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Podcasting 2.0 for April 17th.

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Two-fif-

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Welcome to Podcasting 2.0.

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We're back after one Friday off.

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to give you all things podcast.

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The real podcasting. All things RSS.

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board meeting of Podcasting 2.0 and the only boardroom that wasn't a sneaker company previously. I'm Adam Curry here in the heart of the Texas Hill Country and in Alabama, the man who will never

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Say hello to my friend on the other end, the one, the only, Mr. Dave!

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Jones!

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Don't say never.

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Anything's possible. Don't tempt me. This is true. This is true. This is true. How you doing, brother?

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Good. Yeah. Yeah. Doing good. I'm

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Off work today. What?

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Well, of course, we already had tax season. Yeah, tax season has come and gone. So you get three weeks of, what was it, two weeks of rest, and then it starts all over again?

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Two weeks may be generous because all the things you can't do during tax season you have to do as IT. You have to do after tax season.

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You can't make no changes during tax season. How was this tax season? Were people happy? Did they get bigger refunds because of no tax on nothing?

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No tax on that. People did get bigger refunds. Okay. It was the headlines I saw were humorous, though. It was like.

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Yes, tax refund sizes are up, but not by as much as previously thought. No, it's maybe 8% or 10%, I think. Like 11%. That's pretty good. That is pretty good. Yeah, that's not bad. I would like 11% more money.

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I'll take it. I'll take it. Yeah. I mean, like talk about making a negative out of a positive. Oh, well, typical. I was listening to.

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First ring day.

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So what? What show?

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First Ring Daily, it's a very...

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in like a niche.

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podcast about

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It's daily about.

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Microsoft stuff. It's only last like.

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Oh, okay.

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It's just, it comes up.

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eat every day.

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Another one of those things I listen to for work, but Paul Theriot was talking about.

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The insanity, just the craziness of headlines now. And like one of the ones he was quoting was.

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this headline that said um these seven things on mars will kill you instantly

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And the subtitle was, Number 5 will truly blow your mind. Oh, that sounds like AI slop right there. Oh, it totally is.

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There's seven things on Mars that could kill you. I mean, like the number – just the fact that they're – like number one is all – it's the whole thing. Like just the lack of oxygen. Well, yeah. Everything else is just a stupid gravy on top. I mean – The world is insane. Well, the world is – the internet is breaking. The internet is – It is, and I'm so happy about it. Oh, well, let's start there.

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Because there's a couple different angles. I know you've been fighting all kinds of things. I'll save the CICD prompt injection for a little bit later on, which I find very interesting, actually. I love – like I don't know how many things can happen in a single week, but this week may have been a record.

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Well, tell me about the Claude Code Gemini CLI credential theft because I is a developer now.

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until everyone got the 500.

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from the API and then suddenly I wasn't a developer anymore, which was kind of fun. What is happening? Is that because people are putting their credentials into Claude and it's getting sucked in there and spitting back or what's happening?

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You're catching me off guard. I'm not sure I know what you're talking about. Exposing GitHub credentials through PR titles.

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Modern CICD pipelines are a train wreck, says Dave, post Dave on podcast index. My bad. Yeah, you got it.

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Yeah, so...

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Pull requests. Yeah, the pull. This is a continuation. GitHub actions are having a bad day. What are GitHub actions? They're having a bad month, actually. What are GitHub actions?

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So GitHub Actions are a way that you can trigger.

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for non-developers, non-SRE sysadmin people.

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There's a thing modern code

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is distributed to a production system.

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typically based on...

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call a CI-CD pipeline, which is continuous integration, continuous deployment. Right. A typical flow would look something like this. It would be...

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there's a development server or a staging area where things are tested, then... Testing's for pussies. Live, baby. We'll do it live. Oh, you're talking to the king of modifying the production server in flight. Yes, I agree.

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We'll leave you with a – I can't do it.

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We'll do it live.

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We'll do it live! F*** it!

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That f***ing thing sucks!

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That's Dave. Dave in the dev department. Yes. I'm just less angry about it.

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um,

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Yes, the...

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So what happens is you have this staging environment or this development environment and then things are tested and they go through, tested by people and by automation.

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The changes are considered valid and good, and then you promote it to a release.

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So then you would typically do some.

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it with a version number.

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this would

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trigger a release or sometimes the release trigger is manual and then that goes once that happens this whole it kicks off a whole slew of downstream

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functions that take over.

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So once the release is finalized.

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All this, this whole, the whole process of getting it over to your production servers that are actually serving traffic to the world.

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It's almost out of it.

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Practically out of everyone's hands. It just happens. Mm-hmm.

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This is.

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Kicked off by GitHub actions. And so these GitHub actions can.

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you know, uh,

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build the project, do things like build a Docker image off the project.

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And yeah, then perhaps do a security scan to make sure no malicious packages were included as part of the build because the build is pulling from package managers. So this is all coming from a large language model triggering this through an API on GitHub?

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No, it's not large language model. This predates LLMs by a long shot. These are all just, it's code flow. It's DevOps. And it's a good idea. It's considered, you know, you could say like infrastructure as code.

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Where you're defining a set of things that need to happen every single day.

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single time.

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And instead of a human being running, just sitting there running these scripts.

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The automation takes over and

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It does, and it runs tests at each step of the way to see if anything fails before it deploys.

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You know, the idea is it can catch problems before it gets to production.

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So, I mean, the ideas involved are not bad, but.

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course there's going to be

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risks because the risks of automation are always there.

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What if somebody gets in – what if somebody figures out a way to get into your pipeline?

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And the more steps you have in that chain, the more opportunities there are for something to have.

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something malicious injected into it. And this is what happened.

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earlier

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Let's see, like earlier in March, so the first half of March, the Axios breach.

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Right. Yeah. That's what that came from.

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LLM breach, all of that stuff has started with, with.

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It wasn't GitHub Actions itself that was the problem.

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The developer accounts.

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of other

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Package repositories got breached.

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And then they were able to update the things that were called in the GitHub actions.

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those injected the malware and so or the info stealers and that sort of thing so um the the biggest one was

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Smarks, I think is what it's called. It's a security. It's a GitHub action security scan.

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And so the idea here is that you build your production.

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build your release bundle.

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then it goes through and looks for vulnerabilities in what it just built. And it's, so it's a security scanner, like an antivirus scanner. And.

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But somebody compromised that.

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And so...

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Every time that thing ran.

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It was deploying an InfoStealer into the code that you just built.

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That took place across.

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dozens of huge major repositories. I mean, we still don't know the extent of that.

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I think if I'm not mistaken, that's what took down Cisco's. I don't know if you heard about that, but Cisco's entire GitHub private GitHub repository got stolen.

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All of Cisco's proprietary code is now leaked. It's been hacked.

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That's it.

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came from that breach. So this is just a continuation of the same thing of attacking GitHub Actions.

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And this thing figured out that.

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There was a way that you could.

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Use the titles of –

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pull requests.

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to execute code.

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So you could inject a malicious pull request.

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And just the presence of that pull request would trigger the action. So like somebody, for instance, our web UI repository for podcast index. It's a great it's a good example of this. When somebody submits a pull request.

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to our website repo.

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A bunch of automatic checks happen to make sure that because the primary use case for that is people adding.

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themselves to the podcastapps.com page. And so...

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That's all based on a JSON file.

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And the GitHub action that triggers when somebody submits a pull request on that JSON file is it checks the syntax, makes sure that they did.

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everything right.

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end up pushing to production a broken JSON.

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So now, so this means that.

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this particular vulnerability.

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could have made somebody deploy a malicious pull request to your repo.

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The automatic checks happen in certain circumstances.

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If they put code in the title, that code would execute.

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could scrape your data and send back.

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that they're not supposed to have. It's a disaster. This whole thing is so fragile. We don't...

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We built systems over the past decade.

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that are not ready.

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for the way

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for how fast things are.

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Deployed.

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Deployed and yeah, because like.

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It's that famous phrase like from Jurassic Park, you know, you.

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All you thought about is whether you could. You didn't stop to think about whether you should. Yeah.

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And that's what's happening really here is these package managers or package repositories. Like now every time I build something, I just hold my breath.

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I'm not kidding. Like I was building something this morning. I was doing a – I was doing a –

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some work on the local aggregator for Godcaster this morning.

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I needed a composer package.

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Put into.

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because that runs Laravel.

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So it's all handled with Composer, which is PMP.

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PHP.

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I did composer, you know, install.

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I just had this anxiety the whole time watching the screen. I'm like, what's about to take over my computer?

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This is code coming from some... In that sense...

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Honestly.

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What we've been – we complain about AI creating code that we don't read.

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or that we don't understand or we never look at? Oh, I mean, that's, if you think about package repositories.

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That's been going on for 15 years. We have no idea.

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What is in most of these? Just all these apps install. Boom.

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Well, you know that.

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The

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apt-get

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The Debian repositories, because it – I feel more comfortable that those have been –

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vetted more thoroughly and they're also older packages you don't typically like especially on an lts release what you're getting is typically a package that's been frozen at a version that's actually pretty old

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Comparatively speaking, so those Linux repo, Linux distro package repositories are actually

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Those do not bother me.

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much i would much rather get one of those than something off like npm or p or pip

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I mean, or PiPi. Those things have, oh man. I mean, like those things are a train wreck, right?

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So I've been thinking about all of these and you'll tell me which one you want to talk about. But all of these different clearly vibe coded systems that have been been brought up to create podcasts. And, you know, it's like the big topic.

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The only thing it's bad is just it's just it's flooding systems. You know, podcasting doesn't have a discovery mechanism. You know, I really.

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I do have some thoughts on this cloning of titles or close to cloning on titles, close to cloning on images. I have some thoughts on that.

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But in general, all of these, you know, so, okay, if someone happens to be searching.

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like, oh, I have my podcast app. I'm going to search for a podcast because I don't have anything to listen to.

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I'll bet you that that's a very low.

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amount of people that are doing that.

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positive. Yeah. I mean, so if they're searching for a particular podcast, yeah, that of course is a problem. If there's a whole bunch of clone feeds and things that look like it sounds like.

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But I don't think anyone's really, I mean, this is a business that is not going to last very long.

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You know the the true way to stop it is to just stop giving away free accounts Or or you know free account, but not if AI or whatever

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Um,

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Uh...

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If anything, it's going to ruin podcast monetization, download-based monetization.

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Because advertised like, well, it's all scam. I don't think anyone's listening to this stuff. So I.

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I view that as generally good, but not good for people like Dave.

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It's because I was trying to update. We get to do this, the podcast. And I'm like, it's not happening. Why is it not happening? And then I waited for an hour, 45 minutes, an hour. Like, this is ridiculous. I don't know what's happened.

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Of course, I thought it was my fault, but it's an RSS.com feed. So those are usually good. I check it. The feed is there. I check the raw feed. Feed's good. So then I wind up issuing a reset, which I don't like doing because I know that it takes a lot of extra resources. And that did get through and that did update the feed, not in the way it should have. And then you come back later and say, well, this is the reason, which is

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crazy process that was, was it searching fountain feeds? What exactly was going on there?

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I don't – I can't give you a step-by-step of exactly – so what I – you mentioned something Wednesday about we get to do this, not updating.

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This being very or being stuck scanning. Yeah, that's why. Well, I couldn't tell if it was stuck. It just it said scanning and it wasn't doing it. So.

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And so later, a little bit later, I looked at it and I was like...

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By that time, it had gone through.

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I don't...

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really see anything. That was probably after my reset though.

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I don't.

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don't know to see this is all very hard to understand because what so i look of course the first thing i do usually in a situation like that is i go look at cloudflare and see if we're just getting you know

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And I didn't see anything that looked out of the ordinary based on – what I mean is out of the ordinary based on what I have seen lately.

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I mean, we're serving a lot.

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I wish we had kept

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I wish I had kept historical traffic charts.

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because

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What we're serving lately is a lot. What's a lot, Dave? Let's see.

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Thank you.

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analytic. Here we go.

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I'm just looking at our Cloudflare stats.

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So over the last 24 hours, we've served.

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322 gigs of

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9.2 million API requests.

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Let's see over the last seven days. This is down significantly.

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from what it was yesterday.

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You can see on the chart it just – when Oscar fixed their issue, it just – it fell off.

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Over the last seven days, we've served two terabytes of data and 75 million API requests.

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I

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How many podcasts?

