lots of comments from 1 viral youtube from another guy who also hasnt tried devin at all haha. @GergelyOrosz we can livestream to try it out if u want, i got the go ahead to do it, theyre not scared just watch my devin vs opendevin vs swe agent livestream to understand how
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PyTorch Compile Tutorial: Optimizing Machine Learning Code
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https://
pytorch.org/tutorials/inte
rmediate/torch_compile_tutorial.html
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PyTorch Optimization: torch.compile vs Vanilla Performance
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this isn’t comparing to torch.compile, which is the torch-native optimized version, it’s comparing to vanilla pytorch which is notoriously bloated and slow 🙂
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llm.c Optimization: Matching PyTorch Performance After Bug Fix
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Highly amusing update, ~18 hours later: llm.c is now down to 26.2ms/iteration, exactly matching PyTorch (tf32 forward pass). We discovered a bug where we incorrectly called cuBLAS in fp32 mathmode . And ademeure contributed a more optimized softmax kernel for very long rows
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ONNX WebAssembly Trade-offs in AI Model Deployment
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i’m very skeptical that that’s a better decision than just using onnx wasm or whatever else is available
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End to End Latency vs Opus Weaviate Embeddings
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whats end to end latency? vs just opus + weaviate + embeddings
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Tokenizer Training Data: Understanding Token Presence Significance
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If uberinternal WAS a token that tells you that it was one of the top ~30,000 character sequences present in the text they used to build the tokenizer – which is a different corpus from the training set used to train the model uberinternal not being a token doesn't tell you much
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AI Tool Building Websites Better Than Intern-Level Work
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I have been using it for all sorts of tasks where it builds little websites or tools. It works better than an RA at first pass for most things. Intern-level work, not experienced expert.
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Objective-C Skills Remain Valuable in Tech Job Market
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Dang those Objective-C skills still pay off.
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From Apple Notes to GitHub Issues: Capturing and Implementing Ideas
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I use Apple notes for this about a dozen times a day, but I try to turn the more interesting notes into GitHub issues threads if I want to actually implement the ideas that I captured