The instrument generates a podcast referred to as Deep Dive, which includes a male and a feminine voice discussing no matter you uploaded. The voices are breathtakingly reasonable—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 Expertise Evaluation’s One hundred and twenty fifth-anniversary concern into NotebookLM and made the system generate a 10-minute podcast with the outcomes. The system picked a few tales to concentrate on, and the AI hosts did a terrific job at conveying the overall, high-level gist of what the difficulty was about. Have a hear.
MIT Expertise Evaluation One hundred and twenty fifth Anniversary concern
The AI system is designed to create “magic in trade for a little bit little bit of content material,” Raiza Martin, the product lead for NotebookLM, mentioned on X. The voice mannequin is supposed to create emotive and fascinating audio, which is conveyed in an “upbeat hyper-interested tone,” Martin mentioned.
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, equivalent to altering the size, format, voices, and languages, Martin mentioned. 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, equivalent to hallucinations and bias.
Listed here are a few of the important methods persons are utilizing NotebookLM to date.
On-demand podcasts
Andrej Karpathy, a member of OpenAI’s founding staff and beforehand the director of AI at Tesla, mentioned on X that Deep Dive is now his favourite podcast. Karpathy created his personal AI podcast collection referred to 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 collection took him two hours to create, he says.
