Meta has recently launched a project called NotebookLlama, which can generate podcast-style summaries, similar to Google's NotebookLM. This project utilizes Meta's own Llama model to process uploaded text files and produce podcast-style summaries.

Firstly, NotebookLlama creates a transcript from the file (such as a PDF of a news article or blog post). It then adds "more dramatic effects" and pauses before feeding the transcript into an open text-to-speech model. Although the results do not sound as good as NotebookLM, Meta's researchers indicate that the quality can be improved with more powerful models.

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On the NotebookLlama GitHub page, they wrote: "The text-to-speech model limits its naturalness." "Additionally, another way to script podcasts is to have two agents discuss a topic of interest and outline the podcast. Currently, we use a single model to outline the podcast."

Although NotebookLlama is not the first attempt to replicate NotebookLM's podcast functionality, it remains a project worth watching. However, all AI-generated podcasts share a common issue: the problem of hallucinations, meaning that AI-generated podcasts inevitably contain some fictional content.