Technological trends have a great impact on the business processes and this is mainly due to the constant evolution in technology. Therefore, businesses have taken conscious steps towards adopting these latest technological trends for numerous positive…
[Updated on 2023-01-27: After almost three years, I did a big refactoring update of this post to incorporate a bunch of new Transformer models since 2020. The enhanced version of this post is here: The Transformer Family Version 2.0. Please refer to t…
A Google interview candidate recently asked me: “What are three big science questions that keep you up at night?” This was a great question because one’s answer reveals so much about one’s intellectual interests – here are mine:
Q1: Can we imitate “th…
An overview of all the neurons in the first five layers of InceptionV1, organized into a taxonomy of ‘neuron groups.’
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Agents with a self-attention “bottleneck” not only can solve these tasks from pixel inputs with only 4000 parameters, but they are also better at generalization.
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GitHub
Redirecting to attentionagent.github.io, where the article resides.
Disclaimer: I am not an epidemiologist, but there is an interesting potentially important pattern in the data that seems worth understanding. World healthcare authorities appear to be primarily shifting towards Social Distancing. However, there is potential to pursue a different strategy in the medium term that exploits a vulnerability of this disease: the 5 day …
Continue reading “What is the most effective policy response to the new coronavirus pandemic?”
By focusing on linear dimensionality reduction, we show how to visualize many dynamic phenomena in neural networks.
What can we learn if we invest heavily in reverse engineering a single neural network?
By studying the connections between neurons, we can find meaningful algorithms in the weights of neural networks.