Explaining the New AI Paradigm

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[00:03:38] - [First question] - What a pre-trained transformer is 

[00:06:12] - What latent representation means in the context of AI models 

[00:09:57] - Models using math to interpret input data and generate images accurately 

[00:11:43] - Whether or not understanding AI complexity in light of the results they arrive at will become a black box scenario 

[00:14:13] - A high level history of the companies involved in generative AI

[00:17:51] - The precursory technology that makes generative AI art possible

[00:21:01] - What people are doing to improve AI models in between versions 

[00:26:39] - Things that are literally happening during AI training

[00:29:44] - The power dynamics and barriers to entry for building AI models

[00:33:38] - Whether or not AI models might one day function as a utility like electricity

[00:36:01] - Coding using GitHub Copilot and what it’s felt like to use it 

[00:40:30] - How he’d approach starting an AI company from scratch 

[00:44:40] - Developing this technology beyond general and into specific use cases

[00:49:44] - The secret sauce for defensibility in the AI model space 

[00:53:02] - What he’s watching more closely as the story unfolds 

[00:56:32] - Whether or not he thinks that these toolkits will eventually learn how to use other systems like Unreal Engine on our behalf