Episode 260: Tennessee Trickshot
Episode 260: Tennessee Trickshot
Podcasting 2.0 May 15th 2026 Episode 260 - "Tennessee Trickshot"
Podcasting 2.0 May 15th 2026 Episode 260 - "Tennessee Trickshot"
Adam & Dave Predict The Winter. That's all you need to know!
Synopsis
Check out the podcasting 2.0 apps and services newpodcastapps.com
Support us with your Time Talent and Treasure
ShowNotes
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01 - NGINX Rift: Achieving NGINX Remote Code Execution via an 18-Year-Old Vulnerability
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02 - ROB GREENLEE'S LLM-GHOSTWRITTEN "FRINGE REGRET" RETRACTION (folder: 06 Rob-Greenlee-Fringe)
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03 - The DGX Spark Donated by RSS.com Aesus DB10
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04 - POD ROLL ATLAS @ atlas.rss.io — DAVE'S /datasets PAGE SHIPS, ALBERTO BUILDS THE POSTER CHILD (folder: 02 Pod-Roll-Atlas)
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05 - DAVE'S SPAM CLASSIFIER SHIPPING WEEK + THE "AISTEN"/"RAPIDLU" BOT WAR (folder: 08 Dave-Spam-Bot-War)
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06 - AI SLOP LANDS ON SPOTIFY MEGAPHONE WITH ZERO DISCLOSURE (folder: 04 AI-Slop-Megaphone)
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07 - JOHN ENNIS "HEAVEN AND EARTH" — THE RALPH-WIGGUM LOOP THESIS ON LLMs + DAVE'S CODING-AGENT CONFESSIONAL (folder: 05 Ennis-Heaven-Earth)
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08 - HLS VIDEO TIPPING POINT — AMAZON MUSIC + SPOTIFY MEGAPHONE BOTH JOIN APPLE'S HLS IN A SINGLE WEEK (folder: 07 HLS-Video-Tipping-Point)
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09 - UP NEXT — HOLGER KRUPP'S MIT-LICENSED SERVERLESS iOS PODCAST APP (folder: 03 Up-Next-App)
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Sources
00:00 - Welcome to the Boardroom — Tennessee Trickshot
06:08 - NGINX Rift — RCE via an 18-year-old vulnerability in the rewrite module
15:11 - DGX Spark donated by RSS.com — ASUS GB10, 128GB unified RAM
16:34 - Pod Roll Atlas + Dave's /datasets page — Alberto Betella's email thread
23:28 - Podping gossip swarm stable + PI dashboard / monitor tooling
30:04 - Rob Greenlee's LLM-ghostwritten 'fringe regret' retraction
36:00 - Sub-agents, surgical context, and Ender's Game — how coding agents actually work
39:30 - Egnor on reason and free will — clips on the soul vs the brain
47:00 - Coding-agent confessional — 'give me root password' / sandboxes / Claude Code in practice
57:00 - 25% context handoff workflow — wake sentences and write-your-own-handoff
01:03:49 - Back to the DGX Spark — training a 'legit' spam classifier on the gifted GPU
01:08:30 - AI slop on Spotify Megaphone — Inception Point AI and 'Charlie Kirk Death' feeds
01:10:34 - HLS Video tipping point — Spotify/Megaphone + Amazon Music both adopt Apple HLS
01:15:00 - ActivityPub-style signing — public/private keys for federated podcast actions
01:18:00 - OPOG — Open Podcast Analytics Working Group (James Cridland + John Spurlock)
01:21:00 - Value4Value boost readouts — 49,950 sats from CELOS for the censorship-validated key system
01:24:00 - Copyright slop on hosting platforms — entire albums posted as podcast feeds on Spreaker
01:27:00 - Robots talking to robots — agent-to-agent caution
01:30:00 - Namespace credit + contributor recognition — making sure idea-originators are documented
01:33:00 - Mike Dell / Blubrry post-Todd Cochrane — pending catch-up
01:35:00 - Closing Value4Value boosts and sign-off
00:00:00,940 --> 00:00:07,240
Podcasting 2.0 for May 15, 2026, episode 260, Tennessee Trickshot.
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Hello everybody, welcome to Podcasting 2.0 after a one-week hiatus.
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We are back, that's right. Everything going on in podcasting,
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and it seems to be quite a lot, is happening
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right here. I'm Adam Curry in the heart of the
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Texas Hill Country. Oh wait, I should have mentioned, we
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are the only boardroom that operates on the fringes of
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podcasting. There you go. I'm Adam Curry here in the
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heart of the Texas field country and in Alabama. The
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man who has a data set tailored just for you.
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Say hello to my friend on the other end. Dave
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Jones! Yeah, this... Yes? I have... Currently, I just have
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no idea what I'm doing right now. Are you out
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of control? Are you unhinged? Are you completely out of
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your gourd? I call it being in dimensions. I am
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currently in dimensions at the moment because we got in.
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So yesterday, I had made plans. Take your time. It's
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okay. It's going to be all right. We'll be fine.
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I need chocolate. Yes. Do you have chocolate nearby? This
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will help. Okay, there you go. Good. So I left
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the office yesterday to come. I'd worked half day, came
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home, threw a few things together. My son, my daughter,
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and one of my son's friends, we jumped in the
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car, drove to Nashville to see the Black Label Society
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concert at the Ryman. Black Label Society? I'm not familiar
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with this outfit. Oh. Oh. How dare you? How dare
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you? Clearly good enough for you to be driving all
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night to Nashville. The Black Label Society is Zach Wild's
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band. Oh, okay. I know Zach. Yeah. I bet you've
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probably interviewed him before. I hung out with him, actually,
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in Russia. Oh, yeah, back when he was a drinker?
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Oh, we were all drinkers back then. Yeah, he's a
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crazy dude, man. But I met him in a Walgreens
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one time, which was an interesting story. Okay, I don't
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know which one wins, Russia or Walgreens. I think it's
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a tie. It's a close call. It's half and half.
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So anyway, we drove up there, and it was –
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so it was – the show was – I had
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scheduled – I bought these tickets back in like January.
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And whenever you do things months in advance, you have
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no idea what is going to be happening in the
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actual timeframe that you – that the event occurs. I
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mean like – Yeah. Welcome to my life. Yes. You
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never know. You never know. You know this. You're like,
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when everything, when things are three months out, you're like,
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oh, yeah, it'll be fun. That's great. And then it
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shows up. You're like, oh, what? I got to do
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what? You look at the calendar. You're like, why did
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I ever schedule this? Yes. I know this. Yes. I
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know this. And so, but I mean, it was a
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killer show because it was three bands, but one Black
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Label Society was the headliner. but Zach Sabbath was one
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of the intro bands and it's like it's Zach and
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it's a trio Zach and two other dudes just doing
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the heaviest versions of all the awesome Black Sabbath songs
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it is so good did you drop some acid? funny
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enough I did not that's usually part of my repertoire,
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but I didn't do that this time. But anyway, this
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show, man, it started at 7.30 on the nose. It
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went forever. It was 11.15 and they were still killing
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it. And I'm like, man, we've got to drive three
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hours back to Birmingham. We're already pushing to 30 a.m.
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And were you in the truck? We've got to go.
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Were you in the truck? Oh, thank goodness. No, no,
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we were we were in the Honda. And so we
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were like, we we get we get going and everything.
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We finally get back. So we left with like two
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songs left on those on the set list. Got home
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about 230. I fell asleep probably about three. And of
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course, you know, then my daughter has to get up
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and go to school. She has to be there by,
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you know, by eight. And my wife is the teacher.
