My guest this week is Jeremiah Lowin. Jeremiah has been on the podcast a number of times over the years. He’s one of my oldest friends who has been a sounding board for me throughout my career. Today he is the founder and CEO of Prefect, which helps companies automate and orchestrate their dataflows. In full disclosure, Positive Sum is an investor in Prefect. We didn’t plan this conversation, but when OpenAI released ChatGPT, I called Jeremiah for a primer on what’s happening under the hood and how best to contextualize this product amidst the growing AI movement. We have these conversations often, but this time I decided to record it so we can all learn from someone I consider to be a leading mind in the fields of data science and machine learning. We start off in the weeds and zoom out as the discussion unfolds. Please enjoy this conversation with my friend, Jeremiah Lowin.
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For the full show notes, transcript, and links to mentioned content, check out the episode page here.
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Show Notes
[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