Happy to get this EMNLP paper by @_akpiper@RichardJeanSo and myself out there: "Narrative Theory for Computational Narrative Understanding" https://t.co/i2onKfwOvf
@Ted_Underwood Yes, almost for sure. It’s actually a problem when building new datasets for long form QA or narrative summarization because you can’t include any popular media that might have a wikipedia, goodreads, or reddit page that a pretrained model would have already consumed.
PLAY SOMETHING will show you:
✔️ A new series/film similar to one you've watched before
✔️An episode/film you’ve already watched and may want to watch again if it's been a while
✔️ An episode from a show you've started but haven't finished (it will pick up where you left off)
@peligrietzer@beausievers BART is still trained on predicting masked spans though, not reconstructing the whole input. Though it occasionally does if the span is sentence size.
For our school's day off, I spent some time learning d3.js and css to make an interactive trainee ranking graphic for #iQiyi's #YouthWithYou3. I will update it for each new ranking. Enjoy!
https://t.co/pUxl6FWUjz
#青春有你3#QCYN3#ywy3#爱奇艺
I got you something ✨nice✨ this year:
🎁 The biggest movie premieres
🎁 In theaters and on HBO Max the exact same day
🎁 Beginning December 25 with #WonderWoman1984#HBOMax#WBPictures
https://t.co/QA8MlErRYQ
*** It’s LIVE ***
I've made an index with 340 creative Machine Learning projects!
More coming every week!!
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👉 https://t.co/P7OdrKAk1X 👈
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(*・ω・)ノ🍾 YAY!!
How engaging is your streamed game? It turns out that the behavior of your viewers can help us predict gameplay engagement with top accuracy! How? Check out our new @FDGconf paper “Moment-to-moment Engagement Prediction through the Eyes of the Observer” https://t.co/UUMiU6WWrn
The way forward in AI is to focus on understanding, as opposed to mimicry.
If you want to understand the nature of life, you'd look at autopoiesis, molecular biology, DNA. If you wanted to mimic life, you'd be drawing cartoons. Big difference.
Lots of "AI" is a neural cartoon.