The ESPHome Display Handbook: From Simple DIY to Ready-to-use Devices
seeedstudio.com·10h
🏎️TensorRT
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PyTorch Team Introduces Cluster Programming
i-programmer.info·56m
📜TorchScript
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SK hynix Roadmap 2029-2031: When memory becomes a strategic battleground
igorslab.de·13h
🔍Nsight
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Reliability assessment of multi-performance system incorporating multiple common buses and transformation devices
sciencedirect.com·3h
⏱️Benchmarking
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One Terra After Another - My First SFF Build
pcpartpicker.com·10h·
Discuss: r/sffpc
🏗️Build Systems
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Moving past speculation: How deterministic CPUs deliver predictable AI performance
venturebeat.com·2d
🧠CPU Architecture
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A portable picokernel for async I/O
ryansepassi.com·3d·
Discuss: Hacker News
📊Profiling Tools
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The best AI inference for your project. Blazing fast responses.
dev.to·19h·
Discuss: DEV
⚡Flash Attention
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Don't let these 3 CPU specs trick you into paying more
xda-developers.com·22h
⚡Flash Attention
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Gated DeltaNet (Linear Attention variant in Qwen3-Next and Kimi Linear)
sebastianraschka.com·1d·
Discuss: r/LLM
👁️Attention Optimization
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Development Trends and Architecture Evolution of AI Agents
dev.to·1d·
Discuss: DEV
🤖AI Coding Tools
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Most universal tools for learning embedded
reddit.com·6h·
Discuss: r/embedded
📉Model Quantization
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Get Ready for Clojure, GPU, and AI in 2026 with CUDA 13.0
dragan.rocks·5d·
Discuss: Hacker News
⏱️CUDA Events
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Amazon Secures $38 Billion Deal to Host OpenAI's NVIDIA GB200/GB300 AI Servers
techpowerup.com·1d
🔗NCCL
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Intel's killed-off BMG-X3/X4 GPUs: 3D stacked die, up to 40 GPU cores, 512MB Adamantine cache
tweaktown.com·1d
🔧PTX
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The Science of AI Internal State Awareness
responseawareness.substack.com·3h·
Discuss: Substack
🤖AI Coding Tools
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Experiences with NVIDIA RTX 5070 Ti vs AMD RX 9070 XT on Arch Linux (Gaming + AI workloads)
reddit.com·3h·
Discuss: r/archlinux
🎯GPU Kernels
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Building Resilient Event-Driven Systems: Lessons from the Distributed Trenches
dev.to·11h·
Discuss: DEV
🌐Distributed Computing
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Predicting Encoding Energy from Low-Pass Anchors for Green Video Streaming
arxiv.org·13h
🔗Kernel Fusion
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AI Progress Should Be Measured by Capability-Per-Resource, Not Scale Alone: A Framework for Gradient-Guided Resource Allocation in LLMs
arxiv.org·13h
📊Gradient Accumulation
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