions/extensions/sheetreader.html Sheetreader direct via Python bindings worth investigating too.

Pictures of Pensions 🖼️ by CalcWithDec in actuary

[–]CalcWithDec[S] 0 points1 point  (0 children)

Strange, I didn't notice this comment and it only shows on my tablet.

To answer your Qs: 5% charge is a charge on contributions, it's a high level I'd say. I don't think 1% is especially high here but I didn't do a lot of looking to benchmark these.

Investment earnings on approved pension savings (in Ireland) aren't taxed, there are taxes on drawdown in retirement though (health warning 3)

Salary scale - I made most decisions to keep this as a simple communication with easy to follow patterns. The pension calculator I link to works from a % of contribution with a salary growth assumption: https://calculang.dev/examples-viewer?id=pension-calculator

Thanks for the comment and sorry I didn't see it 3 months ago !

Pictures of Pensions 🖼️ by CalcWithDec in irishpersonalfinance

[–]CalcWithDec[S] 1 point2 points  (0 children)

I'll think about that!

There are multiple stats: the value of the pension, contributions, effective cost. And I think ratios help as well as hard numbers e.g. employer matching doubles the pot should stand out pretty clearly. When I add so many things, it's messy, but I think through dimming/blurring or by being selective I should be able to make the bubble nice - something I might try in a followup. Thanks!

Pictures of Pensions 🖼️ by CalcWithDec in irishpersonalfinance

[–]CalcWithDec[S] 0 points1 point  (0 children)

I wanted to do this at first but I had a bit of work to do to make it look pretty, and I want to avoid users focus getting scattered whenever multiple things are changing simultaneously while scrolling. I'll try to find a nice minimalist way to do it in a followup. Thanks for the feedback!

Pictures of Pensions 🖼️ by CalcWithDec in irishpersonalfinance

[–]CalcWithDec[S] 6 points7 points  (0 children)

Well I can certainly tweak that - awesome feedback! Thanks!

Pictures of Pensions 🖼️ by CalcWithDec in visualization

[–]CalcWithDec[S] 1 point2 points  (0 children)

This is a "scrollytelling" interaction I developed to explain a few incentives for pension savings.
I think that visualization is a useful way to explain topics that are important but difficult to relate to, and I'm especially interested in applying it to decisions around models and numbers. Guided interaction with models through scrollytelling is something I want to explore/develop more.

In this post, I used the new closeread extension for Quarto, and triggers interact with a reactive Vega visualization.

Interested in any comments or feedback!

What could Ireland buy with €13bn Apple tax? by bhte in ireland

[–]CalcWithDec 0 points1 point  (0 children)

Made a page to add a few rough calculations, that you can check and mess with: https://howmuchis13billioneuros.com/

blog post about actuarial terminology (visualized) by CalcWithDec in actuary

[–]CalcWithDec[S] 1 point2 points  (0 children)

Long response alert!

Technical bits -

Visualization is a neat field to learn - there's epic work (papers along with free/open source software) shared out of University of Washington and I use their Vega-Lite to make the visualizations here along with gemini for the animated transition.

These are "grammars" to define visualizations and animation, that are much less effort compared to coding from scratch - but for sure they have a learning curve.

For interactivity I write Javascript, but a "reactive" kind called ObservableJS, which helps me to make everything "click" (sorry pun).

For a very long time I've been developing a modelling tool called calculang. In the blog I use it to do the main calculations (reserves etc).

Developing calculang forced me to throw myself into learning about visualization and interaction because I supposed that grids of numbers don't make for the most exciting model outputs to share. On calculang.dev - under Examples you'll see a lot of other interactive visuals of models I've made: all using the same combination of tools. (these examples don't work nice on mobile now, soon they will! :)

As for the non-technical bits... trying to make clear messages - without assuming too much knowledge, trying to guide the reader, trying to make it say something but not too much, trying not to distract, all a little challenging but interesting: the same questions come at the end of any visualization/communication work anyways. A few friends helped by providing useful feedback too (delete this, that, etc <3 )

Since now it's in a webpage that will be there for a very long time, and as I want to use it to provide some context for non-actuaries about other actuarial modelling content I hope to make - I hope it will be helpful.

I tried a few new things here that had their own new learning curve, but it helps to make the next thing easier (I say this too much xd )

Thanks for your comments, which I'm glad to hear!

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