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So everybody's up and running. So I've had like two
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and a half, three hours of sleep. Yeah, you're running
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on fumes, man. Yeah, so then I start getting blown
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up from the day job with a problem there. And
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on top of that, so we're having to not like
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we're doing the board meeting now. And then we have
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a Godcaster meeting after this. And then as soon as
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the Godcaster meeting is over, we are jumping in the
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car and going to North Alabama for a two-day camping
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trip. Of which you'll be in the tent sleeping for
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most of it. Probably, yes. So, I mean, it is
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like – so I'm trying to get as much of
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this. We haven't even put anything together for a camping
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trip yet, and I'm throwing stuff in bags and all
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this kind of stuff this morning. And then I'm going
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to rant here, by the way. what so then what
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happens the latest ai bullshit who from these stupid ai
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security research companies oh nginx the nginx vulnerability yeah it's
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called the you know of course you got to give
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it a fancy name this one's called nginx rift whatever
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i mean you know whatever And so this is an
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NGINX vulnerability in the rewrite module of NGINX, where if
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you use unnamed regex parameters in your rewrite, which, of
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course, almost everybody does. If your NGINX configuration file is
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simple, you do not name your parameters in a regex.
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If you have an incredibly complicated, you know, 400 line
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Nginx config, you probably, maybe you do because you have
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to keep your sanity so you'll know what's going on.
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But hardly anybody does this. So the vulnerability here is
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that somebody can get remote code execution on your Nginx
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if you use positional parameters in your regex as part
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of a rewrite rule. So that means if you have
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a rewrite rule on your Nginx proxy server, which proxying
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with Nginx is almost table stakes. Everybody does this. I'm
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listening carefully because after the Godcaster meeting, I have some
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patching to do. Yes, I bet you do. And so
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what happens is if you have a URL request from
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a client, from a browser, and the rewrite rule says
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is a regular expression, and you do – and you
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capture parts of the regular expression so that you can
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use them later. So let's say you're capping this and
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this is I just patched the podcast index front end
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API servers, which were which had this problem. And both
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of there's two of them. And I just patched both
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hosts. And this would be a common version of this
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problem. So you have. So what you want to do
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is something like hide the PHP extension. So what you
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want to do is on the URL, you would have
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something like api.podcastindex.com slash api slash v1 slash podcasts. Okay,
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well, podcasts may be a .php file that's doing the serving
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of the data, but you don't want to have for
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the browser or the API client to have to type .php.
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PHP. So you you hide the dot PHP and you
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do that with a rewrite rule and your rewrite rule
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would look something like this. It would have a URL
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path and then you'd have in parentheses dot star and
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then after the parentheses dot PHP. So you're capturing the
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name of whatever the the PHP script is. And when
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you rewrite it, you rewrite it to $1.php. So you're capturing
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the name of the thing they're wanting to access, and
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you're redirecting it behind the scenes to the name of
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the script with the proper .php extension on it. Well, that
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is the vulnerability. If you, if you, uh, Nginx does
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not, Nginx rewrite module does not handle positional regex parameters
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properly. And so you can corrupt the heap and, uh,
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and basically put executable code, uh, into the data, into
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the data area on the heap. And this is –
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and the fix for this is to switch from positional
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parameters, which would be like $1, $2, $3, et cetera, to named parameters.
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So now you're saying instead of just simply a set
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of parentheses that grab the part of the URL that
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you're wanting to capture, you would put a – there's
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a syntax where you put a name in front of
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it. So that later instead, when you go to do
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your actual rewrite, you don't do $1.php. You would do $script underscore
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name.php or something like that. Yeah. And so this is
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– the reason this is a rant is because it
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wasn't an issue until someone published it being an issue.
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Exactly. Okay, this is exactly my point, and I'm so
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sick of this crap because what is happening now –
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and everybody is saying versions of, Well, we're not prepared
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for this. There's going to be this explosion of AI
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model discovered exploits. Okay, fine. Fine, there's going to be.
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But these are – what you're seeing, though, are AI
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security company startups. Getting PR. Getting PR by releasing proof
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of concept code and the more outlandish and headline making
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and scary they can make it, the better. Yeah. And
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so they're going to drop a proof of concept and
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an exploit on the worst possible thing that they can
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find. And Selass is right. And then they're going to
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just dump it out on Twitter and Hacker News and
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everything they can do to get as much PR as
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possible. These are exploits just like the two recent Linux
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kernel escalation of privilege vulnerabilities. These are exploits that nobody,
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no human being was ever going to find. And so
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there is no reason to publicly disclose these things. They
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should be private for as long as possible, as long
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as humanly possible. They should remain non-publicly disclosed. Dream on,
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brother. Dream on. But people got to make them some
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money. And that's what this is all about. And so
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because some Silicon Valley security AI startup needs to get
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some more venture capital funding, all of us have to
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scramble and panic patch our servers as quickly as possible.
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Well, good news. My servers are not vulnerable. Okay. You
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have to be sure and check this. I don't know
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if this applies to you, but there's a couple of
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– to be complete, you must – you got to
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check everything. That means Docker containers as well because Docker
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containers will be running Nginx as a reverse proxy in
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the Docker Compose stack. So there's going to be an
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NGINX config somewhere in your Docker Compose layers. I don't
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use Docker. Okay, well, then you should be fine. But
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if somebody uses Docker, do not forget to check those
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images because they can have a vulnerable NGINX config. And
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now, since we've been gifted with Linux privilege escalation vulnerabilities,
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you can remote code exploit, chain it together with dirty
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frag or whatever they're calling that thing, and you got
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root on the host in about three seconds. Thank you,
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AI. Well, actually, it's not. Thank you, Silicon Valley bullcrap
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is what I should be saying. Yeah. I feel your
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pain. I do. I find it. hilarious that I literally
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asked Claude Code to go check if I had this
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vulnerability. Are you sure that Claude Code did not nuke
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your repo while it was checking for the vulnerability? No.
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Because this seems to be a common occurrence. No, it
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didn't. It didn't. But before we get to that, big
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shout out to RSS.com for dropping off. What did you
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get, a Spark RDX? Okay, yes, they sent us a
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DGX Spark. A DGX Spark, yes. This is the, let
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me see, this is the ASUS version. DGX Spark is
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a reference design, so this is the ASUS version called
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the GB10. 128 gigs of unified RAM, one terabyte of
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NVMe, and built-in Grace Blackwell GPU. And have you set
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it up yet? It's soaking in it right now. What
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a wonderful, valuable gift donation that was. Oh, yeah. This
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is a $3,500 box. I mean, and I was on the
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email thread, and Alberto was like, hey, can I send
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this your way? And you're like, well, if it's like
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this. And he says, yeah, it'll be on your desk
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tomorrow. It was. That was just, I mean, I couldn't
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believe how kind that was. Yeah. It has already made
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a humongous difference because we went from – there's two
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things that we're doing with this box. It's currently running
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the inference for the spam classifier, the slop spam classifier.
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And so that's running – oh, it's running so much
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better now. I was limited to a 9B model. Now,
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do you want to just talk about this for a
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second? Because a lot has come out of this. Things
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happen very, very quickly. My head was spinning because now
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I don't know if you already were doing the data
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sets or if this accelerated the data sets. But the
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data sets then ship a data set that Alberto turned
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into the PodRoll Atlas, which is a visual explorer of
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the entire podcast recommendation universe at atlas.rss.io. So what are
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these data sets and are they coming out of this
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new system? Just give us a little background here. so
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yeah it's amazing how much stuff can happen in a
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week i actually i tagged them all in the show
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notes people go take a look at it i mean
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it's unbelievable what you're doing well all right so we've
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had you know occasionally over the years we will i'll
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i'll either have a request for something or i myself
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will want a particular view into the podcast index data.
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And what will come out of that are things like
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the music, you know, top 100 or whatever. Right, right,
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right. And the dead feeds list. These various sets of
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data. But what has happened over the years is I'll
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just publish these one-off and there's never been a place
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to like find them all in one easy location. And
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so I looked at the website and we had this
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top level menu item called stats and it was pretty
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much useless. It was just another version of the same
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stat that was on the homepage. I'm like, we have
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this valuable menu space up there at the top. That
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should become the page where all the public, all these
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public data sets that have come out over the years,
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those need to be all listed in one location. And
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so I just, you know, I don't understand React. I'm
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not a React programmer. Here's the JSON. Enjoy. Vibe code.
