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HiPerGator Symposium - Shared screen with speaker view
Tracy Gale
02:16:36
Okay...after watching this video, how many people are totally grossed out and dread your next trip to Publix?!?!
Plato Smith
02:16:56
Agree.
Jorge X. Santiago
02:17:22
Yes
Adrian roitberg ipad
02:18:36
how are you going to deal with the obvious bias danger in this project? who decides what is a hazard? you must know this will end up with people of color being targeted, right?
daviddepatie
02:21:10
That was SUPER Gross!!!!!
daviddepatie
02:22:22
If being captured, do they resolve the obvious issues?
daviddepatie
02:23:18
No wonder the packages are SEALED!
Ryan Weaver
02:26:02
this interdisciplinary approach to implementation is amazing. the simulation capability is fantastic.
Plato Smith
02:26:16
How can AI predict human behavior if developed with bias algorithms? This project reminds me of AI in Minority Report to predict crimes in advance.
Cory Lowe
02:28:10
It seems as if there is some confusion - the HazardNet project isn’t attempting to predict behavior, we are attempting to detect coughing in retail stores so that employees can respond and clean up the area or provide people with masks.
Adrian roitberg ipad
02:29:19
you explicitly mentioned police! come on....
Read Hayes
02:29:20
We have no data indicating any racial group commits more tampering or aggression than another; and a very diverse group of participants are involved in creating the dataset to train possible models. The model will ID possible tampering with or aggressing against others. We're working to protect victims.
Plato Smith
02:29:40
My mistake. Thanks for clarification. Pardon.
Ryan Weaver
02:30:18
this agricultural food based approach could be very useful within the context of GIS mapping and health issues.
Bryan Kolaczkowski
02:30:36
definitely a good approach to generate 'simulated' data; the researchers can 'control' participants and avoid detection biases associated with race or other factors. Overall nice approach!
Christine Vivian
02:30:42
Yes! A good model
Read Hayes
02:32:08
Community members serving as police are sometimes called by fellow citizens to protect place users against intimidating and dangerous behavior including intentional infection threats and actions.
Bryan Kolaczkowski
02:44:13
red queen!
Tracy Gale
02:46:31
Rabin, very interesting data, thank you for presenting.
Sanjib Katuwal
02:46:37
Very informing talk, Rabin. Thank you!
Nitya Singh
02:47:05
Very informative and interesting talk Rabin, Thanks
Ryan Weaver
02:55:34
great way to make data less dirty within data input. it’s awesome.
Ryan Weaver
03:03:20
wow, these data sets overlaying with one another in conjunction with the land grant status/extension system/health system. UF is quite a powerful place to roll out some integrated real world solutions for health, climate, and equitable economic development. And, the academic/public nature in conjunction with sunshine laws really assures safety measures remain in place. it would be great to help. (ADRC systems, clinical, govt, etc). neat stuff.
Jorge X. Santiago
03:04:05
interesting data set
Tracy Gale
03:06:12
Really interesting work, Vincent! Thank you for sharing with us.
Azra Bihorac
03:06:25
Great work Vincent!
Brad Buck
03:06:28
Really great content, Vincent!
Plato Smith
03:06:41
Great presentation!
Azra Bihorac
03:07:02
Great title Dr. Davis and Dr. Roitberg
Vincent Colantonio
03:08:22
Thanks everyone!
Bryan Kolaczkowski
03:10:00
so... neural nets can theoretically learn any function composition... super cool idea to teach a NN quantum mechanics !
liwei chang
03:17:28
Nice introduction of ANI and pretty cool future work, Kate!
Bryan Kolaczkowski
03:17:41
we need full protein models!! :)
Ryan Weaver
03:18:00
that’s super cool, In could see how those quantum data points inputted could parlay answers in other complex fields.
Ryan Weaver
03:33:13
wow tremendous capabilities for shortening the life cycle of vaccines and end meds. the correlation from stucture to purpose makes a clear line to clinical study. you could overlay EMR end points and search for anomalies... really breathtaking.
Ryan Weaver
03:34:35
you could quickly revisit and expand disease state cross over with pleotrooic effects.
Plato Smith
03:36:51
Great work!
Ryan Davison
03:38:52
Spectral Energy Distribution for those that don't know
Ignacio Pickering
03:40:09
@Bryan, great talk quick question about your systems, how do you deal with merging the different intermediate representations in the layers close to the output? doesn't your network get very complex as depth increases?
Katherine Davis
03:42:50
@ Alexander Kane sorry for missing your question. it is ~ 1kcal/mol level of accuracy compared to reference level of theory
Ryan Weaver
03:45:49
wow
Ryan Weaver
03:46:50
super cool, climate energy capability and home insurance premiums 🥰
Katherine Davis
03:46:51
@ Joshua miles there are many actually, and a lot are doing some similar things to the work I am trying to accomplish. People are doing things with charges and long range interactions. Physnet, which is energies, forces, and mulitpoles I think. These are just a couple of examples
Ryan Weaver
03:49:53
amazing really, it gets into super conductors and availability of energy transfer amid power grids and available streams of energy, etc. amazing work.
Bryan Kolaczkowski
03:54:08
@Ignacio - reasoning modules get all the intermediate features; the depth of the feature space does grow linearly with # of network layers. Avoiding dense neural layers helps control parameter count.
Ryan Weaver
03:54:45
there are buoy systems which could benefit from this...
Erik Deumens
03:57:11
Why is by contradiction the most likely/prevalent? Is there an understood reason for that?
Ryan Weaver
03:59:22
this language sounds a lot like economic theory of equitable development.