The software generates a podcast known as Deep Dive, which encompasses a male and a feminine voice discussing no matter you uploaded. The voices are breathtakingly life like—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 A hundred and twenty fifth-anniversary problem into NotebookLM and made the system generate a 10-minute podcast with the outcomes. The system picked a few tales to deal with, and the AI hosts did an awesome job at conveying the overall, high-level gist of what the difficulty was about. Have a pay attention.
MIT Expertise Evaluation A hundred and twenty fifth Anniversary problem
The AI system is designed to create “magic in trade for slightly 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 software, has taken a lifetime of its personal amongst customers. The corporate is now engaged on including extra customization choices, reminiscent of altering the size, format, voices, and languages, Martin mentioned. At present it’s presupposed to generate podcasts solely in English, however some customers on Reddit managed to get the software to create audio in French and Hungarian.
Sure, it’s cool—bordering on pleasant, even—however it’s also not immune from the issues that plague generative AI, reminiscent of hallucinations and bias.
Listed below are a few of the predominant methods persons are utilizing NotebookLM to this point.
On-demand podcasts
Andrej Karpathy, a member of OpenAI’s founding group 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 sequence 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 sequence took him two hours to create, he says.