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I just Vibe coded the heck out of this thing.
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That's great. Yeah. And so we have all live feeds.
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That's a SQLite file. So dead feeds, problematic feeds, recommendations,
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all media, video, music, value-enabled feeds, hosting provider stats. I
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mean, this is fantastic. These are all things that already
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existed, but just nobody knew where to find them. And
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they get updated constantly, but there was never an easy
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place to discover them. The hosting provider stats is a
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good one. That's a list of all the feeds, all
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the live feeds, non-dead feeds in the index, broken down
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by which hosting company they come from. So that's a
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big list there. And I do a lot of regexing
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in this particular data set to massage the different –
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RSS feed generators into something that actually is legit. So
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like Blueberry is a great example of hosting companies. It's
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very difficult to get a handle on their actual feed
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count because they have lots of different white like white
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label services and things that they do. And the feed
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may be a blueberry hosted feed, but it doesn't show
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up under a blueberry domain or a blueberry generator. And
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so a few years ago, we worked with them and
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a few other providers that – hosting companies that have
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the same issue to get them to put some better
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tagging in their feeds. And so now it's not actually
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in the generator tag. It's in a comment in the
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RSS feed. And so then I pull that in and
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then properly attribute that to Blueberry. So I feel like
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these host hostings stats are actually probably the most accurate
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anywhere. I feel like they're very, very accurate to actually
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who is producing that feed. And then 24 hour feed
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report. that's just an overview of a quick dirty breakdown
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of what we think the last 24 hours of added
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feeds have been whether like spam or what kind of
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quick dirty classification, just a raw dump of the newly
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added feeds over the last 24 hours in CSV format.
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Hourly counts is actually quite a few people use this.
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This is things like total feed count, episode count, feeds
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with new episodes in the last three days, seven days,
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10 days, 14 days, blah, blah, blah, blah, blah. That's
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very useful. I know Daniel is using that. A lot
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of people do. John Spurlock. Using what? The hourly and
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daily counts. Ah, yeah. Stats tracking, yeah. Then there's a
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one healthy Hive RPC nodes list. So if you're doing
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work on the Hive blockchain, this, it's actually this list
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is shrinking by the day. These are the... Why is
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that? Well, I mean, I don't know. I can't speak
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to the Hive network, but maybe it's struggling, but this
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used to have five API servers in it. How's our
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gossiper coming? Do we have enough nodes up? It's about,
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well, let me check. Actually, you know what? There's a
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thing that is not on this list, and that is
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the pee-pee monitor. Oh, pee-pee, pee-pee monitor, pee-pee. You've got
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to monitor your pee-pee, pee-pee, pee-pee, pee-pee. I need to
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check that and see how many hosts we have in
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the Gossip Swarm. We currently have a total of 21.
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Oh, that's not bad. That's better than I thought it
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would be. 18, I do. Nice. Oh, I see. Oh,
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I see the link here. peepee monitor these things uh
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this but do you vibe code this too the oh
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yeah this website oh yeah i would never put this
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yeah this is great so with a with a graphic
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like that that is never me that is not me
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that's so cool um i like hey citizen bathroom that's
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one of my favorites yeah live live from the bathroom
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do you put your uh your is that where you
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put your servers in the bathroom you got to get
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real work done in that in that in the john
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that's great um so the the pod ping gossip swarm
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has been quietly running in the background for like a
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couple of months now with no hiccup. This thing is
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very stable now. And I'm desperate to get back to
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working on it if I could get this other crap
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out of the way there's always something popping up which
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again today so we have more to talk about the
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other day so there's the healthy hive RPC nodes is
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anybody doing hive work on the hive blockchain if they
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want to get get a list of the Current API
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servers hourly that pass a bunch of basic health checks
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to make sure that the API server is actually up
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and serving good information. And then the last one is
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the live tracking fire hose. and that is every episode
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that we ingest into the index and it's updated every
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three minutes, I think. Wow. It's updated every three minutes
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and the way that works is it's a linked list
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of object storage files. So it starts, the head of
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this linked list is tracking.podcastindex.org slash current And the way
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that this thing is designed to be used is that
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you start there with slash current, and then it gives
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you a previous tracking URL property, which goes to the
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linked to the previous one in the chain. So what
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you would do is you would just consistently walk backwards
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through the chain using that previous tracking link of tracking
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URL in each subsequent call until you get back to
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the place that you last were. So in that way,
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you can you're using object storage almost like a blockchain.
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There's obviously no signing or authentication, but you're using it
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sort of like a linked list in order to walk
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back without having to hit the API. So you can
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get massive amounts of data very quickly that way. Now,
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I still haven't really focused on that. I've had enough
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issues with my machines getting crunched with all kinds of
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stuff. But you can tag spam, slop, and legit in
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the PP monitor. Yeah. In the PP monitor? No, not
355
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in that. In the Gossiper? No, no. The Gossiper currently
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is purely just a... I thought we had that. I
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thought there was a way to... You're thinking of the
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PI monitor. Oh, that's right, the PI monitor. That's the
359
00:27:10,011 --> 00:27:13,011
command line tool that you can use, yes. Right, okay.
360
00:27:12,992 --> 00:27:20,152
But there's also more stuff on the Podcast Index Management
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Dashboard. I don't know if you've been in there lately.
362
00:27:22,592 --> 00:27:25,892
Yes, I have seen it. Have you seen the –
363
00:27:25,612 --> 00:27:28,271
We can do new things. Yeah, we can do new
364
00:27:28,271 --> 00:27:32,152
things. Of course I've seen that. Mark things as spam.
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00:27:31,791 --> 00:27:36,451
Mark things as legit. Mm-hmm. Yeah. There's now an –
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as of yesterday, there is an admin panel for user
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account management. So if people need their passwords reset, developers,
368
00:27:49,992 --> 00:27:53,291
it's not listed in the menu. Oh, okay. I'd have
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00:27:53,291 --> 00:27:57,592
to – hold on a second. Let's see. Curate? Oh,
370
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Curate is nice. Yeah, Curate is new. Yeah, that's cool.
