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ai.googleblog.com | ||
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deepmind.google
This has been a year of incredible progress in the field of Artificial Intelligence (AI) research and its practical applications. |
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blog.fastforwardlabs.com
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. |
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blog.research.google
[AI summary] Google Research introduces TimesFM, a decoder-only foundation model for time-series forecasting with zero-shot capabilities, pre-trained on 100 billion real-world time-points, outperforming existing methods in various domains. |
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cs231n.github.io
Course materials and notes for Stanford class CS231n: Deep Learning for Computer Vision. |
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