I had the chance to go to Vancouver for @NeurIPSConf, one of the biggest conference dedicated to Machine Learning and #AI.
It's was a big week, and in this thread I'll summarize what I learned there :-)
I liked the poster from @marielpettee about modeling dance. It's always amazing to talk directly to the person who made the research.
Also enjoyed a lot this tech to transform a rough cut and paste into a photo-realistic composition (by using a GAN).
Tuesday, another great poster session:
@NvidiaAI Nvidia presented their Few Shot video translation, following their vid2vid from last year.
youtube.com/watch?v=8AZBuyEuDqc
From @blaiseaguera talk:
“Every exponential is always the first part of a sigmoid”
👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍👍
Take that in your face Singularity. 🤣
He revealed a *VERY* promising work by @zzznah & @RandazzoEttore.
Think of game of life where the rule are neural based & learned.
Then imagine that you draw a digit, and each cell color itself to predict witch digit it is. It converge so at the end the digit has the right color
Wednesday was also the day of Yoshua Benjo's talk.
The last slide is unfortunately a summary of the talk:
Bold affirmation,
Supported by…
nothing
with WTF illustrations and simplistic legends.
It's sad, because this guy has tons of interesting things to tell and teach.
And this poster was mind bending.
What if you have a webcam that record only an object that cast shadows on a wall?
What if you want to reconstruct what is in front of the object, opposite to the camera?
What if you don’t have any pairs to do the training?
Also, I got the explanation about the “Worse is better” design principle from Zachary DeVito.
It’s another way to say “The better is the enemy of the good” witch make total sense in computer (over)engineering.
Friday, super buzy poster from @hardmaru, as always :-)
He shows that a predictive model can emerge if an agent can’t observe all time step, so have to guess the state from time to time. Optimization is only done based on the reward, with no direct comparison to the actual state
About deek fake by @GiorgioPatrini:
1) Pb is not politics, it’s making non consensual video targeting women.
2) Even if a video is not fake, someone can claim it is, there is no proof anymore
3) Analysing sensor footprint vs GAN footprint can work to detect fake
The algorithm was trained on all their previous music and generated tons of melody.
They decided they could not add notes, add harmonies, Jam or improvise.
But they could choose the instruments, transpose melodies or cut them.
And they curated their Lyrics out of text generated by @rossgoodwin
Time to conclude, here my main takeaway:
1) End to end learning lost it’s magical aura.
2) Adding prior to a network is the now cool, by selecting the right architecture.
3) Concept of regrets (how much an agent could have done better) is trending.
Overall, same conclusion than last year:
The industry will need at least a decade to take advantage of all the research done so far.
And of course, the main thing at @NeurIPSConf is all the people you can meet there.
I can’t name them all here, but that’s really the reason why you want to attend in person.
That's all folks!
And If you want to read my last year thread, it's there:
twitter.com/dh7net/status/1071947223020331010?s=20