The following is a conversation with Ishan Mizra,

research scientist at Facebook AI Research,

who works on self-supervised machine learning

in the domain of computer vision.

Or, in other words, making AI systems

understand the visual world with minimal help from us humans.

Transformers and self-attention

has been successfully used by OpenAI's DPT3

and other language models

to do self-supervised learning in the domain of language.

Ishan, together with Yanlecun and others,

is trying to achieve the same success

in the domain of images and video.

The goal is to leave a robot watching YouTube videos all night

and in the morning come back to a much smarter robot.

I read the blog post self-supervised learning

the dark matter of intelligence by Ishan and Yanlecun

and then listened to Ishan's appearance on the excellent

machine learning street talk podcast.

And I knew I had to talk to him.

By the way, if you're interested in machine learning

and AI, I cannot recommend the ML Street Talk podcast highly enough.

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