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Teaser image to We are (still?) not giving data enough credit

 

Munich AI Lectures

We are (still?) not giving data enough credit

Alexei A. Efros, UC Berkeley

   17.07.2024

   6:00 pm - 8:00 pm

   Bayerische Akademie der Wissenschaften, Plenarsaal, 1. Stock, Alfons-Goppel-Straße 11, 80539 München

On behalf of our partners at the Bavarian AI network baiosphere, the MCML cordially invites you to the first Highlight Lecture of the year as part of the Munich AI Lectures.

For most of Computer Vision’s existence, the focus has been solidly on algorithms and models, with data treated largely as an afterthought. Onlyrecently did the discipline finally begin to appreciate the singularly crucialrole played by data, but even now we might still be underestimating it.

In this talk, Alexei A. Efros from UC Berkeley will begin with some historical examples illustrating theimportance of large visual data in human and computer vision. He will thenshare some of their recent work demonstrating the power of very simple algorithms when used with the right data, including visual in-contextlearning and visual data attribution.

Please register for the event.

Organized by:

baiosphere

Bavarian Academy of Science and Humanities

Helmholtz Munich

LMU Munich

TUM

AI-HUB LMU

ELLIS Munich Unit

Konrad Zuse School of Excellence in Reliable AI

MCML

Munich Data Science Institute TUM

Munich Institute of Robotics and Machine Intelligence TUM

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