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are there.

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Well, most of this is just a handful. I can promise you. Yeah.

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But they – so –

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The that's what I mean, that's so up from what it used to be, let's just say a year and a half ago.

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In one sense, I'm really happy that we hold up so well. Stop the hammering!

213
00:20:28,892 --> 00:20:31,652
I mean, I'm really, it makes me.

214
00:20:32,028 --> 00:20:43,491
I'm glad that we're able to handle so much traffic. I mean, that's pretty. That's amazing. That's pretty awesome. Yes. Yeah. Considering the shoestring budget we're on. For sure. Yeah. And.

215
00:20:43,963 --> 00:20:56,675
But then at the same time, it happened so gradually. It's like the boiling frog thing. I never really thought, well, maybe some of this stuff coming from these other places is not organic.

216
00:20:57,147 --> 00:20:59,500
So, like, fountains...

217
00:20:59,655 --> 00:21:07,663
Traffic had been going up steadily for a while, and I had noticed I had noted that in the back of my mind. And I just figured.

218
00:21:09,544 --> 00:21:14,031
serving lots of data. And I'm like, okay, that's fine.

219
00:21:15,624 --> 00:21:17,776
Then what happened was I went.

220
00:21:18,951 --> 00:21:20,784
Oscar was like, hey, you know, this...

221
00:21:21,480 --> 00:21:23,344
Podcast is not updating.

222
00:21:24,872 --> 00:21:27,056
I looked and I was like, I wonder how many.

223
00:21:27,912 --> 00:21:33,263
I wonder how many things are in the queue for the aggregators to poll. I wonder what the queue length is for weight.

224
00:21:34,279 --> 00:21:40,112
I go and I look. That's where you just discovered it. 500,000 podcasts. Waiting for what? To be updated?

225
00:21:40,455 --> 00:21:43,215
to be pulled, to be aggr- - Oh my goodness.

226
00:21:43,655 --> 00:21:47,056
be requested and downloaded for aggregation.

227
00:21:48,455 --> 00:21:49,231
Whoa.

228
00:21:49,640 --> 00:21:50,352
I mean, we.

229
00:21:51,463 --> 00:21:53,296
I mean we pull something like –

230
00:21:54,567 --> 00:21:59,500
something roughly around 2,500 podcasts a minute.

231
00:21:59,784 --> 00:22:03,632
That should not – the Q should never be that big. Right.

232
00:22:04,231 --> 00:22:14,544
It should not even – I mean the most I ever really see it get up to is about 1,600, 1,500, and that's just when we get a flood of things all in, and that usually clears out.

233
00:22:17,223 --> 00:22:28,175
minutes and then it's back to its steady state. This was off the chart. And so I was like, whoa, what in the world? So I go into Cloudflare and I start filtering by what is hitting.

234
00:22:28,615 --> 00:22:35,279
Like, where's this traffic coming from? So looking at all the paths that are getting hit and the one one I saw up near the top was the.

235
00:22:36,168 --> 00:22:38,448
Hub notify API endpoint.

236
00:22:39,016 --> 00:22:44,271
Hmm. Which originally, so this goes back a ways. This is the.

237
00:22:44,680 --> 00:22:46,288
Mastodon stuff

238
00:22:47,592 --> 00:22:49,039
No, so...

239
00:22:51,271 --> 00:22:56,271
If this goes back to the very beginning of the index.

240
00:22:56,647 --> 00:22:57,551
2020.

241
00:22:59,407 --> 00:23:17,400
This endpoint was created to support WebSub. Right. Okay. Yes. PubSub. WebSub. Yeah. PubSub. Yes, exactly. That's why it's called PubNotify. So it's notified. This is a mechanism for us to subscribe to WebSub servers.

242
00:23:17,872 --> 00:23:23,160
for those web sub servers to then ping us when a feed updates.

243
00:23:23,824 --> 00:23:28,567
that Pub Notify has to be an unauthenticated API.

244
00:23:31,152 --> 00:23:32,279
just by default.

245
00:23:33,839 --> 00:23:34,296
And so.

246
00:23:35,248 --> 00:23:45,528
That is for web sub, but over the years we've said, okay, well, you can use it for other things if you just want to ping us and let us know that, hey, a feed changed and we need...

247
00:23:46,799 --> 00:23:55,927
Just send your request to here and you can either use the podcast index feed ID or you can use the podcast index feed URL or the podcast feed URL.

248
00:23:56,847 --> 00:23:59,900
Either one of those will work and we'll just stick it in the queue and pull it.

249
00:24:01,720 --> 00:24:08,096
And that thing should never be at the top of any list of traffic.

250
00:24:08,920 --> 00:24:10,592
And what it was, was.

251
00:24:12,407 --> 00:24:17,728
Fountain was hitting us, was hitting that endpoint with feed IDs.

252
00:24:18,423 --> 00:24:20,480
At the rate of like.

253
00:24:20,983 --> 00:24:21,920
millions.

254
00:24:22,807 --> 00:24:26,624
every 24 hours. And so this

255
00:24:27,096 --> 00:24:28,735
you know, Oscar went in and

256
00:24:29,175 --> 00:24:30,816
I started checking his system.

257
00:24:31,703 --> 00:24:32,160
He was like, oh.

258
00:24:32,663 --> 00:24:51,456
He's like a bot is just killing us. And so he was getting slammed with some sort of automated bot crap. Someone trying to scrape, scrape podcasts through him, which indirectly came to us. Yeah, exactly. It's my my I don't know the way their system is set up, but.

259
00:24:52,215 --> 00:24:55,872
I can imagine designing a system such that.

260
00:24:58,872 --> 00:24:59,900
If.

261
00:25:00,119 --> 00:25:03,552
certain sequence of events happens on

262
00:25:04,344 --> 00:25:15,360
It gets requested or a certain number of things happen and it just triggers – it makes your app think maybe there's a new episode. And so then it just sends a request to us to –

263
00:25:15,735 --> 00:25:16,672
for us to check.

264
00:25:18,135 --> 00:25:31,872
And normally I'm cool. I'm totally fine with that. Like if somebody has a reason to think that there is a new episode that we need to go get, hey, ping us. Let us know. But this was just somebody abusing their system, and it had this downstream effect.

265
00:25:34,680 --> 00:25:39,776
So anyway, so I blocked that traffic and then he fixed, you know, he blocked it on his side and then we got it.

266
00:25:40,440 --> 00:25:41,215
other in this.

267
00:25:43,288 --> 00:25:46,208
through and just cleared all those backlogs because I'm sure.

268
00:25:48,983 --> 00:25:51,392
thousand of those requests weren't even real.

269
00:25:52,855 --> 00:25:57,279
And so then I cleared all that out and then just kind of sort of reset everything back to zero.

270
00:25:57,751 --> 00:25:59,900
everything's working again.

271
00:26:00,311 --> 00:26:01,152
There's.

272
00:26:01,880 --> 00:26:04,000
This is the sort of stuff that...

273
00:26:05,367 --> 00:26:07,168
that you have to deal with.

274
00:26:08,023 --> 00:26:10,880
And it's been every single day.

275
00:26:11,831 --> 00:26:14,175
And you have a wife who has needs.

276
00:26:15,543 --> 00:26:19,456
She does. Funny enough, she does.

277
00:26:19,831 --> 00:26:27,839
Yeah, this this is what I was afraid of last year. I was afraid that this year was going to be the beginning of this.

278
00:26:28,440 --> 00:26:33,824
It has not – it is panned out exactly. It is not disappointed is what you're going to say.

279
00:26:34,231 --> 00:26:38,144
the way that I thought it would. This is the year of slop.

280
00:26:39,384 --> 00:26:41,791
Just abusive bots.

281
00:26:43,192 --> 00:26:43,935
see

282
00:26:45,175 --> 00:26:49,920
What I've had to – there's just been so much that's happened this week, man. Like I had to –

283
00:26:50,392 --> 00:26:52,127
finally just started working on the

284
00:26:54,776 --> 00:26:55,488
I'm like, uh.

285
00:26:55,864 --> 00:26:59,700
classifier stuff. Yeah, I saw that. Yeah, the LLM is

286
00:26:59,791 --> 00:27:05,592
classifying it as spam? Yeah. And I'm not happy with the way that's working, but it is, it is working.

287
00:27:06,703 --> 00:27:10,680
thrilled with it and I'm going to be making this is going to be a long process.

288
00:27:11,311 --> 00:27:19,672
Well, it's hard. I mean, we used to do that on heuristics, and now it's on who knows. I mean, I have a...

289
00:27:20,976 --> 00:27:22,456
I have a Quen model running.

290
00:27:23,375 --> 00:27:25,112
that ingests

291
00:27:26,511 --> 00:27:48,215
the result of RSS feeds that I have set up. And so I probably get about, each run gets about 350 stories. And the Quen model then has to determine if the stories are worth even looking at. And that's hard. It's hard to tweak that just the right way.

292
00:27:49,327 --> 00:27:51,096
Oh, oh yeah.

293
00:27:52,304 --> 00:28:00,799
I don't know if you want to go ahead and dig into this. I mean, I do want to talk about the spam classifier stuff, but maybe you have something else you want to hit. No. Well, actually.

294
00:28:01,084 --> 00:28:10,851
kind of flows into uh what james and sam were talking about for the first half hour of power this power

295
00:28:11,228 --> 00:28:29,668
I haven't listened yet, so I don't know what they're saying. This Light Knot Studios, who copied more than 75 podcasts and created AI slop versions that are obviously different audio, different knot copies of.

296
00:28:29,947 --> 00:28:44,195
the podcast themselves, but you know, uh, history podcast names, you know, all the, uh, very close to the original, uh, successful podcast names. So the only thing I wanted to say, because I heard.

297
00:28:45,467 --> 00:28:46,467
You know, it's.

298
00:28:48,476 --> 00:29:01,700
It's not nice, first of all, but I have some experience in this that I just wanted to share because I don't know if James has mentioned it, but I kind of want to turn that upside down for anyone who's dealing with this.

299
00:29:02,624 --> 00:29:06,344
Well, actually, two experiences. One, a lot of people.

300
00:29:06,912 --> 00:29:09,063
Start naming their podcast No Agenda.

301
00:29:10,720 --> 00:29:18,279
And I'd say most not maliciously. He's like, yeah, this is a great idea. We'll call our podcast. No agenda. We'll talk about sports.

302
00:29:18,847 --> 00:29:19,463
Well.

303
00:29:19,840 --> 00:29:29,128
I mean, if you are serious about what you're doing and you have a podcast, you need to trademark the name. You just need to trademark the name. It's not. Y'all do, right? Oh, yeah.

304
00:29:29,695 --> 00:29:49,864
Because now, I mean, every single time this happens, we have to send a DMCA takedown request. We just did one yesterday on Spotify. Spotify is reasonably quick to respond, but we have had to get lawyers involved more than 10 times at least, maybe 20 times.

305
00:29:49,983 --> 00:29:59,989
Because people are like, well, I don't want to do that. And, you know, I've done it to mainstream. Even my neighbor. She's like, no agenda with Laura Logan. Like, no.

306
00:30:00,380 --> 00:30:05,859
No, you can't do that. Oh, yeah. That was a you sent that to Fox News, right? Yeah. That's when she was on Fox.

307
00:30:06,332 --> 00:30:13,604
And then all of a sudden it popped up again in our podcast. Anyway, that's one thing. But I have a lot of experience with something called the Lanham Act.

308
00:30:14,332 --> 00:30:37,892
And if you, as long as you have your podcast trademarked, and so that would be the name, that's most important. You can also do some trademarking on imaging, but it depends. You have to have kind of the same image. But I have experience with this from the 1994 MTV Networks versus Curry lawsuit, which...

309
00:30:37,915 --> 00:30:53,284
was filed by MTV, because I had MTV.com, which they gave me permission to use. They didn't care. They didn't care about the internet. We have the AOL keyword. Curry, do whatever you want. That was literally what they said. We have the AOL keyword.

310
00:30:53,723 --> 00:30:55,844
interested in this domain name stuff.

311
00:30:56,220 --> 00:31:00,200
So I had the domain name and I used at MTV.com.

312
00:31:00,259 --> 00:31:08,076
personal site, but it was definitely MTV oriented. So the lawsuit that they filed was under the Lanham Act, which was correct, and they were right.

