At #EMNLP2021 Evelina Fedorenko makes a strong case to defuse criticism that neural language models cannot "think". Neither can the human language modules in the brain, she argues, based on human brain studies. #EMNLP2021livetweet
In contrast, due it's predictive coding nature, language is inherently very well-suited to communication. #EMNLP2021livetweet
As far as human brain studies suggest, language is *not suitable for complex thought*, Fedorenko concludes her keynote at #EMNLP2021, as she outlines her future research. #EMNLP2021livetweet
Great fast writeup of the main points Fedorenko's keynote by @ZhijingJin

medium.com/@zhijing-jin/l…
Thanks for the convincing keynote @ev_fedorenko, and thanks for debunking some of those old fashioned linguistic preconceptions.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Zeta Alpha @ EMNLP2021

Zeta Alpha @ EMNLP2021 Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @ZetaVector

9 Nov
In his @NVIDIAGTC keynote Jensen Huang demonstrates @NVIDIAAI leading position in powering the AI ecosystem in R&D, enterprise and edge computing, with a zillion new announcements. Here's a few notable ones.
Graph Neural Network acceleration with CUDA-X. Image
Nemo Megatron allows training GPT-3 scale Large Language Models on distributed hardware. Image
Read 5 tweets
27 Sep
Catch up on recent AI research and code highlights - join @ZetaVector this Friday 1 Oct at 15:00 CET for the monthly "Navigating Current Trends and Topics in AI" webinar.

zoom.us/webinar/regist…
Expect to learn how Pupil Shapes Reveal GAN-generated Faces, Makeup against Face Recognition, Multimodal Prompt Engineering, CNNs vs Transformers vs MLPs, Primer Evolved Transformer, FLAN, and whether MS MARCO has reached end of life neural retrieval, and much more...
Check out some of the trending topics in AI / ML twitter right now:

search.zeta-alpha.com/?q=&d=lm&sort_…
Read 4 tweets
12 Dec 20
In typical space-cowboy style, @ylecun, donning no slides, but only a whiteboard on Zoom, explains how all the various self-supervised models can be unified under an Energy Based view. #NeurIPS #SSL workshop
In fact, @ylecun sketches that the probabilistic view of loss functions for self-supervised training is harmful us as it concentrates all probability mass on the data manifold, obscuring our navigation in the remaining space. #NeurIPS #SSL workshop
En passant, @ylecun points out the trick why BYOL by Grill et al. from @DeepMind does not collapse despite the lack of negative examples: a magic batch normalization.
Read 5 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!

:(