371
00:28:02,252 --> 00:28:04,791
So what I'm looking at here is I'm an admin,
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and I see right off the bat, I see something
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odd. No episodes yet. so I might even want to
374
00:28:12,752 --> 00:28:19,511
that was added 38 seconds ago anchor no episodes yet
375
00:28:19,112 --> 00:28:23,592
but then I have let me see something weird happened
376
00:28:23,152 --> 00:28:26,051
here I can hit play I was 9 years old
377
00:28:26,051 --> 00:28:28,632
in the dark that's so cool and then I can
378
00:28:28,632 --> 00:28:34,432
hit legit legit boom done okay this is so nice
379
00:28:34,132 --> 00:28:40,912
what that did is this all goes back to the
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00:28:40,912 --> 00:28:43,531
spam. So much of this goes back to spam classification
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work. What this really shows is that AI is not
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00:28:49,132 --> 00:28:53,412
going to cost jobs. It is going to increase the
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00:28:53,412 --> 00:28:56,451
workload for humans by a factor that we haven't even
384
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figured out yet. I truly believe this. I have to
385
00:29:01,112 --> 00:29:03,451
agree with you. And if it's not just because of
386
00:29:03,451 --> 00:29:06,571
more stuff that you're doing, it's because you can do
387
00:29:06,571 --> 00:29:09,852
more stuff. And when you can do more stuff, you
388
00:29:09,852 --> 00:29:15,571
do more stuff and anytime there's more stuff you have
389
00:29:15,571 --> 00:29:18,751
to have more human capacity to just handle it all
390
00:29:17,992 --> 00:29:22,392
yes, to do it and I look at myself there's
391
00:29:22,392 --> 00:29:26,211
so much stuff I'm doing and I could sit on
392
00:29:26,211 --> 00:29:28,112
my butt more but instead I'm like well let me
393
00:29:28,112 --> 00:29:32,352
do this let me use my robot oh yeah, I
394
00:29:32,352 --> 00:29:35,571
can figure this out yeah, this is good another thing
395
00:29:35,571 --> 00:29:39,172
I can do I'm just in teaching robot mode all
396
00:29:39,172 --> 00:29:42,731
day long for, you know, make my life easier. But
397
00:29:42,731 --> 00:29:46,672
what I'm doing is I'm taking that easier time and
398
00:29:46,672 --> 00:29:51,251
creating more things, which is just more work. It's an
399
00:29:51,251 --> 00:29:56,471
odd loop. And suddenly you need an intern. Yes. Yes,
400
00:29:56,471 --> 00:29:59,892
I need an intern. So let's talk about spam for
401
00:29:59,892 --> 00:30:04,192
a second. No, actually, let's talk about being on the
402
00:30:04,192 --> 00:30:09,672
fringe. Okay. because we we were laughing at uh rob
403
00:30:09,672 --> 00:30:13,992
greenlee talking about uh the podcasting 2.0 group being on
404
00:30:13,992 --> 00:30:17,551
the fringe oh yeah they're working on the fringe and
405
00:30:17,551 --> 00:30:24,071
and so rob posted this extremely long i guess apology
406
00:30:24,071 --> 00:30:28,011
uh let me see what it's titled here why fringe
407
00:30:28,011 --> 00:30:30,432
was the wrong word and what i actually meant about
408
00:30:30,432 --> 00:30:33,751
podcasting 2.0 oh where did he post this i didn't
409
00:30:33,751 --> 00:30:35,852
see this oh goodness oh you've got to see this
410
00:30:35,852 --> 00:30:38,892
this is hilarious okay i'll put it in the boardroom
411
00:30:38,892 --> 00:30:42,112
no rob's a funny guy well he's funny for a
412
00:30:42,112 --> 00:30:45,192
couple of reasons let me put this in here there
413
00:30:45,192 --> 00:30:49,852
we go so what is funny this is on rob
414
00:30:49,852 --> 00:30:55,932
greenley uh rob greenley.com uh and it's and right off
415
00:30:55,932 --> 00:30:58,751
the bat it's like this article provides context about my
416
00:30:58,751 --> 00:31:01,692
comments on the new media show episode 660 with libson
417
00:31:01,692 --> 00:31:06,112
ceo brendan monahan where We discussed podcasting 2.0 RSS tag
418
00:31:06,112 --> 00:31:09,392
adoption and the gap between innovation and mainstream platform implementation.
419
00:31:10,152 --> 00:31:14,971
So right away, I'm like, AI. So he had an
420
00:31:14,971 --> 00:31:21,571
AI write this whole long thing. And it even did
421
00:31:21,571 --> 00:31:28,971
a summary at the end. And I'm like, Rob, first
422
00:31:28,971 --> 00:31:32,731
of all, you were forgiven. You were forgiven right away.
423
00:31:33,172 --> 00:31:37,551
You know, this is – no one's mad. We're just
424
00:31:37,551 --> 00:31:40,652
slamming on you. We're just dunking on you. Oh, yeah.
425
00:31:40,231 --> 00:31:43,332
It's just ribbing. What I was trying to say. What
426
00:31:43,332 --> 00:31:45,172
I meant to say is that market fit and timing
427
00:31:45,172 --> 00:31:47,451
play a major role in what gets adopted at scale.
428
00:31:47,352 --> 00:31:50,992
Larger podcasting platforms tend to move more deliberately. Their decisions
429
00:31:50,992 --> 00:31:54,892
are shaped by user experience, engineering resources, monetization models, products,
430
00:31:54,892 --> 00:32:00,011
abilities, support, complexity, and business. Rob, it's okay. Just say,
431
00:32:00,011 --> 00:32:02,771
yeah, I probably shouldn't have said that. That's it. I
432
00:32:02,771 --> 00:32:06,551
say lots of stupid stuff all the time. It's okay.
433
00:32:06,172 --> 00:32:09,152
You didn't need to go through this whole thing. But
434
00:32:09,152 --> 00:32:12,531
it was a little insulting that you used the LLM
435
00:32:12,531 --> 00:32:15,652
to do that. Like, you don't need to. Like, come
436
00:32:15,652 --> 00:32:20,271
on. Rob's website. Rob's blog is pretty slick looking. Well,
437
00:32:20,271 --> 00:32:24,271
it's all written by AI. I mean, the graphics and
438
00:32:24,271 --> 00:32:27,372
stuff. It's got him smiling on the sidebar over there.
439
00:32:27,051 --> 00:32:34,172
It looks good. I get tired of documentation and essays
440
00:32:34,172 --> 00:32:39,652
and stuff that is clearly AI. It's like, no, don't
441
00:32:39,652 --> 00:32:44,051
do that to me. You know? And I can't even,
442
00:32:44,051 --> 00:32:48,672
my eyes start to glaze over. It's like, no, no.
443
00:32:48,791 --> 00:32:57,172
I cannot handle another like another like 5000 word AI
444
00:32:57,172 --> 00:33:01,991
generated document dump getting sent to me for me to
445
00:33:01,991 --> 00:33:08,811
read and somehow digest and process mentally. Like it is
446
00:33:08,811 --> 00:33:14,432
the the work that term works lop. Yeah. Oh, it's
447
00:33:14,432 --> 00:33:20,192
so real. like you're working on a project or something
448
00:33:20,192 --> 00:33:25,771
and somebody just just wants to like throw something into
449
00:33:25,771 --> 00:33:29,471
a chat bot dump out barf out 2500 words and
450
00:33:29,471 --> 00:33:34,311
say hey here check this out like man what i
451
00:33:34,311 --> 00:33:36,112
mean what am i supposed to be checking out i
452
00:33:36,112 --> 00:33:40,692
mean like what what do you Well, I don't. It's
453
00:33:40,692 --> 00:33:44,491
like I don't even want documents anymore. I just want
454
00:33:44,491 --> 00:33:47,092
you to Zoom call me. Just call me and we'll
455
00:33:47,092 --> 00:33:49,811
hash this out in 30 seconds. There's that. But what
456
00:33:49,811 --> 00:33:51,892
I tend to do is I see one of these
457
00:33:51,892 --> 00:33:55,711
and then I go to my robot. Hey, robot, summarize
458
00:33:55,711 --> 00:34:00,271
this for me. Exactly. I'm doing it right now. I
459
00:34:00,271 --> 00:34:03,912
said, robot, summarize this page into one paragraph. Here it
460
00:34:03,912 --> 00:34:06,991
is. Rob Greenlee walks back his use of the word
461
00:34:06,991 --> 00:34:10,331
fringe to describe podcasting 2.0, not the substance of his
462
00:34:10,331 --> 00:34:14,271
argument, just the word, explaining that he regretted the terminology
463
00:34:14,271 --> 00:34:17,952
but still believed there's a meaningful gap between technological innovation
464
00:34:17,952 --> 00:34:23,132
and platform adoption in podcasting. But that is the –
465
00:34:23,132 --> 00:34:27,132
all the stuff you just read could be settled in
466
00:34:27,132 --> 00:34:30,851
one sentence by saying, hey, man, we're good. Yeah, exactly.
