The tool generates a podcast called , which encompasses a male and a female voice discussing whatever you uploaded. The voices are breathtakingly realistic—the episodes are laced with little human-sounding phrases like “Man” and “Wow” and “Oh right” and “Hold on, let me get this right.” The “hosts” even interrupt one another.
To try it out, I copied every story from ’s A hundred and twenty fifth-anniversary issue into NotebookLM and made the system generate a 10-minute podcast with the outcomes. The system picked a few stories to deal with, and the AI hosts did an awesome job at conveying the final, high-level gist of what the problem was about. Have a listen.
MIT Technology Review A hundred and twenty fifth Anniversary issue
The AI system is designed to create “magic in exchange for just a little little bit of content,” Raiza Martin, the product lead for NotebookLM, said on X. The voice model is supposed to create emotive and interesting audio, which is conveyed in an “upbeat hyper-interested tone,” Martin said.
NotebookLM, which was originally marketed as a study tool, has taken a lifetime of its own amongst users. The corporate is now working on adding more customization options, similar to changing the length, format, voices, and languages, Martin said. Currently it’s purported to generate podcasts only in English, but some users on Reddit managed to get the tool to create audio in French and Hungarian.
Yes, it’s cool—bordering on delightful, even—but it is usually not immune from the issues that plague generative AI, similar to hallucinations and bias.
Listed here are a few of the most important ways persons are using NotebookLM to this point.
On-demand podcasts
Andrej Karpathy, a member of OpenAI’s founding team and previously the director of AI at Tesla, said on X that is now his favorite podcast. Karpathy created his own AI podcast series called , which goals to “uncover history’s most intriguing mysteries.” He says he researched topics using ChatGPT, Claude, and Google, and used a Wikipedia link from each topic because the source material in NotebookLM to generate audio. He then used NotebookLM to generate the episode descriptions. The entire podcast series took him two hours to create, he says.
