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their autopilot is incredible, check out this talk https://youtu.be/oBklltKXtDE I bet the hackathon would be fun even considering that they use pytorch

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I think I see some early code for some adversarial networks -- can't wait to see the outcome. Neat code, I like the variables for what the neural network is "saying" vs. "thinking" -- a great way to describe the difference between a signal and a message
pic.twitter.com/HPTnArGoN6
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ok, last visualization for Twitter, this is the best one by far. check out the code here: https://github.com/noahtren/GlyphNet …pic.twitter.com/WdQKpCtn6W
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first timelapse of evolving a visual language. interesting to see shapes go quickly from square grids to more organic patterns, almost like ink on a page.
will run again with some different parameters, hopefully to reduce checkerboard artifacts and get more distinct glyphspic.twitter.com/vs8VcAtUmNPrikaži ovu nit -
evolving an artificial alphabet that is robust to noise. model is still converging, but this snapshot is super fun. looks like ancient runes, or an alien language
pic.twitter.com/d5lAI4cPy2
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interestingly, the generated images have different underlying patterns after each run.
this is probably because the task is too easy (no noise + few unique symbols) and the neural networks quickly converge to a good solution, depending on however they were initializedpic.twitter.com/eu48ARE6M4
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implementing
@_joelsimon's Dimension of Dialogue work in TensorFlow 2 and getting some good results after just a few hours of coding
I think the real fun will begin once some noise is introduced to the communication channel. here's an example of some early gray-scale images:pic.twitter.com/Ft8ULcjjP3
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this maybe seems petty, but using hotkeys is a pretty underrated game-changer for computer work. consider if you could save 2 seconds each minute by not having to reach for the mouse: (https://www.brainscape.com/blog/2011/08/keyboard-shortcuts-economy/ …)pic.twitter.com/TMMwLPmCY2
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definitely -- just tested GPT-2 for generating metaphors and got a pretty good result (cherry-picked from 3 candidates). this will only get better with language models that are trained on knowledge graphs (see "ERNIE"
)pic.twitter.com/yFiGkrNZD3
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the level of detail in this taxonomy is awesome... also looks like they have a couple more interactive demos on the site for anyone curious https://www.holoniq.com/interactives/ was surprised to see Photomath at the top of this listpic.twitter.com/tTcMq77zQm
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agreed, my impression is that there is a whole lot of low-hanging fruit (ripe for picking
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if you are looking to get into it maybe check out this mildly entertaining vid (https://www.youtube.com/watch?v=2MK7j_O-vH8& …) or hmu a month from now, I might have an alternative -
@seanmcarroll on understanding math/physics: "my rough feeling is that there's some threshold that one crosses in abstraction when one becomes kind of like a Turing machine" (timestamp link: https://youtu.be/iNqqOLscOBY )Prikaži ovu nit -
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I think this one had two parts originally. never took bio so idk what's going onpic.twitter.com/QOmjNFkOsZ
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hopefully more people become aware of this issue and start implementing tools for interpretability. ex: Andrej Karpathy visualizing LSTM activations in natural language and source code:pic.twitter.com/jsMFYRbH7L
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this just in, I discovered that
@figmadesign has changed their gray background color within the past month. did you notice???pic.twitter.com/KnwUgTJXYf
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