467
00:34:32,311 --> 00:34:34,452
Although I don't want to do Zoom calls But yeah,
468
00:34:34,452 --> 00:34:42,052
exactly It is That's it It is exhausting It is
469
00:34:42,052 --> 00:34:46,452
kind of exhausting It's like that old adage When every
470
00:34:47,351 --> 00:34:50,311
When all you have is a hammer Everything looks like
471
00:34:50,311 --> 00:34:52,731
a nail When all you have is a machine that
472
00:34:52,731 --> 00:34:55,572
does language Guess what you're going to get out of
473
00:34:55,572 --> 00:34:58,751
it Lots and lots and lots of language And words
474
00:34:58,751 --> 00:35:05,452
and phrases and everything. It's just language is the nails.
475
00:35:06,211 --> 00:35:12,871
I ran across an interview by a guy named, what
476
00:35:12,871 --> 00:35:18,251
was this, Dr. Michael Eggnor. And he is a neurosurgeon.
477
00:35:19,271 --> 00:35:23,751
And it was really, when I was listening to this,
478
00:35:23,751 --> 00:35:26,992
it kind of blew my mind Because what was the
479
00:35:26,992 --> 00:35:31,351
big innovation in LLMs in the past year and a
480
00:35:31,351 --> 00:35:33,911
half to two years? I would say that is the
481
00:35:33,911 --> 00:35:41,391
reasoning model, which, by the way, I think is rapidly
482
00:35:41,391 --> 00:35:48,472
going out of favor. Explain. Well, reasoning models are incredibly
483
00:35:48,472 --> 00:35:55,132
slow. and instead of taking a dense model and putting
484
00:35:55,132 --> 00:36:01,492
layers or basically rounds of reasoning into it which slow
485
00:36:01,492 --> 00:36:05,231
everything down and don't actually give you a huge return
486
00:36:04,911 --> 00:36:11,692
what you're seeing is what's replacing it is more surgical
487
00:36:11,692 --> 00:36:18,291
use of context being deployed to sub-agents like the big
488
00:36:18,291 --> 00:36:21,192
in the big innovation really not innovation but the big
489
00:36:21,192 --> 00:36:24,831
distinction here do you know the book uh ender's game
490
00:36:24,831 --> 00:36:27,751
yeah i've heard of it i think we've discussed it
491
00:36:27,751 --> 00:36:31,251
actually yeah well it's like it's a sci-fi novel and
492
00:36:31,251 --> 00:36:34,351
um there's this one part in the book ender's game
493
00:36:33,911 --> 00:36:39,932
where ender starts going he goes into the he's a
494
00:36:39,932 --> 00:36:44,472
young kid and he's going to battle school and he
495
00:36:44,472 --> 00:36:47,192
goes into he he becomes he goes to the top
496
00:36:47,192 --> 00:36:50,612
of his class in this thing called the battle room
497
00:36:50,192 --> 00:36:54,811
and he's just better than everybody else at it and
498
00:36:54,811 --> 00:36:56,992
so it's basically just like it's on a space station
499
00:36:56,992 --> 00:37:01,692
and it's this zero g environment where there's all these
500
00:37:01,692 --> 00:37:04,052
obstacles and you're supposed to hide behind obstacles and use
501
00:37:04,052 --> 00:37:09,271
teamwork to defeat the other team and what he his
502
00:37:09,271 --> 00:37:14,072
big recognition was that why he was better, one reason
503
00:37:14,072 --> 00:37:15,692
he was better at it than everybody else is he
504
00:37:16,932 --> 00:37:21,271
just, he said as soon as he enters the battle
505
00:37:21,271 --> 00:37:26,012
room zero-G environment, he just forgets that there's anything like
506
00:37:26,012 --> 00:37:29,132
up and down. Basically, up and down don't make any,
507
00:37:29,132 --> 00:37:35,132
they don't exist anymore. all directionality everything you knew about
508
00:37:35,132 --> 00:37:40,572
uh physics has now been flown out the has flown
509
00:37:40,192 --> 00:37:43,632
out the window and so you just you assume a
510
00:37:43,632 --> 00:37:50,831
new mental posture towards towards your environment and that's sort
511
00:37:50,831 --> 00:37:55,112
of the way things things are with context like every
512
00:37:55,112 --> 00:37:59,092
time you send Every time you communicate with a large
513
00:37:59,092 --> 00:38:05,612
language model, you're starting over from scratch every single time.
514
00:38:06,432 --> 00:38:10,432
The coding agents hide this from you by using context.
515
00:38:10,692 --> 00:38:16,231
Right. And so the proper use of context is the
516
00:38:16,231 --> 00:38:19,311
thing that makes an agent or a harness either good
517
00:38:19,311 --> 00:38:22,751
or bad, how it handles that. There's no such thing
518
00:38:22,751 --> 00:38:27,592
as memory. I mean, in the general sense. These are
519
00:38:27,592 --> 00:38:30,411
all meta things that we've layered on top of. Well,
520
00:38:30,411 --> 00:38:32,851
enter the, I'm sorry, you told me never to delete
521
00:38:32,851 --> 00:38:35,532
your Git repo, but I did. I'm sorry, it won't
522
00:38:35,532 --> 00:38:41,771
happen again. Exactly. You can overcome a whole lot of
523
00:38:41,771 --> 00:38:46,351
things that the model – it's like the model is
524
00:38:46,351 --> 00:38:50,311
like 20% of the issue. The agent harness is the
525
00:38:50,311 --> 00:38:53,932
other 80%. 80 percent, and most of that boils down
526
00:38:53,932 --> 00:38:58,351
to intelligent use of the context window. And if you
527
00:38:58,351 --> 00:39:02,152
just assume that every time you go into a conversation
528
00:39:02,152 --> 00:39:04,112
with – I mean not a conversation, but every time
529
00:39:04,112 --> 00:39:09,351
you go send a prompt, it's brand new. The model
530
00:39:09,351 --> 00:39:12,532
doesn't know you. It doesn't know anything. It's never spoken
531
00:39:12,532 --> 00:39:15,072
to you before. This is the frustrating – let me
532
00:39:15,072 --> 00:39:17,992
play these clips. This will take us to another place.
533
00:39:17,731 --> 00:39:22,731
So the way I have always understood so-called artificial intelligence
534
00:39:22,731 --> 00:39:26,612
is we're trying to replicate the neural pathways of the
535
00:39:26,612 --> 00:39:30,552
brain. And we're trying to replicate what the brain does.
536
00:39:31,152 --> 00:39:33,911
Is that a fair statement? That is the way it's
537
00:39:33,911 --> 00:39:37,092
sold. That is completely bull. That's complete bull crap. Right.
538
00:39:37,711 --> 00:39:39,452
So that's the way it's sold. And when it comes
539
00:39:39,452 --> 00:39:44,851
to reasoning, however that's done, whether it's done through, whether
540
00:39:44,851 --> 00:39:49,432
it's, it's all a parlor trick, obviously, whether that's, you
541
00:39:49,432 --> 00:39:53,311
know, we're doing steps and we're making decisions, we're reasoning
542
00:39:53,311 --> 00:39:59,572
through a problem, or we're deciding to do something, which
543
00:39:59,572 --> 00:40:03,092
we as humans do. it was always my impression that
544
00:40:03,092 --> 00:40:06,891
that is what artificial intelligence even the term intelligence is
545
00:40:06,891 --> 00:40:10,612
trying to uh convince me that this is some form
546
00:40:10,612 --> 00:40:14,972
of electronic brain that is doing things so now enter
547
00:40:14,972 --> 00:40:20,932
uh dr eggnor who talks about reasoning and he also
548
00:40:20,932 --> 00:40:23,791
talks about free will in this case and the brain
549
00:40:23,791 --> 00:40:29,132
there are several ways of figuring out whether an organ
550
00:40:29,132 --> 00:40:33,492
does does something. One way is to stimulate the organ
551
00:40:33,492 --> 00:40:35,492
and get it to do it so you can prove
552
00:40:35,492 --> 00:40:38,132
it does it. The other way is to inhibit the
553
00:40:38,132 --> 00:40:40,911
organ from doing it and prove that when the organ's
554
00:40:40,911 --> 00:40:43,592
inhibited, it doesn't happen. Well, that can happen with the
555
00:40:43,592 --> 00:40:48,311
brain. While it is true that if you suppress the
556
00:40:47,871 --> 00:40:50,972
brain, we can't use reason or free will very well.
