antoineMoPa

I vibe-coded a tiny local code review tool, a bit like pull-requests, but an agent does the work immediately.

https://github.com/antoineMoPa/moonreview

The intended use is to run `moonreview` instead of `git status` / `git diff` or `magit`, but you can add comments and they get auto resolved. You can also stage hunks if you are happy with them.

Probably other tools exist or will appear in this space (I saw at least another one in the comments on this post), but i think there is something fundamentally too slow and dumb with current corporate code reviews. People are reviewing other people's slop and most of the comments are probably fed back into an agent. So why not have the whole process be done upfront by the original developper. Another cool thing I saw people do is to attach claude to github PR comments, which I think is great and love to work with this, but it's even better if we can also have this locally to catch sloppy code before it even reaches github.

I guess it becomes bad when it negatively affects other aspects of life. I experienced or witnessed all of these with AI at some point:

- Working later because of addictive loops.

- Wasting time and money building stuff nobody will ever use.

- Abusive screen time.

- Loss of deep understanding of a code base and over-reliance on the AI, with reduced incident or bug response time.

- Producing a lot of sloppy code, too much to be owned or reviewed.

- Mental fatigue.

> Please don't post comments saying that HN is turning into Reddit. It's a semi-noob illusion, as old as the hills.

https://news.ycombinator.com/newsguidelines.html

Training a tiny LLM for fun using Rust/Candle - I constantly tweak stuff and keep track of results in a spreadsheet and work on generating a bigger corpus with LLMs. It's a project for fun, so I don't care about finding actual human generated text, I'd rather craft data in the format I want using LLMs - Probably not the best practice, but I can sleep properly despite doing that.

My favorite output so far is that I asked it what life was and in a random stroke of genius, it answered plainly: "It is.".

It's able to answer simple questions where the answer is in the question with up to 75% accuracy. Example success: 'The car was red. Q: What was red? ' |> 'the car' - Example failure: 'The stars twinkled at night. Q: What twinkled at night? ' |> 'the night'.

So nothing crazy, but I'm learning and having fun. My current corpus is ~17mb of stories, generated encyclopedia content, json examples, etc. JSON content is new from this weekend and the model is pretty bad at it so far, but I'm curious to see if I can get it somewhere interesting in the next few weeks.

https://github.com/antoineMoPa/rust-text-experiments

I also loved Zig when manually typing code, but I increasingly use AI to write my code even in personal projects. In that context, I'd rather use Rust more, since the AI takes care of complex syntax anyway. Also, the rust ecosystem is bigger, so I'd rather stick to this community.

> Developers are not Idiots

I'm often distracted and AIs are idiots, so a stricter language can keep both me and AIs from doing extra dumb stuff.

It would be fun to compare with inference providers (groq/vertex ai, etc.).

I'm making a tiny tiny LLM in rust (using candle) to teach myself AI https://github.com/antoineMoPa/rust-text-experiments

I think that this is the explanation I needed, thanks!

What I don't get about attention is why it would be necessary when a fully connected layer can also "attend" to all of the input. With very small datasets (think 0 - 500 tokens), I found that attention makes training longer and results worse. I guess the benefits show up with much larger datasets. Note that I'm an AI noob just doing some personal AI projects, so I'm not exactly a reference.

It's not clear from the landing page whether it's a git code platform / mercurial / entirely new VCS. I wish it was clearer (looking at the Readme, looks like it's indeed a git hosting platform).

I don't really care about the governance model as a user seeing this landing page for the first time, so I wonder why it's so prominent, vs telling me what the actual product is.

Did anyone build a text-to-splat 3D generation model? Seems like it would be pretty straightforward? Should make it really easy to generate assets for video games.

EDIT: yep - https://gsgen3d.github.io/

Nope! I'm also not convinced by it.

To me, this looks like something chatgpt would write.

A tiny tiny LLM (essentially removing the "Large" part of "Large Language Model"). I taught neural networks to remember wikipedia articles (Actually, just one wikipedia article about horses.) and throw it back as-is by predicting the next token (when given the first token).

https://github.com/antoineMoPa/tfjs-text-experiment/blob/mai...

In terms of coding, I love collaboration when it's necessary, but I dread it when it's forced.

I feel like sync communication is necessary for groomings & design review.

> design was taken forward (approved by the team) just to be heavily criticised during implementation

Pretty strange that it was approved by the team and then criticized. Is this a recurring thing or just a one-off issue people did not spot early enough? If it's frequent, the team should either do a better job of discussing before implementation or understand that they have to unite behind the decision once a design is approved.

I work for the company that I want to work for which is on the other side of the country - yet I live in my home town close to my family & I was able to afford a home thanks to the salary / cost of life difference.

I wonder how that compares to SDF rendering of grass. SDF has a high cost due to the raymarching part, but you essentially get free repetition with local tweaks.

Hi! Thank you, I'm having lots of fun using Bevy!!!

At some point I built something very similar using shaders: https://antoinemopa.github.io/xor-explorer/

HN is slowly turning into bread-it.

Happy new year!

One easy and very useful habit we have where I work is to post all questions (even the stupidest questions) in public slack channels. That's also where most technical conversations happen. This helps us to hide less information in private chats.

I'm not sure I agree with everything, but I love the mental models this introduces.

This being said, that while loop of death is pretty terrifying indeed.

> Blender but then they pulled their shit together and it’s kind of a masterpiece now.

I would love to read more about that! Do you have a blog post or other insight?

Yeah on one hand, a lot of successful & high quality software projects are the result of one very dedicated brain, so maybe it's a valid tradeoff to have an arrogant dictator.

On the other hand, that does not feel so nice as a contribution environment, it creates a software design bottleneck on one person, increasing shipping time and creating a dangerous bus factor. It's not a really scalable way do software design. Overall that attitude is pretty detrimental to community as he basically complains about all previous contributors.

Maybe I'd suggest him to:

- Work on his attitude, respect other contributors & stop calling them names.

- Spend less time developing and more time educating other people who work on the project.

- Come up with a set of design principles that the rest of the project can follow.

But yeah that's open source, he's free to fork a project. Probably his project will be successful anyway despite the negativity.