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In mid 2022, a small team within Google Labs had a big idea: an app that would deploy our advanced language models to help people with research, thinking and writing, all grounded in sources they had on hand. Trawling through the docs and slides and links you deemed relevant to a project, it would helpfully find and synthesize the info you needed. Then known as Project Tailwind, it would be released the following July as NotebookLM.
“The first prototype was built in six weeks, with four to five people working on it part-time,” says Steven Johnson, who’s been on NotebookLM since those early days. “But the potential was clear from the beginning.” Two years later, that potential is being realized. NotebookLM has been one of our breakout AI successes, helping everyone from researchers trying to make sense of piles of papers, to college students corralling sources for a thesis and generating study guides.
“One of the reasons NotebookLM has been so successful is the simplicity of the creation process,” says Ani Mohan, group product manager on NotebookLM. “You have all these interesting sources in front of you and don’t need to think very hard about what to make. You can just turn whatever’s in front of you into something even more helpful for learning and understanding.”
Another reason? The team hasn’t stopped working to improve it. “Our team always says we’re aiming for the intersection point of the newly magical and the actually useful,” Steven says. “We look at both the amazing new things that are possible with AI, but also listen closely to our users to figure out what’s most helpful for them.”
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