I'm a recent CS grad trying to break into ML engineering, and I just finished the first version of a side project I've been working on. Posting it here because I want people who know this space better than me to poke holes in it. The idea started from that feeling every dev has had, where you commit something and a second later your stomach drops because you think you just pushed an AWS key. Server side scanning catches that eventually, but only after it's already in your git history. Local tools like gitleaks run before that, which is the right idea, but they're pure pattern matching, so anything that isn't a known secret format slips through and they say nothing about whether the code itself is risky. Piping your diff to a cloud LLM just trades that problem for a different one. So I built a git hook that runs three checks on a commit, all on device. A fast Rust regex pass catches known secret formats and blocks the commit if it finds one. A small classifier running on the Neural Engine through CoreML catches riskier patterns that don't have a fixed string to match, things like shell=True in a subprocess call or disabled TLS checks, and also blocks if it fires. A small local LLM (Qwen2.5-Coder, 1.5B, running through MLX) reads the diff more like a human reviewer and flags things like injection risks or dead code, but it never blocks anything, just leaves notes. I kept it that way on purpose, since a false positive that blocks your commit kills trust fast, but a false positive that's just a comment costs nothing. Biggest weaknesses right now: it's Apple Silicon only since CoreML and MLX are both Apple specific, and the classifier is trained on a fairly small dataset so I wouldn't call it bulletproof yet. Repo's here if anyone wants to dig into the code: https://github.com/stalzkie/local-forge Mainly curious whether the three layer split makes sense to people who do this for a living, and what risky code patterns I might be missing for the classifier. submitted by /u/StalWrites [link] [Kommentare]

The first build video for the Autonomously Exploring Viam Rover is up! This one is showing how to set up the Radxa X4 before putting it into the robot kit. There will be more videos in the playlist, so stay tuned if you want to build your own version! https://youtu.be/v7vi2d8ITEQ submitted by /u/mikelikesrobots [link] [Kommentare]

Months ago, I got my first maintenance project. Before this, I had only built new solutions from scratch and maintained my own code. But maintaining someone else's system feels completely different. ​ ​It’s a prescriptive recommendation system that uses XGBoost models and Differential Evolution for optimization. The problem is that everything is in a single repository: raw data ingestion, transformations, model training, reporting, the optimization engine, post-processing, and MUCH more. The only thing outside the repo is the frontend website. To me, it looks like a massive, super complicated monolith. ​ ​After almost 3 months, I still find new "patches" (quick fixes) every single day. Every time I do, I have to re-learn how the system works. The documentation is very generic and a total mess; it mixes the original design with patches from the two maintenance teams that came before me. I’ve checked some of the docs, but definitely not all of them, because there are about 50 long markdown files. ​ ​Have you ever dealt with a prescriptive system like this? How do you survive? Honestly, I’m debating whether to just quit or keep patching the code however I can until the project ends—even though I know that’s not the right way to do things. ​ submitted by /u/DescriptionBorn153 [link] [Kommentare]

Shared on The Platform Formerly Known As Twitter by Halborn earlier: https://x.com/halbornsecurity/status/2067653567108772061 submitted by /u/Hot_Local_Boys_PDX [link] [Kommentare]

When working on robot models, I often wanted to: Open a shared link See the robot instantly Inspect joints and meshes Validate URDF errors Export to other formats That's why I started building RoboInfra. You can paste URDF/Xacro and instantly get: 1) 3D visualization 2) Validation 3) Auto-fix suggestions 4) URDF → MJCF conversion 5) URDF → USD conversion 6) Shareable robot links 7) And much more What other features would you expect from a tool like this? Free Forever https://roboinfra-dashboard.azurewebsites.net/playground submitted by /u/DateRealistic5066 [link] [Kommentare]

good morning 25x in one hour done for the day submitted by /u/Friendly-Passage1592 [link] [Kommentare]

Moomoo offers up to $1,000 in free stock through it's current promotion ending this month. It has several tiers, $30 at 500 deposited $100 at 2,000 $200 at 10,000 $400 at 50,000 $1,000 at 100,000 I would recommend putting in 20,000. The app gives you an 8.1% APY for 2 months on the first $20,000 you have in. Buying stocks is not necessary at all and the cash you do not invest is fully FDIC insured and gets you that insane 8.1% rate on top of whatever free stock you get at the end of the two months. There is no reason not to use the app. submitted by /u/IAmPhlegmatic [link] [Kommentare]

Hi All! I have developed a research optimizer (QQN Quadratic Quasi-Newton) and published a paper on it where I am able to, but I would really like to make the algorithm itself easily available to the community for evaluation. I have a Rust, Java, and Javascript implementations, but these are built with my own learning frameworks around them (or Tensorflow.js for the last), so I need to port it to something with wider usage. Tensorflow.js seems to lack a central place for optimization algorithms, and also doesn't seem super widely used? I checked out argmin (rust) but it looks like there has been no dev activity on it for about 8 months. I don't want to invest the time porting to a project that might have the same issue! This space is always changing and hard to keep up with, so I thought you guys would have some good ideas. Also, I'm looking for something close-to-metal and strongly typed. Thank you for your time! PS: Apologies if this qualifies as a "career question" - I posted after no small amount of internal debate! submitted by /u/Kooky-Bit8706 [link] [Kommentare]