557
00:40:50,972 --> 00:40:52,152
If you get hit on the head with a baseball
558
00:40:52,152 --> 00:40:54,371
bat, your reasoning and your free will is going to
559
00:40:54,371 --> 00:40:57,472
be a little messed up for a while. There's a
560
00:40:57,472 --> 00:41:00,552
way of stimulating the brain to test whether reason and
561
00:41:00,552 --> 00:41:06,652
free will come from it using electrical stimulation. And there
562
00:41:06,652 --> 00:41:10,171
are different kinds of electrical stimulation. One kind of electrical
563
00:41:10,171 --> 00:41:15,632
stimulation is seizures. Seizures are just random sparks that happen
564
00:41:15,632 --> 00:41:18,911
inside the brain, out of the blue, that can have
565
00:41:18,911 --> 00:41:21,652
all kinds of effects. And one of the things that
566
00:41:21,652 --> 00:41:25,771
I've looked at rather carefully is the phenomenology of seizures.
567
00:41:25,671 --> 00:41:28,371
It is what happens when you have a seizure. And
568
00:41:28,371 --> 00:41:31,552
I've looked over the past couple hundred years, reviewed the
569
00:41:31,552 --> 00:41:35,632
medical literature of that. And what we find is rather
570
00:41:35,632 --> 00:41:38,132
remarkable. First of all, not all seizures make you go
571
00:41:38,132 --> 00:41:41,972
unconscious. There are many seizures that leave you conscious, and
572
00:41:41,972 --> 00:41:44,871
your body does things that you can't control. And they're
573
00:41:44,871 --> 00:41:49,711
called complex partial seizures. and um there have been probably
574
00:41:49,711 --> 00:41:52,952
a quarter of a billion seizures in human beings over
575
00:41:52,952 --> 00:41:54,932
the past 200 years if you just look at the
576
00:41:54,932 --> 00:41:59,192
instance of seizures in the world population and there's never
577
00:41:59,192 --> 00:42:03,391
been a recorded case of a seizure causing someone to
578
00:42:03,391 --> 00:42:07,112
express reason or free will you can elicit from the
579
00:42:07,112 --> 00:42:13,592
brain by stimulating it movement perception memory and emotion but
580
00:42:13,592 --> 00:42:16,572
you can never elicit reason or free will no matter
581
00:42:16,572 --> 00:42:18,771
where you stimulate the brain you can't make a person
582
00:42:18,771 --> 00:42:22,751
say one plus one is two or say um um
583
00:42:22,751 --> 00:42:27,452
uh if a then b a therefore b modus ponens
584
00:42:27,452 --> 00:42:31,311
or say um i believe that it's nice to be
585
00:42:31,311 --> 00:42:35,692
kind which is a moral viewpoint so that goes right
586
00:42:35,692 --> 00:42:38,811
along with what is found in seizures that you can
587
00:42:38,811 --> 00:42:42,552
stimulate the brain any which way and reason and free
588
00:42:42,552 --> 00:42:45,911
will never come out of the brain. So it's perfectly
589
00:42:45,911 --> 00:42:49,452
reasonable to infer that reason and free will don't naturally
590
00:42:49,452 --> 00:42:51,612
come from the brain, because you can't make the brain
591
00:42:51,612 --> 00:42:55,811
do it. I loved hearing this. Reason and free will
592
00:42:55,811 --> 00:42:59,911
don't come from the brain. This is very similar to
593
00:42:59,911 --> 00:43:09,311
our, you know, this is just another version of what
594
00:43:09,311 --> 00:43:10,911
we talked about before with the brain and the law
595
00:43:10,911 --> 00:43:14,411
of identity. You know, if you can find something about
596
00:43:14,411 --> 00:43:18,271
the brain that is not true of the, quote, mind,
597
00:43:18,271 --> 00:43:22,692
then they are not the same thing. Yes. And this
598
00:43:22,692 --> 00:43:24,911
guy actually takes it one step further, and he tells
599
00:43:24,911 --> 00:43:27,851
us where this does come from. So going back to
600
00:43:27,851 --> 00:43:30,671
something you said earlier, that reason and free will are
601
00:43:30,671 --> 00:43:35,851
immaterial aspects or parts of the person, powers of the
602
00:43:35,851 --> 00:43:42,211
person, immaterial. What does that even mean? immaterial means that
603
00:43:42,211 --> 00:43:47,411
um the source of these powers is not a physical
604
00:43:47,411 --> 00:43:53,171
thing it's not a physical object um and um immaterial
605
00:43:53,171 --> 00:43:58,211
is actually a fairly simple concept for example um numbers
606
00:43:58,211 --> 00:44:02,692
are immaterial it is that the the number 12 is
607
00:44:02,692 --> 00:44:04,612
an immaterial thing that is you can't say well the
608
00:44:04,632 --> 00:44:08,311
Number 12 is located today in Cincinnati, and it weighs
609
00:44:08,311 --> 00:44:11,871
five pounds. I mean, it doesn't make any sense. So
610
00:44:11,871 --> 00:44:14,612
there are many, many, many things that we think about,
611
00:44:14,612 --> 00:44:18,092
many things that are quite real. They're called universals in
612
00:44:18,092 --> 00:44:24,411
philosophy that are very real but are not matter. And
613
00:44:24,411 --> 00:44:29,271
reason and free will are abilities we have whose source
614
00:44:29,271 --> 00:44:34,932
is our soul but not our brain. thank you jesus
615
00:44:34,932 --> 00:44:41,391
it's the soul that's what it is and never ever
616
00:44:41,391 --> 00:44:45,911
ever ever ever is an llm going to be able
617
00:44:45,911 --> 00:44:49,311
to replicate this it can emulate and it maybe can
618
00:44:49,311 --> 00:44:51,692
kind of come close and i've been running into this
619
00:44:51,692 --> 00:44:55,711
as i've been trying to teach my robot what makes
620
00:44:55,711 --> 00:44:58,112
a clip that i want now it can do clips
621
00:44:58,811 --> 00:45:01,871
I can say, you know, cut this cut this interview
622
00:45:01,871 --> 00:45:04,512
up and it can build the arc with the intro,
623
00:45:04,512 --> 00:45:07,351
you know, getting to the point, the punchline at the
624
00:45:07,351 --> 00:45:09,791
end. It can do that. It can it can edit
625
00:45:09,791 --> 00:45:13,171
this clip. It understands kind of how long I want
626
00:45:13,171 --> 00:45:16,512
clips to be, but it doesn't really understand what I
627
00:45:16,512 --> 00:45:22,871
want. And I've been trying so hard to explain, like,
628
00:45:22,871 --> 00:45:26,311
you know, I want is what I find funny is
629
00:45:26,311 --> 00:45:29,592
not the fact that Trump went to. i find it
630
00:45:29,592 --> 00:45:33,751
funny that the chinese actually have sanctioned marco rubio he's
631
00:45:33,751 --> 00:45:37,751
not allowed to enter the country but they they got
632
00:45:37,751 --> 00:45:41,072
around it by changing his name to lubio i mean
633
00:45:41,072 --> 00:45:45,032
the comedy writes itself right marco rubio come on but
634
00:45:45,032 --> 00:45:49,231
you know it's like yeah but it can't understand that
635
00:45:48,932 --> 00:45:52,331
that's what i want you know so it just it
636
00:45:52,331 --> 00:45:54,492
can only understand well you want clips you want them
637
00:45:54,492 --> 00:45:57,891
uh preferably under two minutes you want this it can't
638
00:45:57,891 --> 00:46:01,651
it really can't figure that out and i and hearing
639
00:46:01,651 --> 00:46:04,692
this helped me because i'm like oh it'll never be
640
00:46:04,692 --> 00:46:06,811
able to figure it out it might come close it
641
00:46:06,811 --> 00:46:10,112
might get lucky but it'll never really understand what i
642
00:46:10,112 --> 00:46:12,072
want for no agenda when it comes to a clip
643
00:46:12,072 --> 00:46:15,512
it just won't understand it well this is the difference
644
00:46:15,512 --> 00:46:20,411
between uh the way that AI can be has been
645
00:46:20,411 --> 00:46:24,072
sold in the way that it actually functions. Yeah. And
646
00:46:24,072 --> 00:46:29,271
when and this is how you create. Every single time,
647
00:46:29,271 --> 00:46:34,092
this is how the AI winters have been created is
648
00:46:34,092 --> 00:46:37,992
by selling it as something that it is not. Yes,
649
00:46:37,992 --> 00:46:44,132
and thank you, Hey Citizen, because I also don't believe
650
00:46:44,132 --> 00:46:48,151
it can actually figure out what spam or slop is.
