Robohub.org
 

Yann LeCun: The Next Frontier in AI (Unsupervised) | CMU RI Seminar


by
19 November 2016



share this:

Link to video on YouTube

The rapid progress of AI in the last few years are largely the result of advances in deep learning and neural nets, combined with the availability of large datasets and fast GPUs. We now have systems that can recognize images with an accuracy that rivals that of humans. This will lead to revolutions in several domains such as autonomous transportation and medical image understanding. But all of these systems currently use supervised learning in which the machine is trained with inputs labeled by humans. The challenge of the next several years is to let machines learn from raw, unlabeled data, such as video or text. This is known as unsupervised learning. AI systems today do not possess “common sense”, which humans and animals acquire by observing the world, acting in it, and understanding the physical constraints of it. Some of us see unsupervised learning as the key towards machines with common sense. Approaches to unsupervised learning will be reviewed. This presentation assumes some familiarity with the basic concepts of deep learning.




John Payne





Related posts :



Robot Talk Episode 132 – Collaborating with industrial robots, with Anthony Jules

  07 Nov 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Anthony Jules from Robust.AI about their autonomous warehouse robots that work alongside humans.

Teaching robots to map large environments

  05 Nov 2025
A new approach could help a search-and-rescue robot navigate an unpredictable environment by rapidly generating an accurate map of its surroundings.

Robot Talk Episode 131 – Empowering game-changing robotics research, with Edith-Clare Hall

  31 Oct 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Edith-Clare Hall from the Advanced Research and Invention Agency about accelerating scientific and technological breakthroughs.

A flexible lens controlled by light-activated artificial muscles promises to let soft machines see

  30 Oct 2025
Researchers have designed an adaptive lens made of soft, light-responsive, tissue-like materials.

Social media round-up from #IROS2025

  27 Oct 2025
Take a look at what participants got up to at the IEEE/RSJ International Conference on Intelligent Robots and Systems.

Using generative AI to diversify virtual training grounds for robots

  24 Oct 2025
New tool from MIT CSAIL creates realistic virtual kitchens and living rooms where simulated robots can interact with models of real-world objects, scaling up training data for robot foundation models.

Robot Talk Episode 130 – Robots learning from humans, with Chad Jenkins

  24 Oct 2025
In the latest episode of the Robot Talk podcast, Claire chatted to Chad Jenkins from University of Michigan about how robots can learn from people and assist us in our daily lives.

Robot Talk at the Smart City Robotics Competition

  22 Oct 2025
In a special bonus episode of the podcast, Claire chatted to competitors, exhibitors, and attendees at the Smart City Robotics Competition in Milton Keynes.



 

Robohub is supported by:




Would you like to learn how to tell impactful stories about your robot or AI system?


scicomm
training the next generation of science communicators in robotics & AI


 












©2025.05 - Association for the Understanding of Artificial Intelligence