The software generates a podcast known as Deep Dive, which contains 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 One 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 give attention to, and the AI hosts did a fantastic job at conveying the overall, high-level gist of what the difficulty was about. Have a pay attention.
MIT Know-how Evaluate One hundred and twenty fifth Anniversary problem
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, mentioned on X. The voice mannequin is supposed to create emotive and interesting audio, which is conveyed in an “upbeat hyper-interested tone,” Martin mentioned.
NotebookLM, which was initially marketed as a research 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 the moment it’s imagined 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 is usually not immune from the issues that plague generative AI, reminiscent of hallucinations and bias.
Listed here are among the foremost methods individuals are utilizing NotebookLM to this point.
On-demand podcasts
Andrej Karpathy, a member of OpenAI’s founding crew 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.