313
00:31:08,483 --> 00:31:27,180
So we settled because, you know, it turns out they had said you can go ahead and do this and they hadn't covered their their backsides. And honestly, if they just said, hey, can we have the domain name back? I would have given it to him. So that turned into them suing me under the Lanham Act. I countersued. We settled out of court. Neither party has any further comment.

314
00:31:27,875 --> 00:31:28,683
I'm still smiling.

315
00:31:29,572 --> 00:31:46,923
But the Lanham Act is there specifically. In fact, I'll give you the little paragraph about it. Federal trademark law protects brands from consumer confusion. Cortez, would a reasonable consumer be confused about who made, sponsored or endorsed a product?

316
00:31:47,652 --> 00:32:00,500
Courts look at how similar the marks are, how related the goods are, evidence of actual confusion. And it covers domain squatting. That actually came from my, you know, it was jurisprudence, my lawsuit with MTV.

317
00:32:00,559 --> 00:32:04,791
brand impersonation, cloned content designed to look like the real thing.

318
00:32:05,327 --> 00:32:25,048
So the Lanham Act is the way to go. Forget about DMCA and all this stuff and going to the hosting company. You have to go to a lawyer and you have to threaten them with Lanham Act litigation. And that is the end of it.

319
00:32:25,519 --> 00:32:28,503
If not, then you have to follow through.

320
00:32:28,976 --> 00:32:42,968
So I just want everyone to know that there is in the United States, at least I'm not sure about outside the United States, but the Lanham Act is the way to go. And any of these podcasts clearly can create confusion. It is obvious to prove that.

321
00:32:43,440 --> 00:33:00,000
one legal letter should make them go away. If they don't, then you'll have to take it a step further, but you will win that. And unfortunately, if you're in a business, and I've defended all kinds of copyright cases, including the first Creative Commons.

322
00:33:00,028 --> 00:33:15,076
copyright case. I was the first one to fight that in court. I won. I got zero money, but I won. Wasn't really the point. Yeah. So the Lanham Act is the way to go for anyone who's dealing with this. And we just have to do it. The thing that.

323
00:33:15,708 --> 00:33:18,115
that, uh, that I'm worried about.

324
00:33:18,715 --> 00:33:19,364
And.

325
00:33:20,604 --> 00:33:41,764
I know that Spreaker has a lot of this going on. And so when you combine creating Lanham Act offenses, which a lot of people just don't know how to defend, won't defend, shrug their shoulders, whatever, combined with bots submitting hundreds of thousands of podcasts, the only thing I'm a little worried about.

326
00:33:42,107 --> 00:33:57,955
is that at some point a company like Spotify will say, well, that's been ruined. You should just come to us and we'll take care of you. And we're safe here because you can do it with our API and trusted partners and you're good to go.

327
00:33:58,779 --> 00:34:00,099
That's the thing that I'm worried about.

328
00:34:00,127 --> 00:34:05,768
And maybe I'm giving them an idea, but it's also possible they're thinking about this themselves.

329
00:34:06,304 --> 00:34:08,135
I'm not clear on what you mean.

330
00:34:08,864 --> 00:34:21,288
If the RSS infrastructure becomes so polluted with similar names and similar topics and, you know, and we just can't fight the spam or the slop or.

331
00:34:21,695 --> 00:34:23,815
We don't have a way to help people.

332
00:34:24,224 --> 00:34:28,519
find what they're looking for when they're looking for it in that particular case.

333
00:34:30,016 --> 00:34:32,295
I just I don't want.

334
00:34:33,119 --> 00:34:41,672
companies to go, well, you know, like we're the guys, you know, come to us, we'll protect you. And it just moves away from RSS. That's what I'm talking about.

335
00:34:42,784 --> 00:34:44,103
The only –

336
00:34:44,896 --> 00:34:48,775
I can see the logic of how you're getting there.

337
00:34:50,559 --> 00:34:53,960
The only thing I would say that may...

338
00:34:54,463 --> 00:34:59,400
is I think that the closed platforms are also fighting the exact same battle.

339
00:34:59,811 --> 00:35:16,907
I don't think they can make that guarantee. They could say it, but they couldn't live up to it. OK. Because like YouTube is is full. I mean, it's just a slop factory now. Yeah, it is. Spotify is a slop factory. They're all these. Yeah. All these these closed systems are battling the exact.

340
00:35:17,315 --> 00:35:18,059
problem.

341
00:35:18,596 --> 00:35:19,659
And.

342
00:35:20,260 --> 00:35:23,436
I want to be fair to –

343
00:35:24,036 --> 00:35:26,635
all of the hosting companies.

344
00:35:27,396 --> 00:35:27,851
there

345
00:35:29,668 --> 00:35:33,516
It may seem like I'm giving Spreaker a hard time because they...

346
00:35:33,891 --> 00:35:39,083
They have just become such a factory for slop. Slop factory.

347
00:35:39,748 --> 00:35:43,884
They're a slop factory. They've become a slop factory. They're a slop slut.

348
00:35:46,083 --> 00:35:47,244
This.

349
00:35:47,876 --> 00:35:49,804
The problem is.

350
00:35:50,500 --> 00:35:50,987
that

351
00:35:52,547 --> 00:35:59,300
They are really between a rock and a hard place. This is a difficult thing. The light not.

352
00:35:59,360 --> 00:36:19,911
Studio thing I think that happened to RSS calm. Yeah the and this morning I saw I taught a whole slew of of just scam garbage With phone numbers to call and all the others a full-on scam. Yeah

353
00:36:22,175 --> 00:36:23,175
fishing campaign.

354
00:36:23,583 --> 00:36:28,903
I saw this hitting multiple hosts, Buzzsprout, Podio.

355
00:36:31,423 --> 00:36:33,800
Podbean. It was like three different hosts.

356
00:36:34,592 --> 00:36:35,208
This

357
00:36:35,871 --> 00:36:39,463
The rock and a hard place that the hosting companies are in.

358
00:36:39,967 --> 00:36:42,887
You have to do a free –

359
00:36:43,264 --> 00:36:48,967
Even if you don't have a full, a true free tier, Black Spreaker and RSS.com and Red Circle.

360
00:36:49,503 --> 00:36:51,175
Even if you don't have that.

361
00:36:51,583 --> 00:36:53,096
you still at least

362
00:36:53,728 --> 00:36:56,039
It's table stakes now that you have to have.

363
00:36:56,896 --> 00:36:57,960
trial period.

364
00:36:58,496 --> 00:36:59,199
14 days.

365
00:36:59,199 --> 00:37:01,028
30 days, whatever it is.

366
00:37:01,403 --> 00:37:02,916
You just have to.

367
00:37:03,771 --> 00:37:05,284
A lot of stuff can happen.

368
00:37:05,724 --> 00:37:07,396
a 14-day or 30-day trial.

369
00:37:08,028 --> 00:37:09,539
a whole lot of abuse.

370
00:37:10,396 --> 00:37:12,708
I know for a fact.

371
00:37:15,068 --> 00:37:17,668
There are people in the hosting companies

372
00:37:18,940 --> 00:37:19,396
I've taught.

373
00:37:21,500 --> 00:37:22,563
doing that are

374
00:37:23,355 --> 00:37:28,420
Every single day they spend, who knows, an hour or more?

375
00:37:29,467 --> 00:37:33,539
scraping through the trial accounts trying to get rid of this stuff.

376
00:37:34,012 --> 00:37:41,923
404, these scam feeds. It's hard, man. It's hard.

377
00:37:42,331 --> 00:37:53,347
What I'm doing on my side is trying to make that job for them easier. I want it to be.

378
00:37:54,844 --> 00:37:56,003
I want us.

379
00:37:56,764 --> 00:37:59,500
I want our visibility across hosts.

380
00:37:59,976 --> 00:38:04,271
a benefit to the hosts. Of course. Yes, of course.

381
00:38:04,967 --> 00:38:08,528
Because we can see something happening over here on Podbean.

382
00:38:09,096 --> 00:38:22,639
Before it hits buzzsprout. Exactly. Before it metastasizes. Well, I think, you know, we have hosting companies like RSS.com. I'm just going to be a douche about it now for a second.

383
00:38:22,983 --> 00:38:29,295
RSS.com, Buzzsprout, the boys and girls over there, Blueberry.

384
00:38:29,639 --> 00:38:30,992
who support the index.

385
00:38:33,159 --> 00:38:37,807
So we should be transistor. Yes, we should be supporting them.

386
00:38:38,376 --> 00:38:41,840
The other ones, I don't know so much, Dave.

387
00:38:44,488 --> 00:38:47,407
I mean, I'm just saying.

388
00:38:47,880 --> 00:38:59,300
I understand the sentiment. I just – The evil, mean sentiment that cropped up in me? Yes, yes. That's what that was. Yeah, I did not – that's not what I said. That's what I said. That's what you said.

389
00:38:59,360 --> 00:39:09,639
I understand that sentiment, but also, like you said, the larger goal, though, is that we want to get some sort of traction on this.

390
00:39:10,751 --> 00:39:17,000
Most of this is coming from two motives.

391
00:39:18,175 --> 00:39:20,807
obvious one is

392
00:39:21,663 --> 00:39:22,599
Add.

393
00:39:23,423 --> 00:39:24,711
Revenue.

394
00:39:25,728 --> 00:39:30,887
You throw up a slop cast, you get ad revenue. Slop cast. Yeah, from DAI.

395
00:39:31,456 --> 00:39:32,104
Yeah.

396
00:39:32,927 --> 00:39:38,215
You get that? That's one. That's the obvious one. The other one is SEO spam. Yeah.

397
00:39:39,007 --> 00:39:41,480
And this is just plain Jane.

398
00:39:41,920 --> 00:39:45,895
SEO web traffic scamming that has been with us forever.

399
00:39:47,775 --> 00:39:51,112
If I could make one recommendation.

400
00:39:51,648 --> 00:39:53,224
to the podcast hosting companies.

401
00:39:53,952 --> 00:39:54,760
be this.

402
00:39:57,311 --> 00:39:58,728
If you're on a free tier.

403
00:39:59,423 --> 00:39:59,989
you

404
00:40:00,123 --> 00:40:01,603
or you're in a trial account.

405
00:40:02,876 --> 00:40:09,123
Do not give those accounts any web presence whatsoever.

406
00:40:09,916 --> 00:40:16,099
Right. And also and also mark them as such in the feed. Hmm.

407
00:40:16,891 --> 00:40:22,724
So that everybody knows to ignore them until they become an actual.

408
00:40:23,963 --> 00:40:25,027
paid.

409
00:40:25,500 --> 00:40:28,516
some sort of like a legit podcast

410
00:40:29,467 --> 00:40:30,403
getting

411
00:40:30,940 --> 00:40:33,860
You've verified that they are an actual.

412
00:40:34,748 --> 00:40:36,387
Human of some sort.

413
00:40:37,884 --> 00:40:44,931
Because I know some of the hosting companies try to block the SEO problem by just having their –

414
00:40:45,980 --> 00:41:00,000
Podcast web pages that they generate automatically by having them blocked from Google indexing but that doesn't stop it because Those podcasts feeds then flow into other places like Apple podcasts and podcast index

415
00:41:00,219 --> 00:41:02,340
They flow all over the place.

416
00:41:02,811 --> 00:41:09,603
And then they'll pop up in other spots in the web, get indexed and turned into HTML.

417
00:41:10,043 --> 00:41:10,532
Thank you.

418
00:41:11,260 --> 00:41:20,516
It's not just the straight SEO from the page itself. It's like second-order SEO down the line.

419
00:41:21,500 --> 00:41:27,619
And what I'm seeing now, I mean, it's not new, but it's been going on for a long time. And I'm looking at this stuff for like...

420
00:41:28,411 --> 00:41:30,211
every single day for a while.

421
00:41:31,195 --> 00:41:32,420
And what I'm seeing.

422
00:41:33,179 --> 00:41:33,923
is

423
00:41:35,452 --> 00:41:38,211
trends. I'm beginning to see the trends myself.

424
00:41:40,027 --> 00:41:48,164
And the other SEO, it's not just scam SEOs like online gambling sites in Vietnam.

425
00:41:48,699 --> 00:41:49,923
It's witches.

426
00:41:50,619 --> 00:41:51,139
deal and

427
00:41:52,027 --> 00:41:54,403
Asian gambling sites are a big thing.

