Comment by Rohin Shah - My snapshot: https://elicit.ought.org/builder/xPoVZh7Xq Idk what we mean by "AGI", so I'm predicting when transformative AI will be developed instead. This is still a pretty fuzzy target: at what point do we say it's "transformative"? Does it have to be fully deployed and we already see the huge economic impact? Or is it just the point at which the model training is complete? I'm erring more on the side of "when the model training is complete", but also there may be lo...| www.alignmentforum.org
This page was built by Mailchimp, but it's not loading correctly at the moment. We're aware of the problem and working to fix it.| mailchi.mp
Humans and evolution have tried to solve many of the same problems---storing energy, turning sunlight to energy, moving physical joints, detecting photons, computing... Humans usually solve these problems worse than evolution. But compared to my initial estimates, the gap between human engineer...| Google Docs
Deep learning (DL) creates impactful advances following a virtuous recipe: model architecture search, creating large training data sets, and scaling computation. It is widely believed that growing training sets and models should improve accuracy and result in better products. As DL application domains grow, we would like a deeper understanding of the relationships between training set size, computational scale, and model accuracy improvements to advance the state-of-the-art. This paper presen...| arXiv.org