Incredibly narrow margin on this poll, with some insightful comments. Personally, it seems very much fair use to me, as long as the training data is not entirely from the same author and the model isn't created for competing with some author.
@reza_zadeh
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Fair Use Legal Opinion for Machine Learning with Copyrighted Works
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Some country legal systems have already opined that it is Fair Use https://
project-disco.org/intellectual-p
roperty/011823-israel-ministry-of-justice-issues-opinion-supporting-the-use-of-copyrighted-works-for-machine-learning/
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Copyrighted Data Training for Generative AI Models Falls Under Fair Use
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Using copyrighted data as training data for generative AI model training falls under "Fair Use" clause:
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AI fears versus current algorithmic manipulation reality
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“AI is gonna take over the world and brainwash all of us!!!” Meanwhile, simple probability distributions already control millions of people, manipulating their emotions, keeping them up all night, & destroying their lives.
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2023 Tech Wishes: AI, Learning, Video, Open Models, Robotics
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In 2023, may your: – Generative AI produce beautiful images & text
– Active Learning framework ask the right questions – generations be as beautiful as image
– Model be OSS without censors
– Robotics simulation be faithful to real world Happy New Year everyone! -
Software Importance Surpasses Robotics in Future Vision
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A guess: The future used to smell more like robotics circa 2000-2010, now everyone realizes good software is more important for the future
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Active Learning: The Year of Breakthrough for Machine Learning Systems
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Active learning can enable machine learning systems to: 1) Adapt to changing conditions 2) Learn from fewer labels 3) Keep a human-in-the-loop for most difficult examples 4) Achieve higher performance. AL has been around for decades, 2023 might finally be the takeoff year.
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Generative AI to Revolutionize Active Learning Through Uncertainty
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With recent advances in generative AI, Active Learning is primed for a major breakthrough. When an algorithm is unsure of correct label for some part of encoding space, it can actively generate from that section to get input from a human.
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Universities Need Dedicated Machine Learning Departments
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Every university should have a dedicated Machine Learning department. The field will continue to become a pillar of human knowledge almost as fundamental as mathematics.
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Detecting Out-of-Distribution Data: Impossibility and Learnability Theorems
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Outstanding paper at #NeurIPS22 main idea: is it possible to figure out when test data is coming from classes unknown during training? First they prove an impossibility theorem, then give positive/constructive results to characterize learnability of OOD. https://
openreview.net/pdf?id=sde_7Zz
GXOE
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