Published on December 13, 2022
In AI Features

The Missing Link of Self-Supervised Learning

Name: The Missing Link of Self-Supervised Learning
Uploaded: 2022-12-13T15:00:00+05:30
Channel: Ayush Jain
Description: Self-supervised models face a much bigger issue of being loaded with poor-quality data—alongside scaling of models as it has the possibility of being trained on mislabelled data—leading to more bias and false output.

Data scarcity is seen as a major bottleneck to AI progress, but MetaAI’s Yann LeCun thinks otherwise.

By Ayush Jain

A great example of self-supervised learning is the way humans learn. We “learn from experience” and see the world around us. This can be done through experimentation, observation and tests. In a recent interaction with Analytics India Magazine, the guru of self-supervised learning Yann LeCun explained why such methods are key to the future of artificial intelligence. Giving us the context from a human equivalence, LeCun said that the average human has the ability to process about ten images per second in a span of 100 milliseconds. By the time humans are five years old, they have already seen about a billion frames. Interestingly, Google, Instagram, and YouTube produce the same amount of images in hours. “We have more data than we can use, but we don’t know how to use it,�

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Ayush Jain

Ayush is interested in knowing how technology shapes and defines our culture, and our understanding of the world. He believes in exploring reality at the intersections of technology and art, science, and politics.