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.
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.
AI leaders aren’t important, why not track actual politicians?
That is the plan pls upvote in the website or suggest names there, I will try to add them
They are politicians, just not elected ones
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.
thank you for your feedback, I will definitely look into it.
ahead?
You noticed that too, eh?
Lol i m not from silicon valley.
Quoting a Kai Lentit video as Dario Amodei changing his mind on regulation is peak slop.
Cool idea, I guess, but its just more slop to track the slop.
Indeed. This is not Dario Amodei, despite the caption...
https://www.youtube.com/watch?v=DlTNN0gvkLM
Very funny, btw. "Can we please stop anthropomorphising the LLMs? They hate that."
done..
I wanted to get a place where I can see get info. correctly and AI leaders changing their mind is a slop in itself.
Hi HN, I'm Gaurav.
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.