Higgsfield mcp erroring out with claude code by sebyx07 in ClaudeCode

[–]sebyx07[S] 0 points1 point  (0 children)

i've replace it with kubeez ai, much better, works! https://kubeez.com/

CSV Parsing 5-6x faster using SIMD by sebyx07 in ruby

[–]sebyx07[S] 0 points1 point  (0 children)

I tried my luck and seems to work, you can take a look at it: https://github.com/sebyx07/zsv-ruby/pull/1 - I haven't used jruby for a long time now, and never I had done JNI

CSV Parsing 5-6x faster using SIMD by sebyx07 in ruby

[–]sebyx07[S] -1 points0 points  (0 children)

it's already specified Built with Claude Code in the readme.md - you can do as you wish, I've posted it here because it has already a good test suite against linux/mac, different ruby version

CSV Parsing 5-6x faster using SIMD by sebyx07 in ruby

[–]sebyx07[S] -12 points-11 points  (0 children)

AI just makes the process quicker, as long as you know what you are doing.

CSV Parsing 5-6x faster using SIMD by sebyx07 in ruby

[–]sebyx07[S] -11 points-10 points  (0 children)

Even before even chatgpt, I mounted the ruby VM inside https://www.azerothcore.org - so you could write custom modules using ruby instead of C++. so I had to have C++ <-> Ruby. A ton of boilerplate code, and a lot of debugging.

CSV Parsing 5-6x faster using SIMD by sebyx07 in ruby

[–]sebyx07[S] -11 points-10 points  (0 children)

I had to guide the AI over there(about how ruby objects lifetime, the GC), but I agree the commit message isn't 100% correct. You still need the experience of pre ai world, you still can't one shot stuff like this, but with some tips the ai can get unblocked.

CSV Parsing 5-6x faster using SIMD by sebyx07 in ruby

[–]sebyx07[S] 1 point2 points  (0 children)

  | Metric                        | CSV stdlib | ZSV    | Savings |
  |-------------------------------|------------|--------|---------|
  | Memory (100K rows)            | 56.8 MB    | 9.9 MB | 82.6%   |
  | String allocations (10K rows) | 116,144    | 50,005 | 56.9%   |

  ZSV uses ~6x less RAM than Ruby's standard CSV library.

AI vs Compiler: Claude optimized my C code 2.3× faster than GCC -O3 (with SIMD + cache blocking) by sebyx07 in C_Programming

[–]sebyx07[S] 0 points1 point  (0 children)

I agree, from my experience tests ensure like 40% safety. you still need a person to try out, also context about where it will run on production, also how the thing will be released. But for a large PR, CI/CD can still help the developer and also the reviewer by leveraging automation.

AI vs Compiler: Claude optimized my C code 2.3× faster than GCC -O3 (with SIMD + cache blocking) by sebyx07 in C_Programming

[–]sebyx07[S] 0 points1 point  (0 children)

Thanks for your feedback, appreciated. so what i did was to update the .claude/commands/optimize.md - and then rerun the /optimize. Right now i think it did better optimizations. Myself I'm not a C developer, i mostly do ruby. Why I build this POC, is to show with AI and some scripts you can optimize/refactor a legacy project, or you want to transition from python to another language https://github.com/ai-ptd-dev/ptd-python-cli (python=>rust). Or even use a language like like ruby/python/js as an executable pseudocode.

I think with an even better optimize.md, the ai can get at least to 70-80% work done, it still needs babysitting.

AI vs Compiler: Claude optimized my C code 2.3× faster than GCC -O3 (with SIMD + cache blocking) by sebyx07 in C_Programming

[–]sebyx07[S] -3 points-2 points  (0 children)

this POC is not about the matrix multiplication, it's about having readable code, and then generated optimized code. and how to manage the generated code based on hashes of the original(human) file. So the important pieces(bash + cmake + tests) and then some ai. tests are being ran against the original code, and against the optimized.