YouTube's auto-generated captions are a great product, but one problem is that they can't tell speakers apart in podcasts with multiple people. I'm building something that also works with YouTube transcripts, and it has the same problem.
Speaking nothing of the implementation, this is a very valuable concept. I’m curious if statistically there are trends to identify in beliefs or how beliefs spread over societies. You could likely use that data to determine thought leadership and information diets and measure things like distribution, how far the Bay Area is ahead, and other meaningful data for investments, etc.
Ages ago there was a site called whizbang.com that did something like that on web sites. It tracked various corporate "about" pages and noted how stuff on them changed over time. It may have done other stuff too. It was almost unusably slow and shut down after a while. I assume someone else has the domain now and is doing something unrelated with it.
I have a friend that’s working on a claim provenance database, starting with a focus on Wikipedia and news sources but ideally it could be applied to social media fire hoses as well.
Hmm I feel like the social media aspect would be way more useful for democracies in general.
I remember reading about Switzerland’s government service that tracks each politician, their political actions - which positions they take, which laws they promote, etc. and comparing that with which companies and investments they, their famalies and their close connections have.
All quantifiable data. I always thought something like this was _essential_ for any democracy in general - follow the money and “qui bono” and all that, thought it would be cool to build one. But of course prohibitively expensive for individuals small teams. But with all the ai - this could definitely be a thing.
If it all boils down to “verifiable corruption rating” as a single sound bite, it could seriously affect public opinion I feel. Hope someone gets on that idea someday.
No they don’t - they can ‘influence’ and hope to get their agenda pushed through but no guarantee unless the politician is desperate and you’re putting forth a lot of money (aka musk when trump got re elected).
Show me how often there were lasting decisions made against one of the 'fat cats' and their companies other than to bring them to heel.
Money and politics should never mix. One man, one vote. Not one dollar, one vote. One E.M. just tossed a few hundred million on the table in order to influence the outcome of an election and nobody did anything about it. That should tell you enough.
I've been building a tool that turns YouTube videos and podcasts into searchable transcripts. But somewhere along the way, I became more interested in a different problem.
How do you keep track of what influential people actually say, and how their thinking changes over time?
Take Sam Altman, for example.
In October 2025, talking about compute, he said, "there will come a glut for sure."
In June 2026, he said, "there will be a shortage forever."
Two statements, eight months apart. There may be perfectly reasonable context behind both, but I found it interesting that there wasn't an easy way to see them together, with the original recordings.
It currently follows 20 people in AI, including Sam Altman, Dario Amodei, Alex Karp and Marc Andreessen.
Every day, it looks for new interviews, podcasts and talks where these people are actually speaking, rather than videos of other people talking about them.
For each appearance, you get a short summary, key quotes and links to the exact moments in the original recording.
The feature I'm most excited about is *"What changed".*
It compares what someone says today with their earlier statements on the same topic. You can see both quotes, their dates and the original sources.
I'm not trying to catch people contradicting themselves. People should change their minds when new evidence emerges. I just think it would be useful to have a record of how their thinking evolves.
Building it has been more challenging than I expected.
A surprising number of videos with someone's name in the title don't actually feature them speaking. Reuploads are everywhere. And getting AI to reliably attribute statements to the right person is harder than simply generating a transcript.
I've built filters to handle much of this, and every published "What changed" comparison is still manually reviewed.
It's far from perfect. Speaker identification needs work, some podcasts aren't transcribed automatically, and I'm starting with English only.
On the economics side, a transcript and summary currently cost roughly one US cent in model processing. That makes tracking a fairly large history surprisingly affordable.
Everything is free to read. You can also follow up to three people, receive updates when they speak, and ask questions like "What has Dario Amodei said about open-source AI recently?" with answers linked to the original recordings.
I'm still figuring out which part is genuinely valuable: keeping up with people, searching their past statements, or spotting changes in their views.
I'd love some feedback from HN.
Who else should I track? Would you actually use the "What changed" feature? And if you find something incorrectly attributed or summarised, please report it. I'd rather find the failures early.
There was an interview with Altman where he was talking about various regulatory policies that had been enacted, then at the end he added "but in practice none of it turned out to matter. What we didn't anticipate was that the companies became more powerful than the governments". I wish I could find it today but it seems gone
I remember reading about Switzerland’s government service that tracks each politician, their political actions - which positions they take, which laws they promote, etc. and comparing that with which companies and investments they, their famalies and their close connections have.
All quantifiable data. I always thought something like this was _essential_ for any democracy in general - follow the money and “qui bono” and all that, thought it would be cool to build one. But of course prohibitively expensive for individuals small teams. But with all the ai - this could definitely be a thing.
If it all boils down to “verifiable corruption rating” as a single sound bite, it could seriously affect public opinion I feel. Hope someone gets on that idea someday.
Money and politics should never mix. One man, one vote. Not one dollar, one vote. One E.M. just tossed a few hundred million on the table in order to influence the outcome of an election and nobody did anything about it. That should tell you enough.
Cool idea, I guess, but its just more slop to track the slop.
https://www.youtube.com/watch?v=DlTNN0gvkLM
Very funny, btw. "Can we please stop anthropomorphising the LLMs? They hate that."
I've been building a tool that turns YouTube videos and podcasts into searchable transcripts. But somewhere along the way, I became more interested in a different problem.
How do you keep track of what influential people actually say, and how their thinking changes over time?
Take Sam Altman, for example.
In October 2025, talking about compute, he said, "there will come a glut for sure."
In June 2026, he said, "there will be a shortage forever."
Two statements, eight months apart. There may be perfectly reasonable context behind both, but I found it interesting that there wasn't an easy way to see them together, with the original recordings.
It currently follows 20 people in AI, including Sam Altman, Dario Amodei, Alex Karp and Marc Andreessen.
Every day, it looks for new interviews, podcasts and talks where these people are actually speaking, rather than videos of other people talking about them.
For each appearance, you get a short summary, key quotes and links to the exact moments in the original recording.
The feature I'm most excited about is *"What changed".*
It compares what someone says today with their earlier statements on the same topic. You can see both quotes, their dates and the original sources.
I'm not trying to catch people contradicting themselves. People should change their minds when new evidence emerges. I just think it would be useful to have a record of how their thinking evolves.
Building it has been more challenging than I expected.
A surprising number of videos with someone's name in the title don't actually feature them speaking. Reuploads are everywhere. And getting AI to reliably attribute statements to the right person is harder than simply generating a transcript.
I've built filters to handle much of this, and every published "What changed" comparison is still manually reviewed.
It's far from perfect. Speaker identification needs work, some podcasts aren't transcribed automatically, and I'm starting with English only.
On the economics side, a transcript and summary currently cost roughly one US cent in model processing. That makes tracking a fairly large history surprisingly affordable.
Everything is free to read. You can also follow up to three people, receive updates when they speak, and ask questions like "What has Dario Amodei said about open-source AI recently?" with answers linked to the original recordings.
I'm still figuring out which part is genuinely valuable: keeping up with people, searching their past statements, or spotting changes in their views.
I'd love some feedback from HN.
Who else should I track? Would you actually use the "What changed" feature? And if you find something incorrectly attributed or summarised, please report it. I'd rather find the failures early.