Chapter
The Copyright Debate Around AI Training Data
1:29:28 - 1:33:30 (04:02)
The copyright implications of AI training data are worth discussing, especially as companies like Apple and Google hold proprietary data sets that could affect the output of AI models. Absent unique data or hand-tuning weights, the same data sets will converge to the same output, raising questions about copyright protection.
Clips
This podcast episode raises ethical and financial questions about the future of AI and copyrighted training data, discussing the implications for companies like Google and introducing the idea of scalable infrastructure for emerging applications and services.
1:29:28 - 1:31:42 (02:13)
Summary
This podcast episode raises ethical and financial questions about the future of AI and copyrighted training data, discussing the implications for companies like Google and introducing the idea of scalable infrastructure for emerging applications and services.
ChapterThe Copyright Debate Around AI Training Data
EpisodeE110: 2023 Bestie Predictions!
PodcastAll-In with Chamath, Jason, Sacks & Friedberg
The use of the same data set without hand-tuning weights will eventually lead to the same outputs, except when there is asymmetrically different data involved.
1:31:42 - 1:33:30 (01:48)
Summary
The use of the same data set without hand-tuning weights will eventually lead to the same outputs, except when there is asymmetrically different data involved. Fair use, non-commercial use, parity, and education are protected under machine learning laws and regulations.