nynx

this is about 10,000x too much stuff for the equivalent feature set to a markdown file that your agent updates.

Do you have examples of complex algorithms running on the gpu with rust with competative performance? Radix sort might be a good one to start with

I don’t think this needed to be parallelized.

I don’t understand why this is a useful effort. It seems like a solution in source of a problem. It’s going to be incredibly easy to end up with hopelessly inefficient programs that need a full redesign in a normal gpu programming model to be useful.

This is an interesting line in the readme:

> The language forces clarity — not ceremony.

I find this statement curious because a language, like this, without ability to build abstractions forces exactly the opposite.

In my mind, cad that you’re not going to manufacture is “modeling”. Not sure if that’s a common verbal distinction.

Breps. Nearly all commercial cad packages operate on boundary representations of objects.

Unfortunately, using a geometry kernel [1] that operates on triangle meshes means this is a no-go for serious CAD usage.

[1]: https://github.com/elalish/manifold

Incredible work!

I don’t think it’s falsifiable until there are autism diagnostics that aren’t behavioral. Right now, they’re 100% behavioral, which that any theory that tries to cluster autism symptoms is hopelessly tainted by a recursive definition -> diagnosis -> definition cycle.

I find this type of science is infuriating. Monotropism as a theory of autism or adhd is equivalent to saying that “tendency to focus on a few things” is a theory of autism or adhd. You’re describing the symptoms, which explains almost nothing. A theory of autism would explain the underlying physical causes of the behavior.

As usual, GPT-1 has the more beautiful and compelling answer.

> In this specific situation i constructed that precludes inlining of iterators and allows inlining of for-each, then iterators aren’t inlined.

Sure. I can easily see that often being the case for arbitrary code but not interpreter dispatch loops.

I must be missing something here. How would this help predict interpreter dispatch? Those won’t be a function of previous branch history or pc, which may very well be independent of the next opcode. They’d be a function of state in memory or registers.

How did it get into the standard then?

Is it possible to initialize a prng in C++’s std correctly?

It would be insane to put a system as complex as hazard pointers in the C++ standard.

This is cool for sure. I think you’ll ultimately find that this can’t really be faster than modern OoO cores because python instructions are so complex. To execute them OoO or even at a reasonable frequency (e.g. to reduce combinatorial latency), you’ll need to emit type-specialized microcode on the fly, but you can’t do that until the types are known — which is only the case once all the inputs are known for python.

Readme has “add tests” in the TODO section

It seems the product brief is behind a sign-up page. Please indicate to your sales folks that this is highly counterproductive.

Typeclasses are conceptual interfaces. They don’t have anything to do with vtables.

Depending on what kind of software you tend to work on, you may have written a lot of subtly incorrect C.

Do you still use spinal? Have there been other advances in HDL that you've seen over the last 6 years?

Using a list of heap allocated objects for a 2d FFT is an odd choice.

Forcing an unreasonable price for all broadband providers is an excellent way to prevent any from operating in the area. It seems like people learn this lesson over and over — a market is an efficient way to do demand/price discovery.

This sounds like just an fpga. What do you mean by “routing fabric stripped out?” How does data get from one cell to another?

yeah, i did my undergrad research on biological neuron emulation and most of the research in the area is hilariously moronic things just for pumping "research" out and getting students their pieces of paper.

Biologically inspired neuron models like Hodgkin–Huxley are about as far from an emulation of real neuron behavior as a paper airplane is from the space shuttle. We can learn things from using them and they're an important stepping stone, but they aren't really that useful.

That being said, I hope the founder keeps it up — it's great to have more bright, driven people in this field.