The instrument generates a podcast known as Deep Dive, which encompasses a male and a feminine voice discussing no matter you uploaded. The voices are breathtakingly sensible—the episodes are laced with little human-sounding phrases like “Man” and “Wow” and “Oh proper” and “Maintain on, let me get this proper.” The “hosts” even interrupt one another.
To check it out, I copied each story from MIT Know-how Evaluate’s 125th-anniversary issue into NotebookLM and made the system generate a 10-minute podcast with the outcomes. The system picked a few tales to give attention to, and the AI hosts did an important job at conveying the final, high-level gist of what the problem was about. Have a hear.
MIT Know-how Evaluate a hundred and twenty fifth Anniversary difficulty
The AI system is designed to create “magic in trade for just a little little bit of content material,” Raiza Martin, the product lead for NotebookLM, said on X. The voice mannequin is supposed to create emotive and fascinating audio, which is conveyed in an “upbeat hyper-interested tone,” Martin stated.
NotebookLM, which was originally marketed as a study tool, has taken a lifetime of its personal amongst customers. The corporate is now engaged on including extra customization choices, comparable to altering the size, format, voices, and languages, Martin stated. At present it’s purported to generate podcasts solely in English, however some customers on Reddit managed to get the instrument to create audio in French and Hungarian.
Sure, it’s cool—bordering on pleasant, even—however it is usually not immune from the issues that plague generative AI, comparable to hallucinations and bias.
Listed below are among the principal methods individuals are utilizing NotebookLM to this point.
On-demand podcasts
Andrej Karpathy, a member of OpenAI’s founding workforce and beforehand the director of AI at Tesla, said on X that Deep Dive is now his favourite podcast. Karpathy created his personal AI podcast collection known as Histories of Mysteries, which goals to “uncover historical past’s most intriguing mysteries.” He says he researched subjects utilizing ChatGPT, Claude, and Google, and used a Wikipedia hyperlink from every subject because the supply materials in NotebookLM to generate audio. He then used NotebookLM to generate the episode descriptions. The entire podcast collection took him two hours to create, he says.
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