Show HN: Turn regular JavaScript into a neural net | Hacker News Reader

Show HN: Turn regular JavaScript into a neural net

chenglou.me

45 pointschenglou12 comments

As far as I understand, this doesn't turn "regular" JavaScript into a NN, it's rather "write your logic in a DSL that creates a neural-net-shaped circuit"

the source code for the OS demo is not "regular" code, it's full of `emiRelu`... https://github.com/chenglou/handwired/blob/main/src/handwire...

The main site & readme seem to overclaim, while the docs say things like "With Handwired you write a numeric program" and "No tool converts existing JavaScript source into a program" - https://github.com/chenglou/handwired/tree/main/docs

happy to be proven wrong, to have misunderstood this, etc.

I think for everyone interested in this project checking your OG twitter thread is also somewhat mandatory:

https://x.com/_chenglou/status/2110557373651931267

It took me a bit to wrap my head around what you did.

It seems interesting but I am confused. What is the purpose of that landing page? It is not clear since it showcases several (not related) ideas:

- turning js code into something else, arguably high-level code for training neural networks

- a mini OS inside the browser

- a gallery

- document search

I think this is basically a compiler that turns arbitrary JS code into weights of a neural net that then behaves exactly like the JS program. And the stuff at the bottom are demo projects that are now running as a neural net.

the "DEMOS" label is rather small, I understand the confusion

What is stopping Anthropic, Google etc from essentially building models that completely replace the concept of code?

You point a model to an API and get a fully working UI right away. I don’t mean an agent CODED the UI - I mean the model inferred it from its training data and renders it to you “live”

Or the other way around? You serve it a UI- and it acts as the backend etc? State and persistence becomes an issue, but the model could freeze things into deterministic structures (specific parts become -just in time-frozen, for example when data needs to be saved)

Maybe this is old news already- but the consequences are kind of mind blowing

google/tracr https://deepmind.google/research/publications/22295/

Novelty. The models still cannot produce new solutions. They are getting really good at solving tough problems but only if the problem is defined specifically enough in advance to warrant a narrow solution. Otherwise these models are good at replacing the people who aren’t good at this either.

We are ~18 months away from the entire UI being replaced.

Website is missing the #1 thing I imagine most readers would want to know: why?

Clever, I wonder what would happen if you did this in reverse? Like, if we froze the weights then added some layers trained on a bunch of weird edge cases then tried to convert those weights back into branches.

QA through entropy lol

Lol, if you pass a = 4.5 to their homepage const result = (a > 4) ? 10 : 12 you get 11. Not everything is differentiable.

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