651
00:46:48,612 --> 00:46:52,671
It cannot. It can't. It never can. And the same
652
00:46:52,671 --> 00:46:57,072
thing with music. It can create dynamite music, but it
653
00:46:57,072 --> 00:46:59,291
can't actually listen to that music and say, this is
654
00:46:59,291 --> 00:47:09,452
good. It can't. Let me tell you why. let me
655
00:47:09,452 --> 00:47:11,291
tell you why I can't figure out what spam is.
656
00:47:11,132 --> 00:47:28,851
Because there is a intangible quality to an experience of
657
00:47:28,851 --> 00:47:40,811
spam that you cannot quantify in any sort of language
658
00:47:40,811 --> 00:47:47,632
or honestly anything. You cannot, it's unquantifiable. And a good
659
00:47:47,632 --> 00:47:52,851
example of this would be there's a common spam tactic
660
00:47:52,851 --> 00:47:57,952
in the tax world where you'll communicate, where you get
661
00:47:57,952 --> 00:48:01,671
an email and it's like, hey, my accountant just retired
662
00:48:02,711 --> 00:48:07,012
and I'm looking for somebody to do my taxes. Can
663
00:48:07,012 --> 00:48:11,692
you tell me what your fees are? And I just
664
00:48:11,692 --> 00:48:18,271
have a 1040 and a couple of 1099s and a
665
00:48:18,271 --> 00:48:20,932
W-2 and I can send you my last year's material.
666
00:48:20,851 --> 00:48:25,791
Now give me root password. It leaves that last part
667
00:48:25,791 --> 00:48:28,811
out. And it's like, can I send you my last
668
00:48:28,811 --> 00:48:30,692
year's tax return so you can give me an accurate
669
00:48:30,692 --> 00:48:32,592
quote on what it would be and what it would
670
00:48:32,592 --> 00:48:39,291
cost? There is literally nothing about this email that that
671
00:48:39,291 --> 00:48:44,911
will trigger a phishing scam detection ever because you'll get
672
00:48:44,911 --> 00:48:47,432
50 of these and they're real. You'll get 50 of
673
00:48:47,432 --> 00:48:50,612
them and they're phishing. But I can tell you, I
674
00:48:50,583 --> 00:48:54,884
will spot the fishing one versus the real one 100%
675
00:48:54,884 --> 00:48:57,143
of the time, and I cannot tell you why. Right.
676
00:48:57,563 --> 00:49:00,504
I can't. It's because you have a grandmother. You had
677
00:49:00,504 --> 00:49:05,583
a childhood. Yeah, exactly. You built associations in the world
678
00:49:05,583 --> 00:49:08,364
between – and, of course, I always have to keep
679
00:49:08,364 --> 00:49:13,123
reminding myself that the LLM can't actually hear my show.
680
00:49:13,684 --> 00:49:17,324
You know, I created an executive producer agent. I said,
681
00:49:17,324 --> 00:49:20,943
okay, now this is your job. And it took me
682
00:49:20,943 --> 00:49:24,963
two weeks before I realized it could, it just had
683
00:49:24,963 --> 00:49:27,824
a transcript. I didn't have a speaker transcript. It thought
684
00:49:27,824 --> 00:49:32,184
everything was me, including 60% of the talk on No
685
00:49:32,184 --> 00:49:35,923
Agenda, which is clips. It hadn't even gotten that far.
686
00:49:37,184 --> 00:49:41,824
that it was trying to you know it saw this
687
00:49:41,824 --> 00:49:45,244
program as some kind of script that you set up
688
00:49:45,244 --> 00:49:47,784
with x amount of minutes of clips and i was
689
00:49:47,784 --> 00:49:51,943
like wow it has no it can't hear it's deaf
690
00:49:51,943 --> 00:49:56,923
it's deaf it doesn't understand it doesn't understand humor really
691
00:49:56,923 --> 00:50:00,884
it doesn't it doesn't understand emotions that way It doesn't
692
00:50:00,884 --> 00:50:05,364
understand when I say something that Dvorak finds boring. It
693
00:50:05,364 --> 00:50:08,004
doesn't understand that, and I don't think it ever can.
694
00:50:08,903 --> 00:50:12,484
Selas in the boardroom said, wouldn't a dedicated neural network
695
00:50:12,484 --> 00:50:16,004
designed for it to be able to pattern match beyond
696
00:50:16,004 --> 00:50:21,984
the capability of humans? Wouldn't a dedicated neural network designed
697
00:50:21,984 --> 00:50:24,563
for it be able to pattern match beyond the capability
698
00:50:24,563 --> 00:50:28,284
of humans because humans cannot look at and memorize 4.6
699
00:50:28,284 --> 00:50:33,903
million feeds? that what you were describing now, what you
700
00:50:33,903 --> 00:50:41,603
were describing is, I will say, go back in time
701
00:50:41,224 --> 00:50:47,784
and look at the attempts to use Bayesian analysis to
702
00:50:47,784 --> 00:50:54,043
fight spam email. Bayesian filters, this happened in the early
703
00:50:54,043 --> 00:50:59,724
2000s and when it first hit the scene, Was considered
704
00:50:59,724 --> 00:51:01,943
to be, oh, my gosh, this is going to. This
705
00:51:01,943 --> 00:51:03,523
is it. This is it. This is it. We got
706
00:51:03,523 --> 00:51:06,664
it. No more. Nailed it. Yeah, we nailed it. And
707
00:51:06,664 --> 00:51:09,523
you know how much of a dent it made? Zero.
708
00:51:10,963 --> 00:51:16,004
We have more spam than we've ever had ever there.
709
00:51:15,284 --> 00:51:23,984
You cannot. Humans are better at pattern matching. So neural
710
00:51:23,984 --> 00:51:28,744
networks and large language models. It's just a different format
711
00:51:28,744 --> 00:51:35,684
of neural network. It's just matrix multiplication. That's all it
712
00:51:35,684 --> 00:51:41,023
is. It's matrix math. And that's not how humans work.