428
00:41:54,844 --> 00:41:58,019
It's not just that. It's also –

429
00:41:58,523 --> 00:41:58,980
Is that?

430
00:42:00,059 --> 00:42:01,731
I'm starting – I'm seeing –

431
00:42:02,588 --> 00:42:06,083
Like local businesses. Oh wow.

432
00:42:06,780 --> 00:42:20,867
There was one, it was like PJ's heating and air service in Miami, Florida or something like that. And it was on like four different hosting companies. Well, you know what is big now with the Claude Code type?

433
00:42:21,467 --> 00:42:31,811
things is people are selling. In fact, one of our no agenda producers, not saying that he's doing this, but they'll sell you a marketing system in a box.

434
00:42:32,347 --> 00:42:41,764
And so you log in, they got a little front end on it, and it's got some Claude code stuff underneath. Claude bot.

435
00:42:42,139 --> 00:42:43,108
And.

436
00:42:43,739 --> 00:42:48,355
So it'll build you a website and then it'll do a marketing campaign for you.

437
00:42:49,340 --> 00:42:59,800
And I think that's what we're seeing here is, oh, okay, I can get a marketing campaign for five bucks a month. All right, so I'll use this. And then it's going off and it's doing its SEO business.

438
00:42:59,800 --> 00:43:01,851
And it's doing it through stuff like that.

439
00:43:03,123 --> 00:43:06,588
I just dropped a search.

440
00:43:08,724 --> 00:43:10,844
in the boardroom is a search for

441
00:43:11,380 --> 00:43:17,500
You just search in podcast index for PJ slash PJ space HVAC. I see it.

442
00:43:18,324 --> 00:43:20,123
That's what this is. Wow.

443
00:43:20,659 --> 00:43:23,291
One of them's on, let's see, that one's on Buzzsprout.

444
00:43:24,596 --> 00:43:27,452
Some of these have been 404'd and we just have

445
00:43:27,795 --> 00:43:29,371
We just haven't killed him yet.

446
00:43:30,195 --> 00:43:32,155
This one's on SoundCloud.

447
00:43:32,916 --> 00:43:35,644
This is all the same local business.

448
00:43:36,371 --> 00:43:37,563
Let's see where this one is.

449
00:43:38,324 --> 00:43:41,340
This one's another one on SoundCloud.

450
00:43:43,219 --> 00:43:44,251
Where's this one?

451
00:43:44,628 --> 00:43:46,043
This may be on speaker.

452
00:43:47,731 --> 00:43:59,400
There's three different ones on SoundCloud. But I saw this same one, PJHVAC. I know I saw it on Spreaker and at least one other place. So this was across four different hosting companies.

453
00:43:59,715 --> 00:44:02,347
just a trial. It's abusing the trial account. Right.

454
00:44:02,916 --> 00:44:05,708
Well, I'm glad to see that SoundCloud finally has some traffic.

455
00:44:08,195 --> 00:44:24,748
PJ Mac, HVAC service and repair company in Pennsylvania. Wow. So, I mean, like there's clearly something that is. Yes. Somebody like you, like what you're talking about out there that is just sort of like SEO in a box. Mm hmm.

456
00:44:25,092 --> 00:44:39,307
Part of what we're going to do is we're going to throw you out on all the podcast platforms, and you're not really a podcast. We're just going to make one placeholder episode with – that just says – with our phone number and contact information. It's just – it's abuse.

457
00:44:40,163 --> 00:44:40,811
It's –

458
00:44:41,155 --> 00:44:43,980
It's service abuse because it's not what.

459
00:44:44,324 --> 00:44:46,284
intent of these services are.

460
00:44:48,420 --> 00:44:57,228
Daniel, that PJ Mac HVAC show, that may not be an Apple podcast, but I can tell you for a fact that there are.

461
00:44:57,764 --> 00:44:58,956
Thousands.

462
00:44:59,844 --> 00:45:01,003
of shows.

463
00:45:01,635 --> 00:45:09,291
Of this of varying scam types in Apple podcast because I send the links to them.

464
00:45:10,467 --> 00:45:22,668
I find them in Apple Podcasts also. So this is not – it doesn't – it's not just a matter of the way we do things by scraping up everything.

465
00:45:24,003 --> 00:45:27,692
This stuff is getting into Apple Podcasts also.

466
00:45:28,579 --> 00:45:33,003
And I can bring receipts because I've got them in my email where I've sent them to Ted in the past.

467
00:45:34,755 --> 00:45:41,547
So these people are good at – these scammers and SEO people –

468
00:45:41,956 --> 00:45:43,916
They're very good at this stuff.

469
00:45:44,867 --> 00:45:45,931
They're very good at it.

470
00:45:46,788 --> 00:45:56,427
And if you can get yourself onto Apple Podcasts, you've hit the jackpot. Well, a lot of that's automatic.

471
00:45:57,507 --> 00:45:59,500
The automatic is...

472
00:46:00,519 --> 00:46:02,384
you know, through a lot of the hosting companies.

473
00:46:03,079 --> 00:46:04,304
That is SEO gold.

474
00:46:05,320 --> 00:46:08,208
Because now you're coming off of an Apple.com top-level donut.

475
00:46:09,351 --> 00:46:11,215
Right, right.

476
00:46:13,063 --> 00:46:14,288
So, I mean, like...

477
00:46:15,880 --> 00:46:18,927
What I'm going to have to do.

478
00:46:20,103 --> 00:46:23,376
Let's see. Let me go over.

479
00:46:24,135 --> 00:46:28,175
just sort of what is happening right now, what I've done this week to try to

480
00:46:28,871 --> 00:46:30,159
get some sort of

481
00:46:31,367 --> 00:46:32,304
on this.

482
00:46:37,608 --> 00:46:38,480
So.

483
00:46:39,239 --> 00:46:42,320
What's happening now is.

484
00:46:43,079 --> 00:46:47,088
There's a client process that runs on.

485
00:46:49,447 --> 00:46:51,536
my local system here.

486
00:46:52,519 --> 00:46:53,168
because

487
00:46:54,471 --> 00:46:55,791
Obviously we're running on a budget.

488
00:46:56,583 --> 00:46:58,512
I need to do local inference for this.

489
00:46:59,911 --> 00:47:00,751
So.

490
00:47:01,960 --> 00:47:03,887
have a client processes running

491
00:47:04,360 --> 00:47:08,367
is looking at the recent slash new feeds.

492
00:47:13,768 --> 00:47:17,231
It pulls the most recent.

493
00:47:18,184 --> 00:47:20,079
shows added to the index in the last

494
00:47:21,896 --> 00:47:24,047
Yeah, it's very cool. It's a cool page.

495
00:47:24,711 --> 00:47:30,992
Yeah, it runs every one of them through the inference.

496
00:47:32,007 --> 00:47:33,679
through the Gemmaform model.

497
00:47:34,887 --> 00:47:37,295
What are you running the Gemma 4 on?

498
00:47:38,215 --> 00:47:39,568
It's, uh...

499
00:47:40,168 --> 00:47:42,543
Llama CPP on a Mac Mini. Okay.

500
00:47:43,304 --> 00:47:43,920
And, uh...

501
00:47:44,360 --> 00:47:50,768
So it's running on – it runs through that, does a classification, and there's a big – there's this –

502
00:47:51,175 --> 00:47:52,144
script.

503
00:47:53,992 --> 00:47:56,047
has the notion of

504
00:47:56,391 --> 00:47:59,800
bad feeds. I'm just going to put them in two buckets. There's actually six.

505
00:48:01,523 --> 00:48:09,244
But let's just for simplicity's sake, it has the notion of this is a bad feed, this is a good feed. I'm just going to, let's not get into the meanings of those things.

506
00:48:13,108 --> 00:48:20,956
And so then it runs like you – it has a local SQLite database that keeps all these things tagged.

507
00:48:22,003 --> 00:48:25,083
Here's an example of a bunch of feeds that we've done.

508
00:48:25,748 --> 00:48:27,003
to nuke

509
00:48:27,668 --> 00:48:30,235
here's a bunch of examples of fees that are legit

510
00:48:31,860 --> 00:48:32,988
It just makes.

511
00:48:33,779 --> 00:48:36,827
It sends it to the LLM, makes an inference with a jag.

512
00:48:37,172 --> 00:48:37,916
prompt.

513
00:48:39,891 --> 00:48:40,764
says

514
00:48:41,172 --> 00:48:45,851
yes, this is most likely spam or this is most likely legit. And so you get a, you get a.

515
00:48:46,996 --> 00:48:48,891
decision that's been made.

516
00:48:50,324 --> 00:48:51,483
calls the

517
00:48:52,211 --> 00:48:53,980
Report slash problematic.

518
00:48:55,284 --> 00:48:55,931
point.

519
00:48:56,340 --> 00:49:00,400
to report that feed with a reason code and a...

520
00:49:00,907 --> 00:49:08,628
note about why it was marked as problematic hey is there a way that um here's the thought oh here's a fun thought

521
00:49:09,228 --> 00:49:14,003
Is there a way that I can add my Vulcan to the process?

522
00:49:14,891 --> 00:49:18,804
help you with that? What's a Vulcan? My Vulcan 3090 card, baby.

523
00:49:21,579 --> 00:49:23,476
Vulcan. The Vulcan. Yeah.

524
00:49:24,108 --> 00:49:29,076
Yeah, I don't know if you know in Birmingham we have this huge statue on top of Red Mountain.

525
00:49:29,420 --> 00:49:33,364
In the center of Birmingham, it's a statue of Vulcan.

526
00:49:33,804 --> 00:49:53,076
Roman god of... Oh yeah, you guys are all pagan cult worshippers over there. We are. Once a week we all go and bow to the... The Vulcan. The Vulcan, yeah. So we had this radio station in town called the Vulcan. The Vulcan.

527
00:49:54,604 --> 00:49:58,003
Rocking, flame-throwing Vulcan, Alabama.

528
00:49:58,731 --> 00:49:59,989
think anybody can run this.

529
00:50:00,000 --> 00:50:01,092
script.

530
00:50:04,188 --> 00:50:05,860
I'll have to think about how that would work.

531
00:50:07,068 --> 00:50:09,764
But it's definitely – it doesn't require –

532
00:50:10,396 --> 00:50:11,172
any sort of

533
00:50:14,076 --> 00:50:24,804
It doesn't run on the podcast index structure, so you can run it in your house. Here's a thought. So here's how people could really help. It does take a lot of VRAM, though. Well.

534
00:50:25,148 --> 00:50:28,387
I've really gotten into the rented GPU stuff.

535
00:50:29,211 --> 00:50:43,876
Are you familiar with this? I've rented GPUs, yes. Vast.ai, RunPod, Together.ai is the one I've had the most success with. Grok, G-R-O-K, which has no dev tier, but they have a lot of free stuff right now.

536
00:50:44,284 --> 00:50:45,284
Um,

537
00:50:46,364 --> 00:50:49,347
I do a lot with that, particularly Whisper.

538
00:50:50,076 --> 00:50:51,364
So I'll do a...

539
00:50:52,219 --> 00:50:59,500
Someone says, hey, this is a great podcast. You should listen to this. I'm like, no, I'm going to listen to it. So I send my bot out, my robot, and it grabs.

540
00:50:59,751 --> 00:51:02,224
podcast or the YouTube turns it into a

541
00:51:02,695 --> 00:51:15,311
an audio file, whispers it, and then summarizes, tell me what's in it, if there's any good clips, anything I should get from it. And that costs like pennies because it goes so fast.

542
00:51:15,655 --> 00:51:17,679
on this rent stuff.

543
00:51:18,184 --> 00:51:41,068
So if you had like and I think you can set up like almost like I don't know what the term is, but it's like a docker basically where you can have an API endpoint that's stored. So anybody if anybody could just access that. So you could you know, you could just have a whole bunch of machines firing with the same model, the same weights, the same parameters all the time to help.

544
00:51:41,068 --> 00:51:48,911
in that process. So you distribute the cost and the actual load of the service. I mean, we could fight this stuff.

545
00:51:49,255 --> 00:51:50,992
Does that make sense what I'm saying?

546
00:51:51,527 --> 00:51:53,519
I think it, yeah, it does make sense for sure.

547
00:51:53,960 --> 00:51:54,704
Um,

548
00:51:55,655 --> 00:51:59,199
The only caveat I would throw in there is...

