Why Computer Vision Is a Hard Problem for AI

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Published 2023-10-24

Computer scientist Alexei Efros suffers from poor eyesight, but this has hardly been a professional setback. It's helped him understand how computers can learn to see. At the Berkeley Artificial Intelligence Research Lab (BAIR), Efros combines massive online data sets with machine learning algorithms to understand, model and re-create the visual world. His work is used in iPhones, Adobe Photoshop, self-driving car technology, and robotics. In 2016, the Association for Computing Machinery awarded him its Prize in Computing for his work creating realistic synthetic images, calling him an “image alchemist.” In this video, Efros talks about the challenges and changing paradigms of computer vision for AI.

00:00 Why vision is a hard problem
1:18 History of computer vision
2:01 Alexei's scientific superpower
3:14 The role of large-scale data
3:37 Computer vision in the Berkeley Artificial Intelligence Lab
4:15 The drawbacks of supervised learning
4:57 Self-supervised learning
5:33 Test-time training
7:08 The future of computer vision

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All Comments (21)

@weinhardtadam1159 6 months ago

I love that with 120.000 citations, he is regarding the grad students and the next generation of scientists as his biggest achievement.
@Alex-rh5jo 6 months ago

It's great that there are professors out there that value their students as their greatest achievement!
@joaoguerreiro9403 6 months ago

As a computer scientist working in Computer Vision tasks (and other AI applications) for medical imaging processing, this video made me smile :)
@QuantaScienceChannel 6 months ago

Read more about Alexei Efros's research in a written interview by Susan D'Agostino on the Quanta website: www.quantamagazine.org/the-computing-pioneer-helpi… Quanta is conducting a series of surveys to better serve our audience. Take our video audience survey and you will be entered to win free Quanta merchandise: quantamag.typeform.com/video
@JZFeser 6 months ago

Wonderful video! I love everything this channel has made!
@xXMaDGaMeR 6 months ago

my favorite topic in CS
@brianfunt2619 3 months ago

I love how at 8:08 one of the students' phone falls out of their pocket and everyone turns and looks at it
@werwardas1 6 months ago

Thank you for the insights and this very well produced video!
@MichaelFergusonVideos 6 months ago

Wonderful! Looking forward to the future!
@greatviktor4017 6 months ago

Love this channel
@liangcherry 28 days ago

thank you for explanation!
@terryliu3635 1 month ago

Love the short video!❤
@BenMitro 6 months ago

All very interesting. I wonder if we are limiting computer vision by only considering human vision. Each other organism has vision selected to make the organism successful, and its not like ours. I wonder if there is something we can learn from this diversity of purpose for visual systems in all organisms. Alexei Efros has touched on this diversity of purpose with his own experience of vision.
@brain_respect_and_freedom 6 months ago

Thank you👍
@alirezaahmadi5018 6 months ago

so amazing.😍😍🤩🤩.good luck.
@harishhanchinal2838 6 months ago

Nice informative video.
@a4ldev933 4 months ago

Man.. I wish you were my CS professor. 👍
@Fine_Mouche 6 months ago

what about use analogue computing in the futur for AI ?
@andrewsun4385 6 months ago

Cool!!!❤❤
@presence5834 21 days ago

I had an idea when I was working on my thesis that if we have transformer for vision and a new embedding system that treat the visual data like human we can have a model that will understand the images of the universe that is beyond the computer ability of human brains such as the cosmic microwave background. But it’s an idea only😢