BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Drupal//recurring_events_ical//2.0//EN
BEGIN:VEVENT
UID:12170f37-128e-435c-a5d1-337b4ccf4ac4@support.access-ci.org
DTSTAMP:20250409T152324Z
DTSTART:20250418T163000Z
DTEND:20250418T180000Z
SUMMARY:RCAC Lecture Series: Unveiling the Mystery of Deep Learning: Past, 
 Present, and Future
DESCRIPTION:April 18, 2025 12:30PM - 2:00PM Online via Microsoft Teams*For
  those local to Purdue, in-person attendance is also an option and will be
  held in Stewart Center room 279The Rosen Center for Advanced Computing (R
 CAC) is excited to host an informative short course, “Unveiling the Myst
 ery of Deep Learning: Past, Present, and Future.” This course is designe
 d to provide those who utilize artificial intelligence (AI) tools with a d
 eeper understanding of the technology, allowing them to innovate in the fi
 eld as well as optimize their workflows.Deep learning has revolutionized a
 rtificial intelligence, but its journey from early theoretical foundations
  to modern breakthroughs has been long and complex. “Unveiling the Myst
 ery of Deep Learning: Past, Present, and Future” is a lecture series tha
 t will explore the historical evolution of deep learning, tracing its orig
 ins from the early days of neural networks in the 1980s to its resurgence 
 in the 2010s and 2020s. The series will be hosted by RCAC in conjunction w
 ith Purdue’s Institute for Physical AI (IPAI). Dr. Elham Barezi, an AI R
 esearch Scientist for RCAC, will lead the course. Throughout the series, p
 articipants will obtain a comprehensive understanding of what deep learnin
 g is, how it evolved, and where it is headed. The goal is to equip partici
 pants with deeper knowledge of AI’s development, enabling them to think 
 critically about future innovations rather than just follow trends. By und
 erstanding the strengths and limitations of different deep learning techni
 ques across time, participants will be better equipped to choose the most 
 suitable approach for their specific problems and data. The lecture series
  will be split into multiple sessions, all of which will be hosted at Purd
 ue University. Session 1 was well received, with more than 80 participant
 s taking part either in-person or online. It focused on the history of dee
 p learning and AI research as a whole. Barezi took attendees through the b
 eginnings of AI research in the 1960s, “AI Winters,” and why deep lear
 ning remained dormant for decades, and how technological advancements have
  triggered its most recent rise. She also covered how deep learning has de
 veloped over time, giving the participants insight into precisely what dee
 p learning is and how it works. For those who were unable to attend Sessi
 on 1 but would like to take part in Session 2, please review the first ses
 sion recording here.Session 2: Foundations of Deep Learning: From Discrimi
 native Models to Generative AI (Upcoming)Date: Friday, April 18Time: 12:30
  PM - 2:00 PM ESTVenue: Stewart Center, Room 279The second session in the 
 series will focus on fundamental discriminative deep learning models to ex
 plore the foundations of deep learning, including CNNs, RNNs, and early at
 tention-based mechanisms before the Transformer revolution. It will cover 
 how deep networks extract and represent features, dive into autoencoders, 
 and develop an understanding of the role of deep learning in modern featur
 e engineering and representation.“Unveiling the Mystery of Deep Learning
 : Past, Present, and Future” is open to all Purdue faculty, staff, resea
 rchers, and students who want to improve their understanding of and abilit
 y to use AI tools in their work. To attend the second session in the serie
 s, please register here: REGISTRATIONThis event is intended to be in-perso
 n, but for those unable to make it on-site, you can join via a Teams link,
  here: Teams Meeting LinkFor the remaining sessions in the series, input f
 rom the participants of this first event will be used to determine ideal d
 ates, times, and locations to ensure ease of access and availability for t
 he audience.RCAC is committed to helping Purdue make the next giant leap i
 n artificial intelligence. We offer the physical infrastructure, education
 , and expert staff to support the AI work of researchers and students at P
 urdue. Whether you are looking to advance AI research itself or to harness
  the power of AI in your current projects, we have the resources you need 
 to achieve success. To learn more about our AI-related services, please vi
 sit: https://www.rcac.purdue.edu/services/datascience 
URL:https://support.access-ci.org/events/7912
END:VEVENT
END:VCALENDAR