The most fascinating thing about AI is how in a thread like this one, answers range between 0% and infinity.

To be accurate, it’s between negative gains and infinity.

Personally I do not trust for a second self-reports anyways. They are bound to be wrong.

To be fair, for my coding at work, AI is “only” like a 2x booster because stuff at work is a lot less greenfield.

Thanks! Yes I loved the ratio of apparent simplicity to underlying complexity of this project. I have filled around 120 pages of draft and notes just for the math of the solver :)

That's great feedback, thanks! I agree with you, but I don't want to flip the default because this is an experiment I made for fun, and the whole point is to lean in to the chaos a little bit. In a serious product the UX would definitely need a lot more work though.

Graphically, I really like the way autodesk makes sketches in fusion 360 blue until they are fully constrained, and then they are black. My intuition here is that you could color code “degrees of freedom” and “locked” states so that it was more intuitive.

You can do this with bidicalc already! You just have to model the problem correctly. If you expect the ratio to remain constant, what you actually want is a problem with a single free variable: the scale.

    A1 = 1.0       // the scale, your variable
    A2 = 6 * A1    // intermediate values
    A3 = 8 * A1 
    A4 = A2 + A3   // the sum

Now update A4 (or any other cell!) and the scale (A1, the only variable) will update as you expect.

Interesting, thanks! I had never heard of this. Yes, bidicalc is much more advanced. You can update any value of an arbitrary dependency graph of cells.

Why do you think that 6+8 is a better solution than 7+7?

When C1 changes from 7 to 14, that’s a scalar change. The least-assumption, information-preserving update is to scale both inputs by the same factor.

It preserves an implicit relationship, ratio, between A and B.

I wasn't aware of this chapter, but I did use constraint propagation for the solver (among other things), thanks!

You can do it and it is explained, actually. Use # as a prefix to indicate a constant, e.g.: #50 will be a constant and not a variable.

In the future I'd like to support more user input constraints, in particular domain constraints for variables. So you could tell the solver that this cell must remain in some interval, and it would respect that interval instead of assigning any real value.

IMO constant should be the default and variables should be annotated.

Jokes aside, let's say someone does figure out how to break RSA over a weekend project. The evil options are easy to come up with, but what is the actually responsible, ethical, thing to do? Never tell anyone?

Contact a known and trusted security researcher who can verify to the world that you did what you said you did, so everyone else can have as much time as possible to figure out exactly how fucked they are. Doing nothing isn’t an option; once someone figures something like that out, it signifies that conditions were ripe for the discovery to be made, and it’s only a matter of time before it’s discovered again independently.

Also fairly reasonable to assume it has already been done by someone who had a motive to break it and is keeping quiet.

Pretend you had developed a quantum computing advancement and push people to post quantum encryption

Migrating to post quantum encryption is important, but it's also important to not be herded into a "solution" that can be/has been easily compromised.

https://blog.cr.yp.to/20251004-weakened.html

Never used any of those, so I don't know! I'd be curious to read a comparison from anyone who knows about them.

I think what's pretty unique about the bidicalc solver that I made is that it does not depend on the previous input values to update backwards. It's truly solving the root finding problem. The advantage is that there are never any "stuck in a local optimum" problems with the solver. So you can solve difficult problems like polynomials, etc.

Excel Solver allows you to create target function with different variables and describe limits for them. Then you may try to find maximum, minimum or exact value for the target function.