549
00:51:59,355 --> 00:52:00,483
this one and this is a

550
00:52:01,851 --> 00:52:04,675
Because I'm strongly of the opinion right now.

551
00:52:06,043 --> 00:52:07,235
to train

552
00:52:09,115 --> 00:52:17,059
Oh, and I don't mean I don't mean necessarily a full training. What I mean is like a fine tune. We're going to have to fine tune a model. OK.

553
00:52:18,108 --> 00:52:23,811
Because what we really need is not...

554
00:52:24,731 --> 00:52:26,596
what this thing currently does.

555
00:52:27,099 --> 00:52:28,291
which is...

556
00:52:28,891 --> 00:52:31,268
It tries to – which is it –

557
00:52:32,059 --> 00:52:37,476
What it does is it tells the model, okay, here's a new podcast.

558
00:52:38,940 --> 00:52:42,179
Here's the title and the description and titles and descriptions of.

559
00:52:42,780 --> 00:52:45,219
most recent episodes and show links.

560
00:52:45,692 --> 00:52:48,355
It just gives us a ton of metadata about this new podcast.

561
00:52:49,211 --> 00:52:55,940
And it says, here's the same data from about a dozen picked at random podcasts.

562
00:52:56,411 --> 00:52:59,599
from the legit table and about a dozen from the spam table.

563
00:53:02,668 --> 00:53:06,547
It says, okay, now do your best to make a decision.

564
00:53:07,019 --> 00:53:08,148
also taking into account

565
00:53:08,556 --> 00:53:12,211
prompt that we give it with a bunch of parameters about what

566
00:53:12,715 --> 00:53:14,195
going on.

567
00:53:14,987 --> 00:53:18,068
That just has context problems.

568
00:53:18,731 --> 00:53:24,659
What you really want, you don't want to have to provide all of that essentially in a context window.

569
00:53:25,132 --> 00:53:38,675
What you want is for the model to have that knowledge innately because then you can basically train it on the entire index. So this comes to the point of…

570
00:53:39,244 --> 00:53:39,764
Love.

571
00:53:41,068 --> 00:53:46,867
Me and James went back and forth a little bit on the podcastindex.social this week about this topic.

572
00:53:50,251 --> 00:53:51,860
He wrote it up. The Crickler.

573
00:53:53,036 --> 00:53:54,003
Riddler.

574
00:53:55,179 --> 00:53:57,043
Criddled. You got Criddler.

575
00:54:00,460 --> 00:54:01,204
So.

576
00:54:01,675 --> 00:54:04,532
He wrote it up as a headline in podcast.

577
00:54:04,907 --> 00:54:05,556
about

578
00:54:05,900 --> 00:54:09,684
the spam issue and the 24 hour feed report and all that.

579
00:54:10,668 --> 00:54:11,860
Oh, which is fine.

580
00:54:15,628 --> 00:54:19,987
pinged me on podcastindex.social and said, well, you know, and it was making the point.

581
00:54:21,483 --> 00:54:23,188
He called it censorship. I looked.

582
00:54:23,596 --> 00:54:26,739
disagree with that fundamentally. I think.

583
00:54:27,371 --> 00:54:28,980
censorship is.

584
00:54:29,804 --> 00:54:31,603
censorship is when I say.

585
00:54:33,547 --> 00:54:36,659
like what you said and therefore I'm going to block you.

586
00:54:38,443 --> 00:54:42,420
like the, the, the thing, your ideas and what you're espousing.

587
00:54:43,563 --> 00:54:44,884
This is.

588
00:54:45,867 --> 00:54:47,572
This is something completely different.

589
00:54:48,523 --> 00:54:49,172
care less about

590
00:54:50,668 --> 00:54:53,684
is the form, looking at the structure.

591
00:54:54,476 --> 00:54:56,148
and the structure is abusive.

592
00:54:57,708 --> 00:54:59,300
podcasting as a whole.

593
00:54:59,487 --> 00:55:02,248
It's not censorship. It's self-defense.

594
00:55:03,456 --> 00:55:09,255
But I think the larger point of what he's saying, I took some good things away from what he said.

595
00:55:10,655 --> 00:55:13,543
He was – because what he said was …

596
00:55:13,920 --> 00:55:18,952
One of the unique benefits of Podcast Index is that you have all the feeds.

597
00:55:20,063 --> 00:55:21,864
And if you block, if you...

598
00:55:22,304 --> 00:55:25,000
block some from being ingested.

599
00:55:25,695 --> 00:55:26,536
in it.

600
00:55:27,231 --> 00:55:33,800
lessens the value of the index and what it is and what it represents. Fair point. And I think he's right.

601
00:55:34,271 --> 00:55:35,208
but we can tag it.

602
00:55:36,288 --> 00:55:45,896
And so there was a misunderstanding on his part just because the – it's not – well, some of this is not obvious.

603
00:55:48,447 --> 00:55:49,416
And that is.

604
00:55:50,528 --> 00:55:53,351
We have all those feeds.

605
00:55:54,271 --> 00:55:59,199
I'm not deleting them out of the index. The index really doesn't ever delete anything. Right.

606
00:55:59,324 --> 00:56:01,155
The only things we ever delete.

607
00:56:01,820 --> 00:56:08,195
are actually, I mean, like actually remove from the database, like they're no longer even in there.

608
00:56:11,708 --> 00:56:21,188
mostly things that are not podcasts. Sometimes things get in there and it's just a web page. I was like, well, this is not even a pod. I mean, this is literally not even a podcast. Yeah, right. Yeah, right.

609
00:56:21,532 --> 00:56:23,556
Yeah, this is a text file or some crap.

610
00:56:24,220 --> 00:56:29,731
And so like those we remove and then there's just a handful of other things that we removed.

611
00:56:31,516 --> 00:56:33,891
very specific reasons that

612
00:56:34,684 --> 00:56:36,675
Honestly, I don't even remember. Yeah.

613
00:56:38,619 --> 00:56:41,380
But I'm talking about – I mean you could just – you could put that on –

614
00:56:42,331 --> 00:56:43,268
Mm-hmm.

615
00:56:44,220 --> 00:56:52,068
All the rest of this stuff that is getting marked, it's just there's a flag in the database that's just this dead equals one or dead equals zero.

616
00:56:52,923 --> 00:56:59,199
If dead equals one, then it no longer gets served on the website or the API. It's just it's like it's invisible.

617
00:56:59,836 --> 00:57:01,411
Data is still there.

618
00:57:02,652 --> 00:57:24,771
And when I say data, I mean the episodes are deleted, but the full feed record with the title, the description, the feed URL, if it had an iTunes ID, the status code, the HTTP status code, how many episodes were in the feed, all of that data, that metadata about the feed, all of that still exists.

619
00:57:25,884 --> 00:57:28,387
So wouldn't you want to –

620
00:57:28,827 --> 00:57:37,028
a thought. So when you want to have one or more flags, we already have flags like AI slop, spam, etc.

621
00:57:37,371 --> 00:57:52,260
have the flags so you can, when you're polling the API, you get whatever you want. If you want everything, then you say, please add these flags. And only if someone actually polls that particular.

622
00:57:53,083 --> 00:57:56,068
Podcast Enix ID, do we do a scan?

623
00:57:58,043 --> 00:57:59,199
That makes sense.

624
00:57:59,836 --> 00:58:00,771
Or was that not useful?

625
00:58:03,099 --> 00:58:07,043
Run that by me one more time. I'm not sure I followed 100%. So we have everything.

626
00:58:07,452 --> 00:58:13,795
But instead of it being dead, if you want to query the entire index, including the spam and the slop, etc.,

627
00:58:14,523 --> 00:58:28,195
query it and you can get the information, get the top level information about the podcast. But only if someone says, well, I really, really need this Abraham Lincoln AI generated history podcast. Only then do we scan that feed.

628
00:58:30,204 --> 00:58:39,492
So we keep the – That would be a challenge. Oh, okay. That would be a challenge because we just – it's just dead one or –

629
00:58:40,092 --> 00:58:40,739
Dead Zero.

630
00:58:42,172 --> 00:58:49,860
Right, but we're working on flags now, aren't we? Are we coming up with – I mean you're flagging something if I look at this report page.

631
00:58:50,300 --> 00:58:59,199
Yeah, things are flagged as reasons for being marked as dead. Okay, right.

632
00:58:59,836 --> 00:59:02,820
that's in a separate table so that we'd have to check is

633
00:59:03,708 --> 00:59:08,483
I think we could do what you're saying, but I think it would be hard. It doesn't mean it's not.

634
00:59:09,307 --> 00:59:11,076
Doesn't mean we shouldn't do it, but it would be.

635
00:59:14,172 --> 00:59:20,836
Well, I'm just continuously thinking how can we all work together very simple to the gossip system.

636
00:59:21,179 --> 00:59:24,771
So we all can help flag things. We all can, you know.

637
00:59:25,244 --> 00:59:25,827
just

638
00:59:27,355 --> 00:59:37,635
make it useful for everybody for whatever your use case. So if you really want to have, if you really want to search across all of the slop and everything, you should be able to do that.

639
00:59:38,203 --> 00:59:52,675
But that these distributed systems are alleviating the load on the ultimate endpoint from the index to make it easier or ultimately, hey, you know, you want to have an index with all the slop in it? Your gossip has it.

640
00:59:54,268 --> 00:59:59,199
Yeah, so I think James had a good –

641
01:00:00,000 --> 01:00:03,108
I forget if his idea or mine. I don't remember exactly, but.

642
01:00:03,739 --> 01:00:05,891
We came up with a good idea, which is.

643
01:00:07,228 --> 01:00:09,027
index right now

644
01:00:09,692 --> 01:00:16,835
The core part of the index from day one has been this downloadable SQLite database of all the feeds. Of everything, yeah.

645
01:00:17,467 --> 01:00:23,012
And so that, what I've always done is I've excluded the dead feeds out of there.

646
01:00:24,507 --> 01:00:27,907
Just for size constraint and because

647
01:00:28,731 --> 01:00:29,923
want to distribute things that

648
01:00:30,300 --> 01:00:33,380
dead because sometimes they're marked dead for a reason. Right.

649
01:00:34,235 --> 01:00:38,596
Sometimes they're more dead because – It's theft. It's plagiarism, et cetera.

650
01:00:39,356 --> 01:00:42,211
Yeah, and the creator asked us. Yeah.

651
01:00:42,780 --> 01:00:44,291
take it down. And so we don't.

652
01:00:45,755 --> 01:00:46,340
I wanted to just...

653
01:00:48,539 --> 01:00:51,972
distribute that in a different form that goes against their wishes.

654
01:00:53,244 --> 01:00:54,083
And so.

655
01:00:54,876 --> 01:00:55,940
what I think

656
01:00:56,284 --> 01:01:00,199
My next step is going to be to create a second download.

657
01:01:04,228 --> 01:01:09,867
And it's going to continue to exclude all of those things that were marked dead in the past.

658
01:01:10,947 --> 01:01:14,123
Because those things, there is.

659
01:01:15,235 --> 01:01:15,820
Well...

660
01:01:17,347 --> 01:01:23,052
I don't know. I'm going to have to think this through. I told James, I said, give me a few days. I'm going to have to think this out.

661
01:01:25,059 --> 01:01:25,771
cause.

662
01:01:27,364 --> 01:01:29,900
What we want is a second download that

663
01:01:30,724 --> 01:01:32,012
Everything in it.

664
01:01:33,572 --> 01:01:34,155
for

665
01:01:35,012 --> 01:01:36,748
just for the people

666
01:01:38,851 --> 01:01:39,532
And then.

667
01:01:40,164 --> 01:01:41,963
But what needs to be in there.

668
01:01:44,739 --> 01:01:47,052
Who really wants that? Who really needs that?

669
01:01:49,092 --> 01:01:49,708
I don't know.

670
01:01:50,340 --> 01:01:52,876
So it seems like a big lift for a very

671
01:01:53,219 --> 01:01:56,043
few amount of people who really want all that.

672
01:01:56,612 --> 01:01:59,800
Well, let me let me tell you, I could tell you this.

673
01:01:59,891 --> 01:02:00,380
I want.

674
01:02:02,483 --> 01:02:04,123
And here's why.

675
01:02:05,780 --> 01:02:07,867
Well, let me finish that first off.

676
01:02:08,659 --> 01:02:12,860
What we would have to do is in – I think this is the way it would have to work.

