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"Summarize Tech" is a similar tool: Get a summary of any long YouTube video, like a lecture, live event or a government meeting. Powered by ChatGPT. https://www
by rsiqueira 3y ago
"Summarize Tech" is a similar tool: Get a summary of any long YouTube video, like a lecture, live event or a government meeting. Powered by ChatGPT. https://www.summarize.tech/ https://www.summarize.tech/
Pros: It can summarize larger videos for free. Cons: no chat, English only, no full transcript viewer, no settings, no transcript download.
- chpatrick 3y agoHow does that handle videos longer than the token limit?
- ashellunts 3y agoSplit to smaller chunks, summarize them. Then summarize summaries.
- prettyStandard 3y agoYou might want to overlap the first pass of chunks, something could get lost at the chunk boundaries. Not any sort of expert on this sort of thing, it just seems like an obvious pitfall for the context length.
- textninja 3y agoI really like this idea. It’s basically applying similar principles as are used in image based nets - i.e. sliding window convolutional kernels - to text.
- peterhunt 3y agoI built summarize.tech Yes it's a great idea and I have a version that is basically a convolution over the transcript. It works much better than the current version - it can automatically create cohesive chapters and summaries of those chapters - however, it consumes an order of magnitude more ChatGPT API calls making it uneconomical (for now!)
- moneywoes 3y agoCan you please eli5 the difference of old and new?
- peterhunt 3y agoSure. The old one just splits the transcript into 5 minute chunks and summarizes those. The reason this sucks is because each 5 minute chunk could contain multiple topics, or the same topic could be repeated across multiple chunks. This dumb technique is actually pretty useful for a lot of people though, and has the advantages of being super easy to parallelize and requiring only 1 pass through the data. The more advanced technique does a pass through large chunks of the transcript to create lists of chapters in each chunk. Then it combines them to a single canonical chapter list with timestamps (it usually takes a few tries for the model to get it right). Then it does a second pass through the transcript, summarizing the content for each chapter. The end result is a lot more useful, but is way slower and more expensive.
- e1g 3y agoI'm inspired that this is a side project, given everything you run. Kudos.
- peterhunt 3y agoThanks for the kind words. I built it on a few cross-country plane rides and now I mostly just leave it alone. The infrastructure and tooling we have these days is so incredible.
- ralusek 3y agoThis is the standard practice already
- justinator 3y agoSummary worked flawlessly on my own video.
- axpy906 3y agoThis is way better. Than the first one. It was able to process a YouTube live video with it.
- atum47 3y agoThis is awesome. It described my video better than I can do it myself.
- beckerdo 3y agoDid very poorly at a popular Java programming video series: https://www.youtube.com/watch?v=lFbBI85oTnY https://www.youtube.com/watch?v=lFbBI85oTnY
- speedgoose 3y agoIt works very well. The premium subscription is very very expensive though.