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I agree that in this case the animated parts of the graphics were not needed, it's an easy pitfall to be distracted by the beautiful aspects of visualisations w
by m3at 6y ago
I agree that in this case the animated parts of the graphics were not needed, it's an easy pitfall to be distracted by the beautiful aspects of visualisations when crafting them.
I feel the need to defend the author though, it's hard to make research accessible while still distilling valuable insight. I think his post on transformer networks [1] did a good job for example, and you'll appreciate the lack of animations.
[1] https://jalammar.github.io/illustrated-transformer/ https://jalammar.github.io/illustrated-transformer/
- ypcx 6y agoYes this seems like an early work in progress, compared to Jay's previous Transformer articles. In addition to your link, I've found a really good Transformer explanation here (backed by a Github repo w/ lively Issues talk): http://www.peterbloem.nl/blog/transformers http://www.peterbloem.nl/blog/transformers Additionally, there's a paper on visualizing self-attention: https://arxiv.org/pdf/1904.02679.pdf https://arxiv.org/pdf/1904.02679.pdf
- m3at 6y agoThat's a good complement, thank you for the links
- deleted 6y ago[deleted]
- ypcx 6y agoCan't edit the post anymore so adding it here - further research reading on improving the current attention model: https://www.reddit.com/r/MachineLearning/comments/hxvts0/d_breaking_the_quadratic_attention_bottleneck_in/ https://www.reddit.com/r/MachineLearning/comments/hxvts0/d_b...