677
01:02:13,492 --> 01:02:16,891
What we'd have to do is we'd have to export it, do a second export.

678
01:02:18,291 --> 01:02:19,355
It has everything in it.

679
01:02:20,403 --> 01:02:24,155
And it's going to have to have at least one extra column, probably a few.

680
01:02:24,820 --> 01:02:26,972
that details if it's dead, why.

681
01:02:29,012 --> 01:02:32,764
The reason would be out of the MF – out of the problematic table.

682
01:02:33,268 --> 01:02:40,284
Listing, okay, well, we considered it spam or abuse or slop or whatever. And here's the note on why it was.

683
01:02:41,588 --> 01:02:42,652
marked as dead, excuse me.

684
01:02:45,012 --> 01:02:47,195
have that. But then these older feeds.

685
01:02:47,987 --> 01:02:51,036
We would probably – what we'd probably have to do is if –

686
01:02:52,340 --> 01:02:55,420
The HTTP status code of the last scan is...

687
01:02:57,139 --> 01:02:59,500
200 or if it's a valid.

688
01:02:59,655 --> 01:03:02,576
HTTP access code or response code.

689
01:03:03,336 --> 01:03:05,936
We would probably have to somehow.

690
01:03:07,367 --> 01:03:08,911
still not export that.

691
01:03:09,831 --> 01:03:16,880
Because that's probably an – that is most certainly an indication that that – that we were asked to remove it.

692
01:03:17,576 --> 01:03:23,952
But then if it's marked dead for some other HTTP status code, like a 404 or something like that, then we could stick that in.

693
01:03:24,903 --> 01:03:29,840
And say, OK, well, it's obvious why this was removed. This was removed because it's no longer validly served.

694
01:03:31,079 --> 01:03:35,376
So there's going to have to be some work here to make this function properly.

695
01:03:35,784 --> 01:03:42,735
But once we do have that second download, this is what we fine-tune the model on.

696
01:03:44,199 --> 01:03:47,440
So what we'll have to do, because when you fine tune a model, you have.

697
01:03:49,831 --> 01:03:51,887
You have to create a data set.

698
01:03:53,159 --> 01:03:58,192
dataset, it's a lot like training a machine learning model.

699
01:03:58,860 --> 01:04:00,884
What you have is a data set.

700
01:04:02,092 --> 01:04:08,052
It comes down to here's a bunch of words and then here's a decision.

701
01:04:09,163 --> 01:04:16,019
is it this thing or that thing? And so what it's just like a whole, it's a lot, it's a series of funnels.

702
01:04:16,652 --> 01:04:26,675
This is a series of tubes that flow from a bunch of content into what amounts to a single decision.

703
01:04:29,547 --> 01:04:33,492
And so then you feed that into the fine tuning.

704
01:04:33,867 --> 01:04:34,387
Thank you.

705
01:04:36,076 --> 01:04:37,556
There's a bunch of these scripts out there.

706
01:04:38,220 --> 01:04:41,460
So we can fine tune a GGUF model or something like that on.

707
01:04:42,764 --> 01:04:44,019
on this data

708
01:04:44,619 --> 01:04:57,715
from this second download because it's going to have all the valid ones in there and all the spam junk. So what does it take to train or fine-tune a model? That's above my knowledge base.

709
01:04:59,139 --> 01:05:03,755
But what is the application that does that? What is the system that does that?

710
01:05:04,867 --> 01:05:14,315
I think there's some – it's easier now than it used to be. I think there's a couple of tools out there. NVIDIA just launched one through Onsloth.

711
01:05:15,427 --> 01:05:19,275
unsloth studio or something like that that will help it's it makes it easier

712
01:05:19,811 --> 01:05:23,500
But you can still just do it with a bunch of like PyTorch Python scripts.

713
01:05:24,931 --> 01:05:25,420
I'll just...

714
01:05:27,523 --> 01:05:29,355
research to figure this out right now.

715
01:05:30,851 --> 01:05:34,635
As soon as I have this second download constructed, then I'll...

716
01:05:36,355 --> 01:05:39,436
headlong into that and try to fine tune a model.

717
01:05:41,411 --> 01:05:43,307
And it's just got a vast.

718
01:05:46,275 --> 01:05:52,460
knowledge to pull from to make these decisions. So that's the, when I said that there was a kink to.

719
01:05:53,028 --> 01:05:54,731
idea of distributing this. That's what I'm.

720
01:05:57,315 --> 01:05:59,000
We'd have to somehow distribute the model.

721
01:06:00,659 --> 01:06:09,628
this point, how that works. I like the idea of providing, of being a clearinghouse and providing the information back to the hosting companies. And that's a great idea.

722
01:06:11,315 --> 01:06:12,028
Yeah.

723
01:06:12,500 --> 01:06:15,483
Yeah, I think, I mean... That's gonna help a lot. It's gonna help a lot.

724
01:06:16,371 --> 01:06:18,619
I hope so. This morning.

725
01:06:19,123 --> 01:06:22,460
We saw this morning started the black magic.

726
01:06:23,220 --> 01:06:24,251
Black magic?

727
01:06:25,556 --> 01:06:34,364
Let me see if I can find one of these. Yeah. I mean, this spam feeds are – I mean, they're entertaining to watch sometimes.

728
01:06:35,220 --> 01:06:44,092
I just want a terminal where I can just watch the spam come by. Like, what do you got? Oh, this is interesting. What do you got here? Oh, OnlyFans.

729
01:06:44,563 --> 01:06:46,300
Let me see if I can find one of these.

730
01:06:49,715 --> 01:06:50,844
It might be a little.

731
01:06:51,603 --> 01:06:54,235
What? Oh, is there? What is that one?

732
01:06:54,675 --> 01:06:59,199
It's like, I think I posted one on podcast index on social.

733
01:07:00,731 --> 01:07:03,523
It was like – it's stuff like how to get your girlfriend back.

734
01:07:05,563 --> 01:07:10,692
And you do it with black magic, and there's a phone number you can call to get them to help you. Oh. Oh.

735
01:07:11,644 --> 01:07:19,619
Oh, it's rad, man. It's rad. It's super easy to – yeah, here it is. How to get your ex-boyfriend back when he has another girlfriend.

736
01:07:20,347 --> 01:07:25,188
Call 91741-409-7597. Excellent.

737
01:07:25,851 --> 01:07:29,188
And it's Black Magic and Val...

738
01:07:29,532 --> 01:07:31,619
Vashikaran?

739
01:07:32,603 --> 01:07:46,115
Top Vashikaran specialist Vikram Sharma is a very good astrologer and world gold medalist. Oh, gold medalist in what? Black magic, I guess. I don't know. Hold on a second. Let me pipe my thing in here for a second.

740
01:07:46,588 --> 01:07:49,764
Pipe it in there. I'm going to pipe it in. Let me connect my phone.

741
01:07:50,940 --> 01:07:52,195
Should my phone be able to connect?

742
01:07:52,603 --> 01:07:58,403
I want to dial that number. Let me see. I haven't actually connected. Oh, here we go. Roadcaster. Boom. Pairing.

743
01:07:59,452 --> 01:08:00,068
That kind of work.

744
01:08:01,628 --> 01:08:08,516
Hey, citizen. Dave, is there an explicit rule banning AI slop from the podcast index? No, we don't have explicit rules about anything.

745
01:08:10,427 --> 01:08:12,036
Our only rule is...

746
01:08:13,371 --> 01:08:14,563
keep it free and

747
01:08:15,739 --> 01:08:16,195
sensory

748
01:08:17,051 --> 01:08:20,707
Okay, I got it paired. Now let me go back here.

749
01:08:23,163 --> 01:08:24,163
I don't believe.

750
01:08:25,275 --> 01:08:31,395
Rules require meetings, and we don't want to do it. What's that phone number again, Dave? Let me get that. Let me dial that phone number.

751
01:08:32,188 --> 01:08:33,252
No, no.

752
01:08:33,724 --> 01:08:36,131
This says 9-1-

753
01:08:36,731 --> 01:08:45,764
Plus 9-1-DASH. Oh, hold on. That's sketch. Okay, plus 9-1. Oh, yeah. Plus 9-1. 7-4-1. 7-4-1.

754
01:08:46,108 --> 01:08:47,811
409. 409.

755
01:08:48,604 --> 01:08:55,587
Seven, five, nine, seven, five, nine. Is this going to cost me a thousand dollars? Oh, I'm sure. Oh yeah, for sure. Let's see if it works.

756
01:08:58,587 --> 01:08:59,199
is ringing.

757
01:09:05,819 --> 01:09:07,332
Hello.

758
01:09:07,676 --> 01:09:14,307
Hi, I'm calling about the black magic to get my boyfriend back.

759
01:09:14,747 --> 01:09:16,387
Yeah, you're good, man.

760
01:09:17,020 --> 01:09:18,115
Is Pete.

761
01:09:20,507 --> 01:09:24,771
Okay, your professional is arriving. What?

762
01:09:26,716 --> 01:09:28,676
What are you doing by profession?

763
01:09:29,435 --> 01:09:35,684
I'm calling about this. I had this number. I found it in my podcast to call if I want to get my boyfriend back.

764
01:09:38,011 --> 01:09:39,268
Okay, no problem.

765
01:09:39,644 --> 01:09:42,275
Send me the details of your boyfriend and your...

766
01:09:42,844 --> 01:09:50,307
on the same WhatsApp number named BigTelCity. Yeah, I got to hang up. It's India. I called India.

767
01:09:51,036 --> 01:09:52,996
None of that. None of that.

768
01:09:53,340 --> 01:09:58,500
How ineffective is this stuff? This doesn't make any sense to me. Why are you saying...

769
01:09:59,296 --> 01:09:59,988
Are you scamming?

770
01:10:00,000 --> 01:10:14,307
I mean, the podcast index for this nonsense is not doing anything for me. They're blasting it all over the world, and then you can't understand what they're saying. You can't understand the dudes. This is no good. This makes no sense. Yeah, this is ineffective. Ineffective. Very ineffective.

771
01:10:15,420 --> 01:10:17,699
But there was, oh gosh.

772
01:10:19,899 --> 01:10:42,884
Meanwhile, I didn't get my boyfriend back. So, you know, this is like a double disappointment. This stuff is going straight. This stuff is going straight into the ecosystem. And then there's some then there's some homeschool mom somewhere trying to start a podcast about, you know, Charlotte Mason education and can't get nothing through.

773
01:10:43,771 --> 01:10:47,619
No traction. That was completely unsatisfying.

774
01:10:48,060 --> 01:11:00,300
No, I always wanted to laugh much harder than that. This didn't work. Because I wanted to say, okay, here's what you do. And then I wanted you to be like, hi, I'm the boyfriend and I'm here. I mean, we could have had a whole thing going here.

775
01:11:01,287 --> 01:11:08,399
That's right. I was fully prepared to be your boyfriend. Salty crayon. Did you turn your boyfriend off and turn him back on?

776
01:11:12,648 --> 01:11:17,264
Exactly. Yeah, yeah, Metis is right. That dude was like, holy shit, somebody called.

777
01:11:17,703 --> 01:11:18,735
It worked.

778
01:11:20,167 --> 01:11:24,944
I spent 10 cents on spamming podcast indexes and I got a call.

779
01:11:25,351 --> 01:11:32,496
C. Los is right. He just said that it was James. James Cridland.

780
01:11:33,960 --> 01:11:40,560
We can always call back. My boyfriend's name is Sam. We've been having a fight.

781
01:11:41,992 --> 01:11:46,895
Oh, I screwed up the script. I can't believe it. Oh, what an opportunity.

782
01:11:48,167 --> 01:11:52,847
Instead I come up with Pete. I'm so stupid. This is James.

783
01:11:53,511 --> 01:11:55,119
That's funny.

784
01:11:55,528 --> 01:12:00,199
Oh, man. All right. Hey, we probably should thank some people. Oh, you have the date. Well.

785
01:12:00,515 --> 01:12:07,372
We got people. I have to clean up my studio. Tina made me commit to it. Like one of those, one of those wife commitment things.

786
01:12:07,876 --> 01:12:24,300
Oh, OK. I need you to commit to something. So you have a hard out. I've got a I've got no out. And you have I got I got a hard out. Yeah. The studio is absolutely atrocious. It's like I've got no agenda. Chachkis and hats and.

