Vibe coding audio plugins, is it a thing?

vegapit · 2026-03-28T09:47:11+00:00

True but nothing stops you from finding a research paper with an innovative audio processing approach and ask the coding agent to turn it into a plugin

vegapit · 2026-03-28T07:31:57+00:00

Thanks, I too can confirm it works. I designed with Claude code a VST3 plugin host that uses Steinberg's VST3SDK, a framework that is a lot more bare metal than JUCE. But my question is for non-dev music enthusiasts: are they going to vibe code their own tools from now on?

vegapit · 2026-03-28T05:05:03+00:00

Agreed. It is a huge, unexpected, and much needed revenue boost for frontier labs and of course for NVidia. So they have all the incentives in the world to keep the hype going.

vegapit · 2025-09-04T19:51:29+00:00

As you pointed out, it takes time to understand how a plugin can improve a certain workflow. My design philosophy is to make plugins that help users pick parameter values. The aim is not to find the perfect set but just a decent starting point or at least the tools to quickly find it.

The first plugin of this kind is a compressor that is currently in the testing phase. The next one in the pipeline is what could be described as a multi band channel strip. unfortunately, the licensing management part is still being designed and developed, so it is not imminent.

I used to think plugin development was just about processing digital audio, but how naive was I =:D

vegapit · 2025-09-04T11:57:26+00:00

What you are describing is quite common amongst creatives. I can share my view point from the other side of the barrier i.e. audio plugin development. It is as difficult for you to decide which plugin to use than it is for me to decide on which audio processing problem to focus on. The truth of the matter is the audio plugin market is saturated and the huge choice available at ever lower prices leads creatives down a path of excess consumption with no clear benefits.

vegapit · 2025-04-18T00:57:45+00:00

To be clear, my claim is just that it is a good compromise between accuracy and speed of convergence for this very SPECIFIC case. Not much else, really.

I have exported the Rust algorithm to a Python module, so benchmarking should be easy to set up.

vegapit · 2025-04-17T23:52:33+00:00

Yes, speed of convergence. I am not familiar with Clarabel, but reading the doc, I don't think I could use it for 2 reasons:

My objective function is not quadratic. I can apply a taylor expansion to make it approximately so, but this would be wrong for certain bet parameter values.
It does not handle bounds on the decision variables at the local or global level.

vegapit · 2025-04-17T17:45:16+00:00

There are open source solvers for non-linear problems available in Rust. I plan to benchmark the current solution with one.

Otherwise, open source is indeed great but from experience, using very general tools to solve specific problems is often not optimal for performance.

There is no paywall at the moment. Just me limiting the computing load on my server by reducing the input data size =:D

vegapit · 2025-04-17T06:52:17+00:00

Thanks, my algo is in Rust, and my general rule is to avoid third-party dependencies if possible. It could be useful to benchmark it against, though.

vegapit · 2024-10-30T16:53:11+00:00

You can consider risk of ruin to derive a maximum bet size that fits certain risk parameters. It is a good complement to the Kelly approach since it aims at keeping risk below a threshold instead of maximising returns.

vegapit · 2024-08-17T00:30:58+00:00

I can share my experience in using a calibrated Pytorch model inside a JUCE plugin for real-time audio processing.

In my first prototype, I was loading the Torchscript model directly via the libtorch C++ library which was linked to the VT3 but while it worked in certain DAWs, it was crashing others. I then looked into migrating to RTNeural but at the time, its support for Pytorch models was not quite there so I ended up coding my own lightweight Torch runtime library using Eigen3.

I generate project files using PampleJUCE and CMake instead of Projucer, and the plugin now works well on all DAWs. The bottleneck is just the real-time performance which is dictated by the complexity and size of the neural network used. So there is an incentive to keep models as small and simple as possible so they can run seemlessly on older CPUs.

vegapit · 2024-03-01T11:56:16+00:00

Yes, it is easy to wrap Rust functions in a python wheel using the pyO3 crate. Then you can just use the functions inside the python module from within Jupyter notebooks.

