A Practitioner's Guide to Kolmogorov-Arnold Networks
arxiviq.substack.comยท3hยท
Discuss: Substack
๐Ÿ“ŠGradient Accumulation
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Weak-To-Strong Generalization
lesswrong.comยท18h
๐Ÿ› Ml-eng
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Machine Learning Fundamentals: Everything I Wish I Knew When I Started
dev.toยท15hยท
Discuss: DEV
๐ŸŽ“Model Distillation
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From hours to seconds: AI tools to detect animal calls
seangoedecke.comยท14hยท
Discuss: Hacker News
๐Ÿ”Type Checkers
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MobileNetV3 Paper Walkthrough: The Tiny Giant Getting Even Smarter
towardsdatascience.comยท8h
๐ŸŽฏTensor Cores
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Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm EnablesFine-Grained Policy Optimization
paperium.netยท10hยท
Discuss: DEV
๐ŸงฉAttention Kernels
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Qwen3 VL 30b a3b is pure love
reddit.comยท1hยท
Discuss: r/LocalLLaMA
๐Ÿš€MLOps
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Can-t stop till you get enough
cant.bearblog.devยท3hยท
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๐Ÿ“œTorchScript
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Yes, you should understand backprop (2016)
karpathy.medium.comยท16hยท
Discuss: Hacker News
๐Ÿ“ŠGradient Accumulation
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ClipTagger-12B VLM: Frame Captioning Tutorial
dev.toยท5hยท
Discuss: DEV
๐Ÿ”„ONNX
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TinyML is the most impressive piece of software you can run on any ESP32
xda-developers.comยท2d
โšกONNX Runtime
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Kimi Linear: An Expressive, Efficient Attention Architecture
arxiviq.substack.comยท22hยท
Discuss: Substack
๐ŸงฉAttention Kernels
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[R] TempoPFN: Synthetic Pretraining of Linear RNNs for Zero-Shot Timeseries Forecasting
reddit.comยท11hยท
โšกONNX Runtime
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A Beginnerโ€™s Guide to Getting Started with add_messages Reducer in LangGraph
langcasts.comยท2dยท
Discuss: DEV
๐Ÿค–AI Coding Tools
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Finetuning Open-source models with Opus, Sonnet 4.5 and Haiku 4.5
reddit.comยท11hยท
Discuss: r/ClaudeAI
๐ŸŽ๏ธTensorRT
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Quantum-Resistant Federated Learning with Homomorphic Encryption for Medical Imaging Diagnostics
dev.toยท12hยท
Discuss: DEV
๐ŸŽ“Model Distillation
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Our newest model: Chandra (OCR)
datalab.toยท12hยท
Discuss: Hacker News
๐ŸŽ๏ธTensorRT
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The middle brother in classifier development: What is RandAugment?
openaccess.thecvf.comยท9hยท
Discuss: DEV
๐Ÿ“ŠGradient Accumulation
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My ML Learning Journey: From Confusion to Building a Working Model
kaggle.comยท2dยท
Discuss: DEV
๐ŸŽ“Model Distillation
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