787
01:12:24,836 --> 01:12:33,003
I've got 8,000 books about scripture and I still have a T-Mobile bag sitting here that I got my phone in. I mean, this is bad.

788
01:12:33,667 --> 01:12:41,100
really bad. Well, I mean, like we did, we covered basically nothing.

789
01:12:41,507 --> 01:12:48,427
But there's like 50 things on my list that I have not even had a chance to talk about.

790
01:12:49,507 --> 01:12:53,452
Well, we can do it next week. We'll do a better job next week.

791
01:12:53,988 --> 01:12:59,899
We had fun, though. I want to call that guy. OK, new segment of the show.

792
01:13:00,055 --> 01:13:23,520
Call a different scammer every week. Okay. I'm good with that. Well, we've got to have a better script next time we screw that one up. Oh, yeah. No. But it will be the James and Sam script. Every time. Sam and James. Sam and James. Call a scammer. I don't know. Does anybody still remember the – what was it? Not the janky boys. The jerky boys.

793
01:13:23,608 --> 01:13:37,279
Remember the Jerky Boys? Yeah, yeah, yeah. The Jerky Boys, man. They were so good at that back in the day. That was like on cassette tapes that people would pass back and forth to each other. Oh, yeah. I think the Beastie Boys made a song about the Jerky Boys, if I can recall.

794
01:13:37,720 --> 01:13:40,671
because they were calling some guy about cookie puss.

795
01:13:42,391 --> 01:13:48,832
Oh, hold on a second. The crank anchors. That's another one. Hold on a second. Let me see if I can find this.

796
01:13:49,880 --> 01:13:55,840
This was a class. You remember, well, you know, the beast. This was actually, uh, let me see.

797
01:13:56,184 --> 01:13:57,536
Peace to you, boys.

798
01:13:58,167 --> 01:13:59,899
cookie puss. This was the

799
01:14:00,055 --> 01:14:05,119
This was the OG Beastie Boys back in the day.

800
01:14:07,192 --> 01:14:08,543
Bye.

801
01:14:20,376 --> 01:14:24,863
17 years ago this. Now it's got to be older than that.

802
01:14:25,239 --> 01:14:25,952
years old.

803
01:14:28,728 --> 01:14:29,376
you forget this

804
01:14:30,104 --> 01:14:31,391
Hello?

805
01:14:33,560 --> 01:14:36,416
Oh, my God.

806
01:14:38,136 --> 01:14:39,039
the number N-Wing.

807
01:14:40,152 --> 01:14:42,207
Last minute.

808
01:14:42,551 --> 01:14:43,391
We'll be right back.

809
01:14:45,655 --> 01:14:46,271
What's up, bitches?

810
01:14:47,095 --> 01:14:47,807
And.

811
01:14:53,496 --> 01:14:54,496
Thank you.

812
01:14:54,967 --> 01:14:58,975
He's calling about the ice cream cookie puss.

813
01:15:00,136 --> 01:15:08,496
That was just one step removed from what was the videotapes?

814
01:15:09,319 --> 01:15:26,608
Faces of Death or whatever. Oh, yeah. Your copy was like an eighth generation. And you always had to skip it at the end because it was the people eating the monkey's brains out of the monkey head on the table with his head sawed off on the top.

815
01:15:26,952 --> 01:15:37,488
And you'd have a big line of snow at the bottom that you just couldn't get rid of no matter how many times. What was the little thing that you would adjust, the little dial on the forehead? Tracking. Tracking. Yeah, that's it, the tracking.

816
01:15:38,055 --> 01:15:41,423
Yeah, tracking. Wow. So that whole...

817
01:15:41,832 --> 01:15:47,471
That whole episode resulted in the one and only boost that came in during the live show.

818
01:15:48,423 --> 01:15:59,699
From C-Loss on Linux. 4,329 sats. Interesting. That doesn't sound like a right number. I'm on the new helipad, so I'm jacked.

819
01:15:59,699 --> 01:16:13,047
into oh yeah big big helipad upgrade by eric pp oh yeah oh yeah this thing had this thing had like 75 commits in it i mean it was like oh that's amazing yeah that's amazing let me see he fixed like every

820
01:16:13,583 --> 01:16:15,672
possible thing. Everything. Everything.

821
01:16:16,207 --> 01:16:18,615
No, Eric P. said he boosted $33.33.

822
01:16:19,984 --> 01:16:25,144
It didn't come through to me. No, Dreb said his boost failed.

823
01:16:25,807 --> 01:16:27,256
Hmm. Hmm.

824
01:16:27,952 --> 01:16:34,136
I don't know why. But C-Lost, was that a key send? Was that an LN URL? Which one was it?

825
01:16:36,560 --> 01:16:42,359
Oh, he did. I said four, three, two, one. Somehow I got four, three, two, nine. I don't know why.

826
01:16:42,768 --> 01:16:45,655
I don't know why that was. Yeah, I see 4, 3, 2, 1.

827
01:16:46,543 --> 01:16:47,032
Interesting.

828
01:16:47,887 --> 01:16:48,792
So I got some extra.

829
01:16:49,359 --> 01:16:58,423
The new helipad now adds eight sats for every transaction. You just get a freebie. Get a freebie. Wait. Let's see. What is this?

830
01:16:59,847 --> 01:17:01,967
crazy. Did you get it?

831
01:17:03,688 --> 01:17:04,207
Random look.

832
01:17:07,047 --> 01:17:14,095
hub export this has become so complicated now yeah silas was that ellen url or was it keysend

833
01:17:20,615 --> 01:17:21,456
Stay here.

834
01:17:25,735 --> 01:17:27,216
It says it failed for you, Dave.

835
01:17:29,159 --> 01:17:31,568
Oh, it did? My note is up, I think.

836
01:17:33,288 --> 01:17:34,032
nose

837
01:17:34,568 --> 01:17:36,015
I'm re-exporting the Albeho.

838
01:17:36,904 --> 01:17:37,456
And I just want to say thank you.

839
01:17:37,895 --> 01:17:42,863
PayPal. Let me see if that came through too. No, I think I changed. I don't think I have a,

840
01:17:43,783 --> 01:17:47,055
Fountains sometimes send strange TOV records.

841
01:17:48,296 --> 01:17:50,095
Let me see. Did it come through?

842
01:17:51,304 --> 01:17:52,655
strange fire.

843
01:17:55,112 --> 01:17:55,855
LTV.

844
01:17:59,119 --> 01:18:01,399
at uncashed payment. I'm looking at...

845
01:18:01,904 --> 01:18:05,176
The runway too. Let's see it on runway. Interesting.

846
01:18:05,711 --> 01:18:09,720
Shouldn't be on runway. It should only because I changed everything to my Albie hub.

847
01:18:12,880 --> 01:18:14,264
helps working

848
01:18:17,488 --> 01:18:21,815
Drebscott just tried again with fancy new customatic. Okay. Well, I didn't.

849
01:18:22,319 --> 01:18:23,479
I didn't hear anything.

850
01:18:25,391 --> 01:18:26,007
I don't see any.

851
01:18:26,384 --> 01:18:28,247
My lightning note is up and running.

852
01:18:28,688 --> 01:18:30,872
You're lightning fast.

853
01:18:32,015 --> 01:18:34,072
Transaction was 11 days ago, though, so.

854
01:18:34,768 --> 01:18:35,960
that's all about.

855
01:18:37,136 --> 01:18:42,551
That doesn't sound right. No, this is all just a train wreck.

856
01:18:43,792 --> 01:18:49,271
Anyway, thank you, C-Loss on Linux, for giving us the only boost I got.

857
01:18:50,448 --> 01:18:52,024
I do see.

858
01:18:52,783 --> 01:18:57,015
91 Sats from Oscar about eight hours ago.

859
01:18:57,724 --> 01:19:03,940
Twice, test one, test two, and then I hit the delimiter. I don't think we got anything else. At least I don't see it on runway either.

860
01:19:04,699 --> 01:19:08,292
I'm currently exporting out of AlbieHub to...

861
01:19:08,731 --> 01:19:09,956
Excel spreadsheets.

862
01:19:10,716 --> 01:19:19,747
This will be fun. It's on 34 out of 79 transactions. Let's see if I have any streams. I don't think I have any streams either. When's my last stream? No, 22 hours ago. That can't be right.

863
01:19:27,931 --> 01:19:40,260
Lyceum sent 7777 via True Fans and 1111. Oh, here's Eric PP. Okay. I got 3333 from Eric PP. Yeah, I got it. That just came in.

864
01:19:40,667 --> 01:19:41,859
Oh, it just took a minute.

865
01:19:42,460 --> 01:19:42,979
Yeah.

866
01:19:44,315 --> 01:19:46,275
Okay, so that worked, but I didn't hear a pew.

867
01:19:47,836 --> 01:19:48,547
Yeah.

868
01:19:49,435 --> 01:19:54,307
Didn't he make some changes to the sound settings? No, I think they carried over.

869
01:19:55,931 --> 01:19:57,600
I know he added some stuff, right? I think.

870
01:19:57,948 --> 01:19:59,988
Let me see. I think it does.

871
01:20:00,123 --> 01:20:00,996
things like MIDI

872
01:20:01,627 --> 01:20:02,948
numerology.

873
01:20:04,315 --> 01:20:10,372
No, he's got it in there. He's got the baller. He's got all that. Oh, Eric said he reboosted with Boost CLI.

874
01:20:11,003 --> 01:20:14,243
What did you, Eric, what did you boost at before, Fountain?

875
01:20:14,652 --> 01:20:15,140
Maybe.

876
01:20:16,123 --> 01:20:18,372
Maybe he's – maybe he's sent it with Fountain and –

877
01:20:19,996 --> 01:20:28,644
I don't know. Maybe Fountain – maybe Oscar's dealing with some issues. Yeah, he has tests. So if he's testing eight hours ago, who knows?

878
01:20:29,404 --> 01:20:31,011
Yeah, I wonder if...

879
01:20:34,203 --> 01:20:37,891
bot abuser thing was it could could totally be that

880
01:20:38,300 --> 01:20:38,756
could be okay.

881
01:20:39,899 --> 01:20:46,115
He may be fighting a battle, so we'll send up prayers for us. He's fighting a battle that we've already won.

882
01:20:49,404 --> 01:20:55,140
It's a worship song. We're fighting a battle that he already won.

883
01:20:56,347 --> 01:21:00,000
Why don't we thank some people, Dave? Okay, I'll do this next.

884
01:21:00,155 --> 01:21:02,180
Speaking of Oscar, Mary.

885
01:21:02,971 --> 01:21:07,460
PayPal. $200. Whoa, hold on a second.

886
01:21:08,859 --> 01:21:09,636
Please.

887
01:21:10,747 --> 01:21:16,676
Yay, thank you very much Oscar. Okay. Well that will cover that 200 will cover the

888
01:21:17,692 --> 01:21:28,644
new database upsize we're going to have to do because we're about 75% disk space on the current database server. Is that something that takes a while or is that like a quick thing?

889
01:21:30,524 --> 01:21:31,811
Uh, it'll take...

890
01:21:33,148 --> 01:21:34,979
Upsizing will take pro-

891
01:21:35,579 --> 01:21:39,779
Hour? 30 minutes. Oh, okay. And you're going to do that when?

892
01:21:42,332 --> 01:21:43,908
Please.

893
01:21:44,347 --> 01:21:48,868
I mean, I love you guys, but I'm not staying up until 2 o'clock in the morning.

894
01:21:49,659 --> 01:21:50,819
I'll just do it on like a Sunday.

895
01:21:51,579 --> 01:21:52,676
Hmm.

896
01:21:53,340 --> 01:21:59,500
How much dispatch are you using? Yeah, our current box has 650.

897
01:21:59,623 --> 01:22:01,296
and we're at like

898
01:22:03,880 --> 01:22:09,711
something what an odd number 640 gigs we just get a terabyte

899
01:22:10,344 --> 01:22:12,560
Well, the new, the new, the.

900
01:22:13,064 --> 01:22:14,703
I've been pricing stuff today.

901
01:22:15,528 --> 01:22:19,984
to try to figure out what to do, 'cause this is what set this whole spam thing off.

902
01:22:20,391 --> 01:22:29,904
I got a warning about disk space on the database server. And I was like, whoa, what? I mean, because 640 gigs, we should have plenty of space. And then I get in there like.