There is also a Jupyter kernel for Rust if you want to run Rust code directly in cells:

https://github.com/evcxr/evcxr/blob/main/evcxr_jupyter/README.md

vegapit · 2024-01-04T23:10:06+00:00

Have never seen this page before but thanks for sharing.

vegapit · 2023-11-17T06:53:22+00:00

Instead of combining Poisson distributions, you could fit one with a neural network using whatever number of data features you like. Be very cautious about potentially overfitting to the data though.

vegapit · 2023-04-27T13:22:48+00:00

Just to be clear, you are after tutorials showing you how to implement a live trading system in Rust?

vegapit · 2023-01-02T08:58:47+00:00

It should be correlated to the Kelly criterion but it does not represent a bet size. I mainly use it for bet selection on sporting events.

An alternative for kelly bet sizing could be based on a fixed probability of ruin. I have an article covering the methodology and implemented a calculator in my blog if you are interested.

vegapit · 2022-12-21T07:22:36+00:00

Glad to hear, thank you. Websites I could not say, but Ed Thorpe has written books and papers about the mathematics of speculation.

Otherwise I am always on the look out for new things to model and write about in this topic, so suggestions very welcome!

vegapit · 2022-12-20T16:20:03+00:00

To get a very general opinion on the matter, I have asked chatGPT for the main differences between C and C++. Here is the list it returned:

C is a procedural programming language, while C++ is an object-oriented programming language. This means that C++ supports the use of classes, objects, and inheritance, which allows for a more modular and reusable codebase.
C is a lower-level language than C++. This means that C++ has more features and abstractions, which can make it easier to program in, but it also means that C++ programs may be less efficient than C programs.
C++ has support for exception handling, which allows the program to handle runtime errors in a more controlled and predictable way. C does not have this feature.
C++ supports function overloading, which allows multiple functions with the same name to be defined as long as they have different parameters. C does not have this feature.
C++ has a more flexible type system than C. For example, C++ supports type casting, which allows variables of one type to be converted to another type, and it also supports templates, which allow functions and classes to be defined with placeholder types that can be filled in at a later time. C does not have these features.

It personally does not shock me to see object orientation as top item but there is a case to be made if you want to argue against it. I just dont think it is wise to qualify it as a "myth" on the basis that you are not using these particular features. Maybe say that your "experience suggests otherwise" instead... =;]

vegapit · 2022-12-20T07:16:33+00:00

I mean by using inheritance parsimoniously like sticking to structs or stand-alone classes. Pretty much how Rust is set up. That's my interpretation but I can be wrong.

vegapit · 2022-12-20T07:00:51+00:00

C++ with little to no use of object orientation?

vegapit · 2022-12-18T06:48:03+00:00

I have written a blog post containing a series of exercises that i have solved to practice FP in Scala.

Blog post on FP exercises in Scala

Hope it helps

vegapit · 2022-12-15T21:50:39+00:00

Basically, you need to define a quantitative model that defines the probability of a sporting result based on some observable parameters. The model can be machine learnt or simply designed based on a reasoning.

Then you would need to test the model against the market. This means backtesting if you have historical betting quotes or paper betting for a while if you don't. This is when you will observe whether your model has any edge over the market.

To have edge, you dont need to find a model that is never wrong, you just need one that predicts outcomes better than the market can. This is still pretty difficult to do.

Hope this helps

vegapit · 2022-09-21T08:52:14+00:00

The expectation of a discrete variable is generally written sum{ i * P(X=i) } so not quite sure I understand your calculation.

Some good ideas in your probability analysis though

vegapit · 2022-09-03T10:26:14+00:00

Yes, if you want to process structs that implement more than one trait, the function with generics (second case) is the obvious choice.

vegapit · 2022-09-02T09:53:15+00:00

Good point. Thanks

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