
01:03:16
Chat bots

01:03:17
contextual analysis?

01:03:35
Text summarization

01:03:35
Screen Readers?

01:03:37
Text summarization

01:03:39
google search

01:03:39
Sentiment Analysis?

01:03:47
Generating images from text description

01:05:54
yes

01:05:54
ive heard of it

01:05:55
heard of it

01:06:00
Yes

01:07:10
yes

01:07:12
yes

01:07:13
yes

01:07:14
on my list is it good?

01:07:15
yes

01:11:35
hahaha

01:11:41
lol!

01:17:39
😂

01:18:07
Becomes a tongue twister too

01:19:20
councilmen

01:19:38
demonstraters

01:19:48
tone?

01:19:48
conceptual history with the words

01:19:50
Based on context

01:19:50
verb

01:19:56
the councilmen wouldn't want violence

01:20:37
I understand that councilmen typically don’t advocate fear

01:23:59
seems like for nlp, we will need metadata on words or context history that may not be provided by training data like a document, making it especially hard in my eyes

01:48:34
is everybody responsible for reading the paper weekly for the discussion or just the presenters?

01:53:53
Does anyone have a list of early papers in NLP/linguistics , or the ones which are really important to the early developments in the field (just basic enough to get started) ?

01:56:16
Got it .. A top down approach !

02:00:18
By the project being publication ready, should it be on the levels of EMNLP, ACL, NIPS or ACM?

02:00:49
there is canvas discussion I think

02:02:03
For the in-person meetings, is it possible to start 12 to 1:30 pm instead of 1 to 2:30pm?

02:03:19
Will there be an order for paper readings? would it be voluntary?

02:04:28
How many papers will be presented during each session? There are only 12 or 13 sessions

02:05:56
I can do it (I'm an MS student though)

02:06:00
I can also

02:07:08
No

02:07:18
yes

02:07:19
yeah

02:07:35
Simple Local Attn paper

02:08:13
I can talk about the Machine Translation Paper (Bengio et. al.) if a paper from outside the list is allowed

02:08:34
got it

02:08:51
yes

02:09:23
I can do the first one then!

02:09:30
I can talk about the gradient descent kernel machine paper

02:09:43
pre-train prompt

02:09:45
yes

02:10:32
Maybe we can fill a form with our paper of interest and collaborators

02:12:35
Very interesting course format..more exciting than typical ones.

02:13:11
thanks prof have a good day

02:13:20
Thank you prof