Pandaemonium Architecture 6.0

In this course

Geoffrey Hinton is a foundational figure in deep learning whose work on neural networks and backpropagation enabled the machine learning systems discussed throughout the course. He appears here primarily through citation chains in technical papers on generative models and language processing, representing the historical lineage of methods now central to contemporary AI. His influence functions as an implicit reference point for understanding how modern deep learning architectures trace back to earlier theoretical breakthroughs in connectionist approaches.

Mentioned in 3 readings

Andrew Brock

et al., LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS

1

We compute the IS for both the training and validation sets of ImageNet. At $128 \times 128$ the training data has an IS of 233, and the validation data has an IS of 166. At $256 \times 256$ the training data has an IS of 377, and the valid…

Illia Polosukhin, et al.

Attention is all you need

1

[14] Zhongqiang Huang and Mary Harper. Self-training PCFG grammars with latent annotations across languages. In Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing, pages 832–841. ACL, August 2009. [15] R…

Timnit Gebru and Emile P. Torres

The TESCREAL bundle: Eugenics and the promise of utopia through artificial general intelligence

1

In this way, TESCREALists have been able to divert resources toward trying to build AGI and stopping their version of an apocalypse in the far future, while dissuading the public from scrutinizing the actual harms that they cause in their a…

Appears alongside

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