Tag: machine-learning
All the articles with the tag "machine-learning".
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Next-Gen Languages, Compilers, and IRs for AI
How MLIR, TVM, and SPIR-V are replacing hand-tuned CUDA kernels in the AI stack: MLIR's reusable compiler dialects, TVM's auto-tuned kernel search that beat handwritten code on Apple M1 at launch, and SPIR-V's vendor-neutral GPU bytecode, and how the three cooperate so one model can run fast on any accelerator, from PyTorch 2.0 to WebGPU.
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O Dia em que Construí uma IA para Prever Preços de Personagens de Tibia
A história completa do TCAQS, um modelo XGBoost que prevê preços de leilões de personagens de Tibia: raspando 650.000 páginas de leilão a três requisições por segundo, convertendo tudo em SQLite, e três rodadas de engenharia de features e limpeza de dados que levaram o modelo de um baseline de 0,89 até 0,935 de R² em teste, com demo ao vivo no Hugging Face Spaces.
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The Day I Built an AI to Predict Tibia Character Prices
The full story of TCAQS, an XGBoost model that predicts Tibia character auction prices: scraping 650,000 auction pages at three requests per second, parsing them into SQLite, and three rounds of feature engineering and label cleaning that took the model from a 0.89 baseline to 0.935 test R², plus a live demo on Hugging Face Spaces.
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Hacking Moleculer and Building Pylecular: A Journey into ML/AI Microservices
How I ported Moleculer.js's broker, action, and event patterns to Python and built Pylecular: an open-source experiment for serving machine learning models as lightweight microservices that call each other by name (no HTTP, no Flask, no REST) while staying fully interoperable with the existing Node.js Moleculer ecosystem.