
11:49
Hi, everyone - I'm a Core staff member. Just a quick note that our Code of Conduct can be found at http://www.ala.org/core/about/statement-of-conduct . Please contact me through private chat or at jlevine@ala.org if you experience or see any violations of the Code.

12:44
If you're not already a member of this interest group, you can join it at https://connect.ala.org/core/communities/community-home?CommunityKey=c6ad80f9-1866-4041-801e-a9bccb7c9a72

13:18
is there sound?

13:27
Yes, John is speaking right now

13:32
Thanks!

13:40
will the recording be available afterwards

13:57
Yes, we'll post links to the recording on the IG Week Program Schedule and in the ALA Connect group

14:18
great

26:36
this is awesome

31:59
Incredible, archival preservation!

34:37
Link to the LC Labs Newspaper Navigator: https://labs.loc.gov/work/experiments/newspaper-navigator/

35:16
Sooo, the aim here is not to rely on library-supplied metadata but the image itself?

35:55
It sounds a lot like the AI deep learning project(s) Google is running.

36:26
Lisa - yes, we train a subset of the images, and then apply the model to other images - so that library-supplied metadata is not applied to all 16M images

38:41
The implications for bibliographic work - the network collects monographic data from the publisher and constructs metadata without the cataloger having to do anything (in theory). Wow!

39:15
Yes, wow!

39:54
BERT is really promsing

40:24
If you are interested in learning more from LAM perspective, join AI4LAM at ai4lam.org

40:44
I can see a service within Makerspaces where patrons can bring in their faded diaries, photos, exc... to help create more readable items. Is this a possibility, or too expensive?

40:48
what hardware were you using

41:38
Does anyone know of library-specific AI and neural net work being done? As mentioned by others, the idea of bibliographic metadata work, for example.

44:46
@Glen. Here is a “look book” of projects done within libraries archives and museums: https://docs.google.com/presentation/d/1iWG9RpPaMlikUAe8mfVlYQeoCiNH8ct2ILFtbMI7P_o/edit?usp=sharing

45:06
Thanks Catherine!

51:09
Have any studies been done as to the accuracy of these projects. What is the accuracy rate when thousands of photographs are analyzed by this method and how accurate would it be for library material cataloging & metadata?

53:54
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57:45
Interested in bibliographic aspects

59:34
Interested in customer service chatbots or sensing technology applications

59:36
I recently attended a presentation by Brian Christian on the alignment problem. I think that is an interesting issue that fits into librarians' values and experience: reducing bias, matching the user's intent (as you touched on with chatbots and relevancy algorithms).

01:00:30
Interested in project management aspect of AI as well as chatbot applications.

01:01:44
Interested in a tech literate society, access to new technology, understanding AI effect on society

01:01:48
Also interested in mitigating bias in training.

01:01:51
Interested in the implications of AI evolution on society, ethics, and philosophy.

01:02:37
I'm interested in the applications of AI for library bibliographical applications. Also applications of chatbots.

01:02:43
Ditto what Adam DeWitt said!

01:04:43
I’m interesting in learning training datasets to supply subject headings and keywords to new metadata.

01:05:09
… to new records

01:06:28
could you comment on getting a pilot project going in a production environment / workplace vis-a-vis IT staff? given the resource heavy nature of AI training (gpu) would you recommend using personal machine or cloud instance

01:06:45
great discussion

01:07:01
Excellent question!

01:07:45
Thanks for the great presentation!

01:09:40
thank you!

01:09:41
Thank you very much!!!!

01:09:43
thank you for all this information

01:09:44
Thank you!

01:09:46
Thank you!

01:09:48
Thank you, enjoyed the presentation. I am excited about the group!

01:09:50
Thank you

01:09:51
Thank you all!

01:09:54
thank you!

01:09:54
Thank you!!

01:09:55
Thank you.

01:09:57
Thank you

01:10:00
Thank you!