The instrument generates a podcast known as Deep Dive, which contains a male and a feminine voice discussing no matter you uploaded. The voices are breathtakingly lifelike—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 try it out, I copied each story from MIT Know-how Evaluation’s A hundred and twenty fifth-anniversary subject 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 amazing job at conveying the final, high-level gist of what the difficulty was about. Have a pay attention.
MIT Know-how Evaluation A hundred and twenty fifth Anniversary subject
The AI system is designed to create “magic in trade for slightly little bit of content material,” Raiza Martin, the product lead for NotebookLM, stated 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 initially marketed as a examine instrument, has taken a lifetime of its personal amongst customers. The corporate is now engaged on including extra customization choices, resembling altering the size, format, voices, and languages, Martin stated. At the moment it’s presupposed 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 additionally it is not immune from the issues that plague generative AI, resembling hallucinations and bias.
Listed here are among the primary methods persons are utilizing NotebookLM thus far.
On-demand podcasts
Andrej Karpathy, a member of OpenAI’s founding group and beforehand the director of AI at Tesla, stated on X that Deep Dive is now his favourite podcast. Karpathy created his personal AI podcast sequence known as Histories of Mysteries, which goals to “uncover historical past’s most intriguing mysteries.” He says he researched matters utilizing ChatGPT, Claude, and Google, and used a Wikipedia hyperlink from every matter because the supply materials in NotebookLM to generate audio. He then used NotebookLM to generate the episode descriptions. The entire podcast sequence took him two hours to create, he says.
