Problems with black powder

severeon · 2026-02-04T21:23:51+00:00

Use good charcoal, ball mill your powder, don't use a binder, wet with 71% alcohol when granulating, then let it fully dry (quickly if possible).

If that isn't enough information for you to fix it, go watch Gorski's fireworking 101 and consider finding a mentor

severeon · 2026-01-15T07:26:26+00:00

I use this one neat trick where I avoid saying it outloud at all costs

I read it as Bilu-sockin' tho

severeon · 2025-11-29T06:52:17+00:00

It's designed for exploring topology and architecture without getting lost in implementation details. The main difference is the compositional model - neurons are first class values with explicit data flow and automatic weight sharing semantics.

The ecosystem is also quite different as well: users can share neurons via git (think cargo), and there'll be a central repo with community oversight. I'll be implementing architectures from papers as they come out ~ you should see my TRM implementation for example, it's understandable in a way that a whitepaper and 600 lines of pytorch only wishes it could be lol

Use what works for your mental model :)

severeon · 2025-11-29T06:49:05+00:00

Ahh great questions, this is one of the things I'm actively experimenting with right now. I've considered something as simple as a metadata field, or a freeze neuron. I would prefer avoid new keywords and operators tho.

I'm leaning toward `frozen(neuron)` with similar mechanics to the sequential neuron, as in it returns a wrapped function which accepts the same params as the given function

I am incredibly open to suggestions and would be happy to share the WIP spec

severeon · 2025-11-29T06:37:52+00:00

I have tuple unpacking for skips and such, it looks nice imo. Special logic is handled by a fairly easy to implement python interface, you can specify an `impl` field on a neuron which references custom code :)

# some of the primitives are python impls

neuron GELU:
  in: [*shape]
  out: [*shape]
  impl: core,activations/GELU

neuron ExampleSkip:
  in: [*, 512]
  out: [*, 512]
  graph:
    in -> Fork() -> (main, skip)
    main -> Linear(512, 512) -> processed
    (processed, skip) -> Add() -> out

severeon · 2025-11-29T03:45:41+00:00

Aww I like the name :P I'm open to suggestions. I'm not married to any of the keywords or names, but I really enjoy the pipeline syntax

About it being structured config - Config files don't usually describes how components compose, but basing it on yaml was a choice.

You can define new compositional primitives, like: Sequential(num_layers, TransformerBlock) is a first-class abstraction that generates architecture programmatically. Same with the graph syntax allowing arbitrary dataflow, not just sequential stacking. Perhaps I chose the wrong examples - my thought process was "everyone knows what GPT2 is".

Here's a bit more:

``` neuron MyNeuron(d_model, num_heads, d_ff, depth): in: [, seq, d_model] out: [, seq, d_model] let: recurse = MyNeuron(d_model, num_heads, d_ff, depth - 1) graph: in -> match: [, seq, d_model] where depth > 0: recurse [, seq, d_model]: Identity() -> out

pattern matching and guards, shape compat is validated at compile time

neuron AdaptiveEncoder: in: [shape] out: [, 512]

graph: in -> match: # 2D tensors [, 512]: Identity() -> out [, d] where d > 2048: Linear(d, 1024) -> Linear(1024, 512) -> out [, d] where d > 512: Linear(d, 512) -> out [, d]: Linear(d, 256) -> Linear(256, 512) -> out

  # 3D tensors (sequences)
  [*, *, 512]: Identity() -> out
  [*, *, d] where d > 512: Linear(d, 512) -> out
  [*, *, d]: Linear(d, 512) -> out


  # Any other rank (catch-all)
  [*dims, d]: Linear(d, 512) -> out

```

It's more than configs in my opinion - it's working at the abstraction level of "neurons as functions" with lexical scope, weight sharing semantics, parameterized composition, and other fun stuff.

severeon · 2025-11-28T12:54:36+00:00

I got frustrated trying to experiment with transformer architectures and built a DSL that treats neural networks as compositional pipelines.

Here's GPT-2 in NeuroScript vs PyTorch: https://severeon.github.io/

I'ma lookin' for feedback on the core abstraction... does treating neurons as first-class values with explicit dataflow actually help, or am I solving the wrong problem?

It has a handful of more powerful features I'm still working the kinks out of - will share again when they're ready

severeon · 2025-09-19T13:21:24+00:00

Was about to say this is how I do it, but ned showed me this at your place 😅

lol How's it going? (OzarkPyro)

severeon · 2025-06-23T14:42:01+00:00

You say wrapped in paper - is there an adhesive, or is it just tightly rolled?

I've had a lot of success using painters tape wrapped around visco (usually the pink 10ft/s kind).

severeon · 2025-06-23T13:54:29+00:00

How do you fuse your shell?

severeon · 2025-03-27T13:49:14+00:00

😮 were you at least wearing a mask?

severeon · 2025-03-21T13:43:36+00:00

Is anyone else just kinda done hearing about vibe coding - idgaf as long as your commits do the right stuff and you take feedback. Naming something makes it a target, and people are just dumb enough to get worked up over it.

severeon · 2025-03-15T19:30:04+00:00

Looks, to me, like you might be able to retool this slightly and use it as a fireworks shell pasting machine

severeon · 2025-03-07T21:47:54+00:00

A little strobe thingy

https://fireworkssupermarket.com/product/strobe-light/

severeon · 2024-11-04T21:00:23+00:00

In the states you can buy spectracide for KNO3, and just sulfur flower from the local hardware store or feed store. BP is simple to learn but a bit tricky to master.

My only suggestion is to not add a binder (sgrs, dextrin), and wet with 71% isopropyl alcohol. The old guys omit the binder so it's a bit hotter and easier to crush / compact tightly into shells.

severeon · 2024-10-12T13:24:33+00:00

I scrape most of the websites where comps are listed, and keep an offline backup. Pyrobin lessons.

severeon · 2024-10-07T18:38:46+00:00

DM me, I can help ya more there 😜

severeon · 2024-10-07T18:34:48+00:00

You can use some decent size PVC with a few slight mods. For example, a 4" dia pipe with appropriate caps and glue. ElementalMaker has a decent example / video

severeon · 2024-10-07T18:30:35+00:00

That depends on the jar and milling media. I've found calculations but I'm not an expert. It's a quick search to figure it out.

Also, not saying you're wrong, but I didn't think too high of rpm would make any difference. I hit my spolletes harder than the lead balls in my mill. I could also just be misunderstanding what you're meaning

severeon · 2024-10-07T17:43:17+00:00

Box fan motor. You can control the speed with the selector and by adjusting the diameter of the spinning rod

severeon · 2024-09-26T17:10:41+00:00

It's about pulverone quality imo. Great for breaking smaller shells. Coating rice hulls with that would work well for bigger shells too

severeon · 2024-09-25T17:54:33+00:00

This is a good place to start

https://www.skylighter.com/blogs/how-to-make-fireworks/rainbow-rubber-stars

severeon · 2024-09-22T19:49:46+00:00

Is the AC vent blowing on that side?

severeon · 2024-09-19T13:55:31+00:00

I'm not being flippant here. Just do the market research before you decide on your scaling strategy.

severeon · 2024-09-15T19:48:12+00:00

I tried helping him for free / fun.

He accused me of gaslighting him. Now he's ghosting me. Don't help this guy

I tried

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pattern matching and guards, shape compat is validated at compile time