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PRODID:www-utn-de//Events//DE
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SUMMARY:NUEDIGITAL: Scaling to Human-Level Visual Understanding with S
 elf-Supervised Learning
UID:1116-7f28-22fb-30499@www.utn.de
DESCRIPTION:Self-supervised learning is an approach in which AI system
 s learn from data without relying on human-labeled examples – by ide
 ntifying patterns on their own. With the rise of models like ChatGPT a
 nd multimodal systems such as SigLIP\, which are trained on vast amoun
 ts of labeled data\, an important question arises: is self-supervised 
 learning still the right path forward? This talk argues that it is. In
 spired by how humans – especially infants – learn from the world a
 round them\, self-supervised learning remains a powerful and scalable 
 paradigm. It is particularly valuable in domains where labeled data is
  scarce\, expensive\, or difficult to obtain\, such as image\, video\,
  and 3D data\, as well as multimodal applications. Despite the growing
  dominance of large multimodal models\, self-supervised approaches con
 tinue to play a key role in advancing AI capabilities. In particular\,
  we will explore why video is emerging as the next frontier – offeri
 ng unprecedented scale and richness of data. Leveraging video data ope
 ns the door to a new generation of visual AI systems with more robust\
 , human-like understanding. Please register for the event via the Nür
 nberg Digitalfestival website.  Register here In addition to register
 ing for our individual sessions\, it’s also worth taking a look at o
 ur event “5 Years of UTN: Where Nuremberg Meets Technology – Join 
 the journey to the future of AI”. Here\, you’ll have the opportuni
 ty to spend an entire afternoon at UTN with a diverse program of event
 s.
DTSTART:20260630T140000Z
DTEND:20260630T150000Z
LOCATION:Cube One (Dr.-Luise-Herzberg-Straße 4\, 90461 Nuremberg)
DTSTAMP:20260504T191628Z
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