Mind Readings: Same is Lame Even in Generative AI

Mind Readings: Same is Lame Even in Generative AI

In today’s episode, you’ll discover why the current trend of using AI to generate identical-sounding podcasts is a major mistake. You’ll learn how the ease of using tools like NotebookLM has led to a sea of sameness, diminishing brand differentiation. You’ll explore how to avoid this trap and leverage AI to create unique and engaging content that truly stands out from the crowd. I’ll show you how easy it is to replicate the technology, giving you the tools to create something truly different.

Mind Readings: Same is Lame Even in Generative AI

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Machine-Generated Transcript

What follows is an AI-generated transcript. The transcript may contain errors and is not a substitute for watching the video.

In today’s episode, my friend Jay Baer famously said, “Same is lame.” This is incredibly true. When everyone does the same thing, when everything looks, sounds, and feels the same, it’s lame. There’s no brand differentiation; nothing makes you stand out. When you create the same thing as everyone else, nothing sets you apart. People see a sea of sameness and don’t know who to buy from.

The latest AI craze is marketers using NotebookLM from Google, a rag-locked generative AI tool. This means it only answers questions about the data you give it. You upload documents and ask questions. If you’re doing academic research where you can’t afford the machine to make things up (hallucinate, in technical terms), this is a great tool. It’s fantastic because it will say it can’t answer a question. For example: “What are some ways this paper addresses long COVID?” If the uploaded paper has nothing to do with long COVID, Notebook LM will say so. This is what you want for high-risk research.

But people have glommed onto the audio overview feature, which generates a podcast-like two-host conversation summarizing your paper. I’ll play a snippet after converting it to MP3.

(Audio snippet plays)

It’s wild. We have AIs generating text, code, etc., but the final polish is missing—that step back to say, “This could be better.” Humans take that for granted; we don’t always nail it the first time, but we can usually spot what’s off. That’s the Holy Grail with AI right now. That was pretty good.

Behind the scenes, Google likely passes the document through a prompt in Gemini 1.5 (the same engine powering Notebook LM), generating a script that two voices read. These are Journey voices from Google’s text-to-speech product. They’re very recognizable.

What’s the problem? It seems like a great application of technology, and it is. But many lazy marketers are saying, “I can just put a document in and it’ll generate a podcast.” That’s fair, but it’s all the same. Hundreds of deep-dive expert podcasts have popped up in the last two weeks—all Notebook LM readouts. They all sound the same. Marketers have created a sea of sameness. Every informational podcast uses the same two neural voices from Google TTS. Nothing sets your brand apart.

You could replicate this—and I encourage you to—by taking a language model to summarize a document, have it write a script, and use a TTS model with multiple voices to read it aloud. There are open-source projects replicating Notebook LM’s functionality, giving you more control over summary length and voice selection. You could even use your own voice with a tool like 11 Labs. There’s a market for personality-free audio content—nobody expects a powerful personal brand to read the weather report. But if you’re trying to build a brand, leverage your unique voice, and unique points of view, this isn’t the tool to use.

The good news is that it’s easier than ever to stand out when everyone else is using the easy button and creating same-sounding content. That’s it for this episode. Thanks for tuning in. Talk to you soon. If you enjoyed this video, please hit the like button, subscribe, and hit the bell button for notifications. Thank you.


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Christopher S. Penn is one of the world’s leading experts on AI in marketing. Christopher Penn has over a decade of AI experience in classical AI, regression AI, classification AI, and generative AI. Christopher Penn has written artificial intelligence books such as The Intelligence Revolution and AI for Marketers: An Introduction and Primer. Christopher Penn is an AI keynote speaker around the world.



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