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Very nice, but probably a bit too expensive to just hand out. I knew a chap that had a similar hardware business card (I don't remember exactly what it did, but it wasn't as cool as this one). I remember that his card was pretty scuffed up, and he insisted I give it back, after he handed it to me. Bit weird.
I half expected this to have a button/mode to show custom QR codes...
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For the most part I agree, but the purpose of a business card is to be read. You can barely read that text.
The render is pretty gnarly, but it's not quite that bad in person https://github.com/Nicholas-L-Johnson/flip-card/blob/main/me...
Off topic, but where should one start learning writing physical simulation? Several years ago I ran into this project [0] and got overwhelmed even the algorithm can be written in 88 lines of C++. I realized that out of all CS topics, physical simulation is probably the one I knew the less (not saying I'm a compiler/database expert or something, but at least I've implemented a toy compiler and some basic data structur…
"Physical simulation" is a very broad scope, so your code for simulating fluids is going to be very different from your code for simulating planetary orbits, and at times it may feel a bit ad hoc. But at its foundation physical laws are written in differential equations and linear algebra.
So whatever algorithm lets you numerically integrate several inter-related variables is going to be broadly applicable to simulating any physical phenomena. At the simplest end of the spectrum you just naively approximate integration by brute force. Eg at each step just update your physical state variables by doing velocity += acceleration, position += velocity. This is called Euler's method, and while simple, it accumulates unacceptable errors rather quickly in most circumstance. The more advanced approach is to use a method like Runge Kutta. In circumstances where you have some known property, like say energy conservation, you can implement a method which explicitly imposes the constraint. This is good for cases where the motion is highly periodic as it prevents the numerical error from accumulating exponentially in orbits that spiral out of control.
Of course at some point you'll have to grapple with the issue of if you are simulating trajectories of free particles or values of neighboring grid points in a field. This question of how best to encode physical systems and simulate them cuts to the heart of physics.
I'll leave it at the old cliche "information is physical"
Would love to see more information about how it was built. He must have worked with a company that can do the surface mount assembly?
>He must have worked with a company that can do the surface mount assembly He did (there are centroid files in the production folder, which tell the board house where to put the components), but you'd be surprised at how possible it is to assemble something like this by hand. You won't believe me, but I find it easier than through-hole soldering (because you don't have to keep flipping the board over). But there's a…
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Yeah but I guess they wanted to add something in the value for everyone of us while they didn't have ofc the whole knowledge to do so. their heart might be in the right place tbh. But that's my 2 cents.
Or is it really ChatGPTs 2 cents? Copy-pasting LLM responses is as useful as posting a "let me google that for you" link. It's a lazy response at a minimum.