The Infinite Loop by Nebius reports that AI scientists are rapidly developing across disciplines, prompting concerns over research diversity as they may lead to a scientific monoculture.

Abstract: Deep neural networks (DNNs) training can be difficult due to vanishing and exploding gradients during weight optimization through backpropagation. To address this problem, we propose a ...

Abstract: Recurrent Neural Networks (RNNs), including the distinguished Long Short-Term Memory Networks (LSTMs), have been shown to be effective in a wide range of sequential data problems. However, ...

‘AI scientists’ are exploding across disciplines. Will they morph what gets researched? When Google DeepMind co-founder and CEO Demis Hassabis articulated his vision for “AI scientists” that could ...

KBR and Applied Computing are using physics-informed AI to enhance energy efficiency in industrial plants. Traditional industrial operations rely on experienced engineers and controlled processes, but ...

This lecture continues on from the previous one and considers some of the issues involved in producing an effective implementation of an RNN language model. The vanishing and exploding gradient ...

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