EPISODE · Nov 8, 2024 · 26 MIN
Understanding Open Source in AI: The New Definition Explained
from They Might Be Self-Aware · host Hunter Powers, Daniel Bishop
00:00:00 - Intro00:00:22 - The Complexity Of Open Source Software00:02:12 - Challenges In Reproducing Open-Source AI Models00:11:49 - Monetary Support For Open Source Projects00:19:00 - The Role And Relevance Of Robots.txt00:23:06 - The Ethics Of 'Do Not Train' Lists00:25:54 - Wrap Up
What this episode covers
They Might Be Self-Aware Podcast (TMBSA) - EPISODE 47 SMASH THAT SUBSCRIBE BUTTON, YA OPEN SOURCE MAVERICKS! This week, we're peeling back the layers of what "open source" really means — spoiler: it's more lock and key than open sesame these days. Are AI models truly open source, or is it just make-believe marketing magic? Should companies play benefactor and pledge cash for open-source support, or does that just miss the whole open-source ethos? And what about that trusty robots.txt file — is it your website's knight in shining armor, or just the invisible cloak everyone ignores? We also debate those "Do Not Train" lists for AI models — ultimate privacy fortress, or a mirage in the desert of data mining? Plus, what happens when you dump your art into the internet void and it ends up training Skynet? Cue the existential dread. Just another wild ride here at They Might Be Self-Aware! For more info, visit our website at https://www.tmbsa.tech/
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Understanding Open Source in AI: The New Definition Explained
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