Fascinating set of slides by Jon Purdy about functional stack languages such as Joy and Factor. https://
web.stanford.edu/class/ee380/Ab
stracts/171115-slides.pdf
…
@alexjc
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Functional Stack Languages Joy and Factor Explored in Stanford Slides
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Claude Update Impact on Developer Understanding and Code Workflow
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Felt it too since the last Claude update. My daily work (via Cursor) significantly changed… Hardest part these days is making the executive decision: do I even need to understand how it works? For throw-away scripts or tools with verifiable outputs it's increasingly tough!
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Simplifying RL Training: Beyond Enterprise Dependencies
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Luckily, codebases like NanoGPT or the speedrun completely reset people's expectations. But I couldn't find the same for RL; just training Qwen3-4b locally requires hundreds of entreprise-y packages, many of which glitch out when you get slightly off the beaten path…
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Unsloth Monkey-Patching Causes Distributed Training Deadlock Issues
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Eventually tracked down the problem to the Unsloth monkey-patching. Distributed runs even with one process fail, but if you use the regular models from transformers and `pef`, trained with `trl` then it doesn't deadlock… Hmm.
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European RL Variant Focuses on Data Protection Privacy
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Me: Did you know there's a European RL variant that focuses on data protection and privacy? Nobody: Oh, what's it called… Me: GDRPO!
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NCCL Timeout Issue with Qwen3 LLM Engine Initialization
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`accelerate test` works with the default config… But the script above hangs for 10 minutes likely due to the NCCL timeout. Somewhere between these two log lines: INFO [core(.)py:74] Initializing a V1 LLM engine (v0.10.1.1) with config: model='unsloth/Qwen3-4B-Base'
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Training Qwen3 Multi-GPU Setup with Accelerate Library
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Anyone manage to get Qwen3 to train on multiple GPUs using `accelerate`? With a fresh install, I can't get even SFT to work with two 3090s.@UnslothAI The demo notebooks are nice, but a reproducible script known to work would be great, ideally with version dependencies pinned! https://t.co/8FkFpC3pdO
— Alex J. Champandard 🌱 (@alexjc) 10 septembre 2025Anyone manage to get Qwen3 to train on multiple GPUs using `accelerate`? With a fresh install, I can't get even SFT to work with two 3090s. @UnslothAI The demo notebooks are nice, but a reproducible script known to work would be great, ideally with version dependencies pinned!
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Concatenative Languages and RL Environment Limitations
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RQ6: Where best apply a concatenative language like Joy? Most datasets are rather static! Even many "RL" environments are single-turn, simple wrappers around static datasets that only allow the model space to think about a unique answer. The authors of the paper I linked
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Cython Interpreter Optimization Through Memory Management Insights
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In the meantime, I spent a few days looking into memory management and reference counting, which led to many insights about improving and reducing allocations, whole program optimization, language design, and ultimately another rewrite of my Cython interpreter. (Approx 15% faster
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Joy Language: Function Composition for LLM Token Processing
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RQ5: Which specific benefits does Joy bring to LLMs by processing tokens? Let's dig into the juicy bits about the primary "raison d'être" for the project… • Joy stands out as a language because it allows function composition by the sequencing of tokens (called "terms").