Compiler

• Chasing Its Own Tail

  With the massive flow of AI-generated content onto the internet, it was only a matter of time until all of those bits of data found their way back into AI models. But what do you get when generative AI models start getting their answers from that content? The Compiler team digs into AI feedback loops, and the unique challenges they present for technologists...and everyone else.

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  36:43
• Navigating Data Rights In AI

  Copyright infringement is a huge issue for AI training and use. Can LLMs give you copyrighted content? What data can you use to train and tune your own model? In this episode of Compiler, we explore who owns what when AI models learn from protected content—and why it matters.

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  38:42
• AI Building Blocks

  There’s no one AI model to rule them all. Each project has its own requirements. Where do you get started building your own model?Compiler continues its conversations with big dreamers about their big projects—and how they’re piecing together the building blocks of their AI models.

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  40:22
• Pie In The Sky

  There is a lot of excitement around AI models, but can it meet the expectations set by blockbuster movies? What’s the current inflection point between what’s feasible and what’s not?The Compiler team talks to both big dreamers and heavy adopters wading into the space, hearing their thoughts on how AI can help scale daunting work, fill in the gaps, and make the fantastic into reality. 

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  33:07
• AI 101

  Everyone’s talking about AI. Everyone says it’s the future. To find out where we’re going, we should know how we got here—and exactly what we’re working with.We hear a short history of AI development before diving into how it’s already changed the ways we learn and code.

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  40:37

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