903
01:22:32,264 --> 01:22:34,800
We're just thousands of feeds a day.

904
01:22:36,488 --> 01:22:38,832
let's see, I was looking earlier

905
01:22:41,640 --> 01:22:46,703
What we're paying now for this VM for the main database is.

906
01:22:48,104 --> 01:22:52,368
Let's see, it's got 32 gigs of RAM and 640 gigs of disk.

907
01:22:54,823 --> 01:22:57,967
$192 a month for that VM.

908
01:22:59,192 --> 01:23:00,384
Upsize it.

909
01:23:00,792 --> 01:23:05,311
next size. Oh, it's going to be a jump. Oh, it's a jump.

910
01:23:06,648 --> 01:23:16,095
64 gigs of RAM and 1280, so 1.2 terabytes. Let's basically double the cost from $192 a month to $384.

911
01:23:17,815 --> 01:23:35,296
But I priced it out, and I was like, okay, well, can we just create a one-terabyte disk? And attach it? And attach it. And attach it. And that would be $100 a month. Oh, okay. So you might as well just go for the whole system. Yeah. It's worth it. Yeah. So they just – it's –

912
01:23:36,311 --> 01:23:59,600
It sucks. I hate spending money. I hate this crap. You're so good at that. I'm the opposite. I'm like, ah, spend the money. Throw money at the problem. Well, no, not throw money at the problem, but at a certain point, you can only wrap yourself in so many pretzel nuts. Yeah. I think I can trim some stuff other places. It's not going to be much.

913
01:24:00,332 --> 01:24:06,387
Maybe 30 bucks off the 12th layer bill. Think about all the extra stuff we can do with 64 gigs of room.

914
01:24:07,884 --> 01:24:15,347
can do more with that. It'll be worth it. Think of all the extra slot podcasts we can index with 64 gigs of RAM.

915
01:24:16,172 --> 01:24:20,180
Think of all the different Wikipedia scraped Egypt history.

916
01:24:20,971 --> 01:24:29,716
LLM read articles we can index. Yeah. It's going to be great. And the funny thing is, is that now Wikipedia is all run by slop bots.

917
01:24:30,572 --> 01:24:42,195
Oh, yeah. Yeah, exactly. So, you know, it's slop creating Wikipedia articles and bots creating slop out of slop. Slop on slop. Slop on slop. Slop on slop.

918
01:24:43,275 --> 01:24:45,555
Okay, Oscar, thank you. Thank you, Oscar.

919
01:24:46,667 --> 01:24:47,507
that's

920
01:24:48,908 --> 01:24:49,779
Boo!

921
01:24:50,604 --> 01:24:54,228
Five dollars. Joseph Maraca. Thank you, Joseph. Appreciate it.

922
01:24:54,923 --> 01:24:57,684
$24.20 from Lauren Ball. Thank you, Lauren.

923
01:24:58,123 --> 01:24:59,500
Mitch Downey.

924
01:24:59,500 --> 01:25:04,847
Thank you, Mitch. So kind. Yeah, that's the pod verse. And then.

925
01:25:05,256 --> 01:25:09,104
Mitch has always had a secondary contribution of $10 for him personally. Thank you.

926
01:25:10,663 --> 01:25:11,600
Christopher Harbaric.

927
01:25:12,231 --> 01:25:13,648
Thank you, Christopher.

928
01:25:14,247 --> 01:25:15,087
and Casa Jack.

929
01:25:15,655 --> 01:25:16,880
$15?

930
01:25:18,631 --> 01:25:27,087
We got Terry Keller, $5. Richard Turoksi.

931
01:25:28,711 --> 01:25:29,967
Thank you, Richard.

932
01:25:30,984 --> 01:25:54,608
Christopher, see Chris Cowan, $5. Paul Saltzman, $22.22. Let me give him a row of ducks here. Where's our ducks? Okay. Here we go. There's my row of ducks. Even though it's not booth, but still $22.22. Row of ducks. Derek J. Vizker, $21. Best name in podcasting. Jeremy Gerds, $5. Thank you, Jeremy.

933
01:25:54,728 --> 01:25:56,752
Todd Cochran.

934
01:25:57,224 --> 01:25:59,500
Thank you, Todd, on the cloud.

935
01:25:59,500 --> 01:26:01,327
Todd up there in the cloud.

936
01:26:02,760 --> 01:26:03,439
It just...

937
01:26:04,136 --> 01:26:10,127
It kind of gives me every time. Michael Hall, $5.50. I want to have all kinds of...

938
01:26:10,823 --> 01:26:13,551
podcast boosts, and I'm going to set up a bot for that.

939
01:26:13,895 --> 01:26:15,311
So that even when I'm dead.

940
01:26:15,720 --> 01:26:18,768
PayPal's and Boost will still go to podcast. That's kind of cool.

941
01:26:20,007 --> 01:26:23,855
Really cool idea. Dead boost. Nice. You just.

942
01:26:24,872 --> 01:26:26,064
free.

943
01:26:27,079 --> 01:26:28,271
prepay

944
01:26:29,832 --> 01:26:31,344
on some cloud hosting provider.

945
01:26:32,840 --> 01:26:33,456
Yep.

946
01:26:35,015 --> 01:26:39,760
Set up a node and then just set it to boost.

947
01:26:40,231 --> 01:26:42,416
to a bunch of different people forever.

948
01:26:42,792 --> 01:26:46,768
But with like random messages.

949
01:26:47,207 --> 01:26:54,511
Yeah, just messages just creative messages. Yeah, with like, do you want to get your boyfriend back?

950
01:26:55,399 --> 01:26:56,368
Call this number.

951
01:26:57,479 --> 01:26:59,399
Gene Liverman.

952
01:26:59,587 --> 01:27:09,931
Thank you, Gene. Timothy Voice, $10. And that's it for our PayPals. All right. Let me see if this.

953
01:27:10,627 --> 01:27:17,931
your spreadsheet came through yet? Has it done it? Has it done its thing? You know, these are always fun to interpret.

954
01:27:20,420 --> 01:27:21,739
Here we go.

955
01:27:26,180 --> 01:27:30,155
This stupid spreadsheet is a train wreck.

956
01:27:30,916 --> 01:27:34,923
Oh my gosh. So why are you doing that?

957
01:27:35,908 --> 01:27:41,452
I'm sorry. It's just humor. After every no agenda show, I have to do all the executive producers.

958
01:27:41,859 --> 01:27:44,876
An associate executive producer and put them in the credits and I have to –

959
01:27:45,475 --> 01:27:47,467
you know, for years, for, for.

960
01:27:48,100 --> 01:27:50,636
almost two decades. I've been copying pasting.

961
01:27:51,363 --> 01:27:58,800
these names from the spreadsheet. And of course, if someone's, you know, a knight, you got to have their knight name and all that stuff.

962
01:27:59,115 --> 01:28:02,644
putting it into the credits. And so I finally just like, hey.

963
01:28:03,020 --> 01:28:03,604
Claudebot.

964
01:28:04,492 --> 01:28:05,716
Can you just do this for me?

965
01:28:06,123 --> 01:28:07,380
And it does it.

966
01:28:08,427 --> 01:28:26,292
It just does it. It goes into the spreadsheet that's just sitting in my donation folder on the drive. And it knows $200 between $200 and $300 associate executive producer. It finds a night name and just puts it into the credits. Oh, wow. This is the stuff I love.

967
01:28:27,115 --> 01:28:29,268
Well, that's not this.

968
01:28:29,707 --> 01:28:40,819
Yet, yet, yet. This is terrible. It's not getting the names. It's not. I've got. OK, I see a Brian. I see Brian Inzminger.

969
01:28:43,788 --> 01:28:51,475
The best performing comedy shows for ads podcast. I don't know what that's. That's like a pod news boost. Why are we getting.

970
01:28:51,948 --> 01:28:52,659
this.

971
01:28:53,323 --> 01:28:57,140
Hope this boost were loaded an old Acer.

972
01:28:57,899 --> 01:28:59,199
All in one with Umbral.

973
01:28:59,387 --> 01:29:00,707
I have my Albie hub running there.

974
01:29:01,051 --> 01:29:08,323
Hope this boost works. Thank you for your show. 73 is Bruce, the ugly cocky 73 is keto five alpha Charlie. Charlie got to renew my license.

975
01:29:08,796 --> 01:29:12,996
You're on the 10 years.

976
01:29:13,500 --> 01:29:17,891
Here's some Bitcoin. Let's see, 1842. Here's some Bitcoin. You guys should start.

977
01:29:18,492 --> 01:29:21,539
government backup more often so it dips more what

978
01:29:22,492 --> 01:29:26,500
Okay, this is unintelligible. I'm punting.

979
01:29:27,163 --> 01:29:29,188
I got to figure this out later.

980
01:29:30,652 --> 01:29:33,731
If you saw this spreadsheet, you would just laugh.

981
01:29:34,716 --> 01:29:42,083
Well, okay, so we got 4321 from C-Loss. You already read that one. Test boost.

982
01:29:42,684 --> 01:29:47,268
And then we got the delimiter, Common Street Blogger, 20,000 sats through Fountain.

983
01:29:48,155 --> 01:29:52,644
A CompStript blogger, all the other boosts are a train wreck.

984
01:29:53,083 --> 01:29:58,851
Comestrip blogger comes through loud and clear every single week. I know. I know. I don't know why.

985
01:30:00,028 --> 01:30:01,188
Howdy, Dave and Adam.

986
01:30:01,564 --> 01:30:03,971
Today, I want to recommend a podcast by James Cridley.

987
01:30:06,011 --> 01:30:15,619
.

988
01:30:16,283 --> 01:30:30,275
Yo, CSB, AI, Arch Wizard, PS, Adam. Yes. You spend many hours talking fictitious deities, not even Cthulhu or Roko Boss Basilisk with Jimmy, who, it's a fact, is a fully paid church employee.

989
01:30:30,779 --> 01:30:36,420
So when you'll give me, not a Skynet employee, a short 33-minute max interview.

990
01:30:36,764 --> 01:30:42,435
Well, that was a grammatically okay, but very long sentence.

991
01:30:42,876 --> 01:30:59,500
Yes, comics or blog. I just need a day. A day. I got no time in my life. It's crazy. And I thought I'd have time today, and I committed to cleaning up the studio. It's sentences like that that make you really question Noam Chomsky's theories. Okay.

992
01:30:59,528 --> 01:31:02,608
We can't get into that, Dave. I got a studio to clean.

993
01:31:03,112 --> 01:31:05,583
All right. Is that it? That's it with the delimiter?

994
01:31:05,992 --> 01:31:23,887
Thank you all very much for supporting the podcast index. You know, we want this to be with us for a long time. We feel it's important. That's why we're here. You know, Dave and I both have other things to do, but we love doing it. We do it as a public service.

995
01:31:24,231 --> 01:31:46,448
You should consider yourself lucky that it's there. I mean, really, just keep the machines running. Dave and Adam get none of this. This goes into the podcastindex.org account, and it funds the machines, the many machines, this space, et cetera, et cetera. The time and the talent is just a bonus that you get from us because we love doing it, and it's important for podcasts.

996
01:31:46,600 --> 01:31:56,655
It's important for the world, for the universe, I would say. We should get a Nobel Peace Prize. Dvorak says it all the time. We should get a Nobel Peace Prize for this. I agree. I agree.

997
01:31:57,576 --> 01:31:58,500
um

998
01:31:58,655 --> 01:32:15,399
And we'll get one right after Donald Trump gets one. Thank you, Boardroom, for being here. And especially, I really I want to thank PJ Mac HVAC Air Duct Cleaning for all the great work that you're doing. Perfectly clean duct work.

999
01:32:16,032 --> 01:32:18,952
We clean out our ducks, baby. It's great.

1000
01:32:20,159 --> 01:32:20,648
board meeting.

1001
01:32:22,112 --> 01:32:25,351
Have a good weekend, everybody.

1002
01:32:30,399 --> 01:32:31,336
Bye.

1003
01:32:37,600 --> 01:32:38,760
You did you.

1004
01:32:39,264 --> 01:32:41,448
been listening to Podcasting Too.

1005
01:32:43,456 --> 01:32:44,072
in this

1006
01:32:45,568 --> 01:32:46,760
Go!

1007
01:32:49,279 --> 01:32:50,311
It's hard, man.