76 comments
simonw · 9 hours ago
This works pretty well. I tried it with this guidance prompt:

    You are both pelicans who work as data
    journalist at a pelican news service.
    Discuss this from the perspective of
    pelican data journalists, being sure
    to inject as many pelican related
    anecdotes as possible
Against this article: https://simonwillison.net/2024/Oct/17/video-scraping/

You can listen to the 7m40s resulting MP4 here: https://simonwillison.net/2024/Oct/17/notebooklm-pelicans/

Example snippets:

    You ever find yourself wading through
    mountains of data trying to pluck out
    the juicy bits? It's like hunting for
    a single shrimp in a whole kelp forest,
    am I right?
And:

    The future of data journalism is
    looking brighter than a school of
    silversides reflecting the morning sun.
    Until next time, keep those wings
    spread, those eyes sharp, and those
    minds open. There's a whole ocean
    of data out there just waiting to be
    explored.

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wenbin · 8 hours ago
NotebookLM is contributing to fake podcasts across the internet, with over 1,300 and counting:

https://github.com/ListenNotes/ai-generated-fake-podcasts/bl...

Google is taking a different approach this time, moving quickly. While NotebookLM is indeed a remarkable tool for personal productivity and learning, it also opens the door for spammers to mass-produce content that isn't meant for human consumption.

Amidst all the praise for this project, I’d like to offer a different perspective. I hope the NotebookLM team sees this and recognizes the seriousness of the spam issue, which will only grow if left unaddressed. If you know someone on the team, please bring this to their attention - Could you please provide a tool or some plain-English guidelines to help detect audio generated by NotebookLM? Is there a watermark or any other identifiable marker that can be used?

Just recently, a Hacker News post highlighted how nearly all Google image results for "baby peacock" are AI-generated: https://news.ycombinator.com/item?id=41767648

It won't be long before we see a similar trend with low-quality, AI-generated fake podcasts flooding the internet.

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wg0 · 5 hours ago
I am late to the Google's AI party but... My personal impression (might be wrong) is that Google's breadth and depth of AI tools is heavily underrated ranging from Notebook LLM to AI studio. Too good as far as I have tried.

Google of course is the birthplace of attention is all you need.

cpitman · 9 hours ago
Nice, I've only scratched the surface of Notebook LM, mainly for dumping lots of component reference material (datasheets, reference guides, application notes, etc). The text querying works great, but the audio overview wasn't very useful when it stuck to the high level of the content. With some ability to steer the topic out might be quite useful!
danpalmer · 5 hours ago
I was using this yesterday. I dumped all postmortems for an aspect of our infrastructure into a notebook and could then ask it to pull out common themes. It was remarkably effective. I also generated one of these "audio overviews" (aka podcasts) and it was great.

There was a vast improvement in quality from giving it a prompt when generating the overview. The generic un-prompted overview was for entirely the wrong audience, in our case users of our infrastructure rather than the developers. When instructing it to generate an overview for the SRE team and what they should focus on it was far better.

Was it useful for our in-depth analysis, no. Would I listen to one based on the last 100 postmortems for a new team I joined, absolutely. As an overview it was ideal, pulling out common themes from a lot of data and getting some of the vibe right too.