Linking pages
- It Looks Like You’re Trying To Take Over The World · Gwern.net https://www.gwern.net/Clippy 274 comments
- May 2020 News · Gwern.net https://www.gwern.net/newsletter/2020/05#gpt-3 200 comments
- Taming the Tail: Adventures in Improving AI Economics | Andreessen Horowitz https://a16z.com/2020/08/12/taming-the-tail-adventures-in-improving-ai-economics/ 75 comments
- Why I'm lukewarm on graph neural networks - SingleLunch https://www.singlelunch.com/2020/12/28/why-im-lukewarm-on-graph-neural-networks/ 47 comments
- The transition to clean energy is accelerating https://www.tsungxu.com/clean-energy-transition-guide/ 11 comments
- From Vision to Language: Semi-supervised Learning in Action … at Scale – Google AI Blog https://ai.googleblog.com/2021/07/from-vision-to-language-semi-supervised.html 0 comments
- Biological Anchors: A Trick That Might Or Might Not Work https://astralcodexten.substack.com/p/biological-anchors-a-trick-that-might 0 comments
Linked pages
- [1712.01815] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm https://arxiv.org/abs/1712.01815 573 comments
- OpenAI Status https://status.openai.com 195 comments
- [1706.03762] Attention Is All You Need https://arxiv.org/abs/1706.03762 145 comments
- https://cdn.openai.com/dota-2.pdf 34 comments
- [1905.11946] EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks https://arxiv.org/abs/1905.11946 10 comments
- [1512.03385] Deep Residual Learning for Image Recognition http://arxiv.org/abs/1512.03385 6 comments
- http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf 4 comments
- Renewable energy: getting to 100% requires cheap energy storage. But how cheap? - Vox https://www.vox.com/energy-and-environment/2019/8/9/20767886/renewable-energy-storage-cost-electricity 4 comments
- [2005.04305] Measuring the Algorithmic Efficiency of Neural Networks https://arxiv.org/abs/2005.04305 4 comments
- [1608.06993] Densely Connected Convolutional Networks https://arxiv.org/abs/1608.06993 3 comments
- https://newsroom.intel.com/wp-content/uploads/sites/11/2018/05/moores-law-electronics.pdf 0 comments
- [1704.04861] MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications https://arxiv.org/abs/1704.04861 0 comments
- [1707.01083] ShuffleNet: An Extremely Efficient Convolutional Neural Network for Mobile Devices https://arxiv.org/abs/1707.01083 0 comments
- [1602.07360] SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and &ampampampampampampampampampampampampampampampampampampampampampampampampampampampampampampampLT0.5MB model size https://arxiv.org/abs/1602.07360 0 comments
- AI and compute https://openai.com/blog/ai-and-compute/ 0 comments
- [1605.07146] Wide Residual Networks http://arxiv.org/abs/1605.07146 0 comments
- [1409.4842] Going Deeper with Convolutions http://arxiv.org/abs/1409.4842 0 comments
- [1812.06162] An Empirical Model of Large-Batch Training https://arxiv.org/abs/1812.06162 0 comments
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