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PyTorch
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Deep Learning, Neural Networks, GPU Computing, Model Training
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Integrate on-device AI
models
into your app using Core AI - WWDC26 - Videos
🤖
LLMs
developer.apple.com
·
2d
2 days ago
·
Hacker News
Actions for Integrate on-device AI models into your app using Core AI - WWDC26 - Videos
Ideogram 4.0
🤖
Machine Learning
ideogram.ai
·
6d
6 days ago
·
Hacker News
Actions for Ideogram 4.0
Pytorch
for
Neural
Networks
Part 9: Taking Steps Toward Better Predictions
🤖
Machine Learning
Content type:
Blog
dev.to
·
1d
1 day ago
·
DEV
Actions for Pytorch for Neural Networks Part 9: Taking Steps Toward Better Predictions
fastai: style
📉
Data Science
Content type:
Reference
docs.fast.ai
·
3d
3 days ago
·
Hacker News
Actions for fastai: style
ml-from-scratch-book/code: Companion code for Machine
Learning
From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and
PyTorch
.
🤖
Machine Learning
Content type:
Code
github.com
·
1d
1 day ago
·
Hacker News
Actions for ml-from-scratch-book/code: Companion code for Machine Learning From Scratch — 10 core ML algorithms built from scratch with NumPy, compared with Scikit-learn and PyTorch.
From Spikes to Insights: Mastering CGM Glucose Prediction with Transformers and
PyTorch
🤖
Machine Learning
Content type:
Blog
dev.to
·
2d
2 days ago
·
DEV
Actions for From Spikes to Insights: Mastering CGM Glucose Prediction with Transformers and PyTorch
vla.cpp: A Unified Inference Runtime for Vision-Language-Action
Models
🧠
Deep Learning
Content type:
Academic
arxiv.org
·
1d
1 day ago
Actions for vla.cpp: A Unified Inference Runtime for Vision-Language-Action Models
Pytorch
for
Neural
Networks
Part 6: Understanding Epochs and Loss
📈
Optimization
Content type:
Blog
dev.to
·
5d
5 days ago
·
DEV
Actions for Pytorch for Neural Networks Part 6: Understanding Epochs and Loss
apple/coreai-models
: Model export recipes, Python primitives, and Swift runtime utilities for on-device AI
🔧
Developer Tools
Content type:
Code
github.com
·
1d
1 day ago
·
Hacker News
Actions for apple/coreai-models: Model export recipes, Python primitives, and Swift runtime utilities for on-device AI
An announcement from the Steering Council regarding the JIT project
🔧
Developer Tools
discuss.python.org
·
5d
5 days ago
·
Lobsters
,
Hacker News
,
Hacker News
,
Hacker News
,
r/Python
Actions for An announcement from the Steering Council regarding the JIT project
StageFrontier: Synchronization-Aware Stage Accounting for Distributed ML
Training
🤖
Machine Learning
Content type:
Academic
arxiv.org
·
2d
2 days ago
Actions for StageFrontier: Synchronization-Aware Stage Accounting for Distributed ML Training
Show HN: One-Shot Program Generation Through Direct Memory Diffusion
⚡
Assembly Language
Content type:
Code
github.com
·
5d
5 days ago
·
Hacker News
Actions for Show HN: One-Shot Program Generation Through Direct Memory Diffusion
Inside MisoTTS, an 8B Speech
Model
Built for Voice Continuation
🤖
LLMs
hackernoon.com
·
1d
1 day ago
Actions for Inside MisoTTS, an 8B Speech Model Built for Voice Continuation
Flash Attention: what it does and why it matters
🧠
Deep Learning
Content type:
Blog
dev.to
·
9h
9 hours ago
·
DEV
Actions for Flash Attention: what it does and why it matters
nnAudio 2: Overcoming Dynamic Compilation Barriers and Transform Inconsistencies
🤖
Machine Learning
Content type:
Academic
arxiv.org
·
5d
5 days ago
Actions for nnAudio 2: Overcoming Dynamic Compilation Barriers and Transform Inconsistencies
TensorBench: Benchmarking Coding Agents on a Compiler-Based Tensor Framework
🤖
Machine Learning
Content type:
Academic
arxiv.org
·
5d
5 days ago
Actions for TensorBench: Benchmarking Coding Agents on a Compiler-Based Tensor Framework
Forgis-Labs/HEPA: HEPA: Self-supervised horizon-conditioned event predictive architecture for time series. Spotlight at FMSD @ ICML 2026.
🤖
Machine Learning
Content type:
Code
github.com
·
10h
10 hours ago
·
Hacker News
Actions for Forgis-Labs/HEPA: HEPA: Self-supervised horizon-conditioned event predictive architecture for time series. Spotlight at FMSD @ ICML 2026.
CodegenBench: Can LLMs Write Efficient Code Across Architectures?
🤖
Machine Learning
Content type:
Academic
arxiv.org
·
6d
6 days ago
·
Hacker News
Actions for CodegenBench: Can LLMs Write Efficient Code Across Architectures?
Tejas-TA/predikit: The missing bridge between your ML
models
and your AI agents.
🤖
Machine Learning
Content type:
Code
github.com
·
1h
1 hour ago
·
Hacker News
Actions for Tejas-TA/predikit: The missing bridge between your ML models and your AI agents.
Google Colab, but in your favourite terminal
🔧
Developer Tools
Content type:
Blog
dev.to
·
4d
4 days ago
·
DEV
Actions for Google Colab, but in your favourite terminal
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