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laurakalbag.com | ||
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isfeed.com
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| | | | | Illustration by William Joel / The Verge Even three months after Gebru's controversial termination from the AI Ethics team, the sustained campaign of aggressive tweets and emails keeps coming Timnit Gebru had expected her colleagues to rally around her when ... | |
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www.lesswrong.com
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| | | | | Background on the events I have been thinking about this since the firing of Dr. Timnit Gebru, and yet still no one has actually written about it be... | |
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www.wired.com
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| | | | | She was a star engineer who warned that messy AI can spread racism. Google brought her in. Then it forced her out. Can Big Tech take criticism from within? | |
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blog.fastforwardlabs.com
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| | | Graph Neural Networks (GNNs) are neural networks that take graphs as inputs. These models operate on the relational information in data to produce insights not possible in other neural network architectures and algorithms. While there is much excitement in the deep learning community around GNNs, in industry circles, this is sometimes less so. So, I'll review a few exciting applications empowered by GNNs. Overview of Graphs and GNNs A graph (sometimes called a network) is a data structure that highlights the relationships between components in the data. | ||