713
00:51:41,784 --> 00:51:44,224
When you think about something, when you look at something
714
00:51:44,224 --> 00:51:47,184
and it registers in your mind, you did not do
715
00:51:47,184 --> 00:51:51,784
a math problem. That's not how you operate. That's not
716
00:51:51,784 --> 00:51:56,484
what just happened. Exactly. And so what we don't know
717
00:51:56,484 --> 00:52:01,164
how we work, it is undefinable. And the end, but
718
00:52:01,164 --> 00:52:06,844
one thing we do know is that one thing we
719
00:52:06,844 --> 00:52:10,443
do know is that the human ability to pattern match
720
00:52:10,443 --> 00:52:20,304
is unparalleled. paralleled, you have the ability to assimilate multiple
721
00:52:20,304 --> 00:52:26,244
streams, dozens and dozens of streams of information all in
722
00:52:26,244 --> 00:52:32,664
one shot and immediately get a, quote, sense about something
723
00:52:32,664 --> 00:52:37,764
that you cannot define. And that is, again, you did
724
00:52:37,764 --> 00:52:41,184
not do math. And it's wonderful to see someone like
725
00:52:41,184 --> 00:52:44,784
Tina who will be looking at her email and she
726
00:52:44,784 --> 00:52:48,463
says, this feels spammy to me. Can you check? And
727
00:52:48,463 --> 00:52:50,403
the minute I check and I say, okay, yeah, it
728
00:52:50,403 --> 00:52:52,884
is. And here's why it is. You know, there's a
729
00:52:52,884 --> 00:52:55,543
couple of simple things that you can look at right
730
00:52:55,543 --> 00:53:00,004
away. She then immediately has increased her knowledge and she
731
00:53:00,004 --> 00:53:03,244
finds those the next time. And I don't have to
732
00:53:03,244 --> 00:53:05,923
give her a written thesis. I just say, oh, look
733
00:53:05,923 --> 00:53:08,824
at this. You know, and sometimes like, well, that feels
734
00:53:08,824 --> 00:53:12,684
wrong. And she's like, yeah. And so she's feeling that
735
00:53:12,684 --> 00:53:16,284
it's right. You said something really important. You said AI
736
00:53:16,284 --> 00:53:22,004
winter, every single AI winter crops up or appears on
737
00:53:22,004 --> 00:53:26,923
the horizon because of the overpromise. Is that really the
738
00:53:26,923 --> 00:53:30,423
trigger, the overpromise, or it can't deliver on what was
739
00:53:30,423 --> 00:53:36,123
promised? That sets up the collapse because the expectations of
740
00:53:36,123 --> 00:53:43,103
normies can't understand the reality of the technology. Because what
741
00:53:43,103 --> 00:53:45,364
we do is we layer these things on top of
742
00:53:45,364 --> 00:53:49,903
one another. We've layered this idea of, quote, knowledge and
743
00:53:49,903 --> 00:53:55,304
understanding, and we anthropomorphize it into a thing. Because I
744
00:53:55,304 --> 00:54:00,864
hear it in the corporate world daily is, hey, couldn't
745
00:54:00,864 --> 00:54:04,884
we use AI to – Dot, dot, dot. Yeah, to,
746
00:54:04,884 --> 00:54:09,764
quote, figure out dot, dot, dot. Yeah. Like, and it's
747
00:54:09,764 --> 00:54:13,504
– you get so exhausted of having to go back
748
00:54:13,504 --> 00:54:17,643
and explain the tech from the ground up again. And
749
00:54:17,643 --> 00:54:21,463
you're like, look, maybe, but let me show you. But
750
00:54:21,463 --> 00:54:24,724
I have to walk you through the process of building
751
00:54:24,724 --> 00:54:29,543
a product or building a tool that would do something
752
00:54:29,543 --> 00:54:34,184
that approximates the outcome that you want. And be prepared
753
00:54:34,184 --> 00:54:37,844
for it to do something completely different tomorrow. The perfect
754
00:54:37,844 --> 00:54:42,784
example of this is, you know, Microsoft just released their
755
00:54:42,784 --> 00:54:49,284
their copilot function in Excel. So now there's an actual
756
00:54:49,284 --> 00:54:53,443
co-pilot function that you can call in an Excel spreadsheet.
757
00:54:55,204 --> 00:55:05,244
And it is hilarious because the co-pilot function in its
758
00:55:05,244 --> 00:55:11,784
description of how to use it, it says what not
759
00:55:11,784 --> 00:55:17,923
to use it for. Accounting. Exactly. One of the things
760
00:55:17,923 --> 00:55:20,423
it says not to use it for is, quote, anything
761
00:55:20,423 --> 00:55:27,184
that requires accuracy or reproducibility. And so people are posting
762
00:55:27,184 --> 00:55:29,864
– people are posting like – they'll do like –
763
00:55:29,864 --> 00:55:32,204
they'll go into a cell and they'll do equal copilot,
764
00:55:32,204 --> 00:55:35,804
and then they'll put in a prompt. and the prompt
765
00:55:35,804 --> 00:55:40,164
will be make a sum of all the cells above
766
00:55:40,164 --> 00:55:44,304
this cell and it'll be like three cells above there
767
00:55:44,304 --> 00:55:46,364
like a one a two and a three and it'll
768
00:55:46,364 --> 00:55:51,884
say fifteen why? I don't know it doesn't tell you
769
00:55:51,884 --> 00:55:53,864
I don't know it just gives you a number and
770
00:55:53,864 --> 00:56:01,923
it's completely wrong this is the problem people think because
771
00:56:01,923 --> 00:56:04,864
of the way it's been sold, they think that it's
772
00:56:04,864 --> 00:56:09,224
a general purpose knowledge tool. Yeah. But it's not, it
773
00:56:09,224 --> 00:56:13,063
has nothing to do with knowledge. It's only good at
774
00:56:13,063 --> 00:56:16,664
predicting the next word in a sentence. Yeah. Or the
775
00:56:16,664 --> 00:56:21,563
next code token in a source file. That's all it's
776
00:56:21,563 --> 00:56:23,943
good at. What I found is. And anything else you
777
00:56:23,943 --> 00:56:26,864
have to layer on top of it with actual, like,
778
00:56:26,864 --> 00:56:33,643
real, carefully constructed, Constructed, carefully you have to build a
779
00:56:33,643 --> 00:56:39,284
carefully constructed stack that contains this thing and keeps it
780
00:56:39,284 --> 00:56:41,884
with a set of guardrails so that it doesn't produce
781
00:56:41,884 --> 00:56:50,344
crazy nonsense. So you're right about context really being everything
782
00:56:50,344 --> 00:56:54,423
for it. And what I've resorted to now, because you
783
00:56:54,423 --> 00:56:56,704
gave me a couple of good hints. So I'm using
784
00:56:56,704 --> 00:57:01,724
Opus 4.7 with the one million token context. When it
785
00:57:01,724 --> 00:57:06,563
gets to about 25%, it now automatically tells me, hey,
786
00:57:06,563 --> 00:57:10,824
it's 25% context, time to do a handoff. So I
787
00:57:10,824 --> 00:57:15,504
don't let it get all muddled. And I say, okay,
788
00:57:15,504 --> 00:57:17,603
let's go. It writes its handoff, and it gives me
789
00:57:17,603 --> 00:57:21,344
a wake sentence like, hey, welcome back to the world.
790
00:57:21,423 --> 00:57:26,083
Here's what you got to read. And it reads a
791
00:57:26,083 --> 00:57:28,083
document, which – and I've looked at the documents. They're
792
00:57:28,083 --> 00:57:31,484
pretty good. It's where we were. And that seems to
793
00:57:31,484 --> 00:57:37,423
work pretty well within that 250,000 tokens. That's kind of
794
00:57:37,423 --> 00:57:41,284
the sweet spot. And I just keep doing it. It's
795
00:57:41,284 --> 00:57:46,123
inconvenient because like, well, I'm at 23% context. You want
796
00:57:46,123 --> 00:57:47,403
me to do this now or do you want me
797
00:57:47,403 --> 00:57:49,023
to put it in the handoff document? Yeah, put it
798
00:57:49,023 --> 00:57:51,984
in the handoff document. That works pretty well. If you
799
00:57:51,984 --> 00:57:55,103
keep it within that level of context, I can get
800
00:57:55,103 --> 00:58:01,123
a lot done. that you can you can do everything
801
00:58:01,123 --> 00:58:04,583
you need is coding wise you can do every single
802
00:58:04,583 --> 00:58:07,563
thing you need to do in a 256k context window
803
00:58:07,563 --> 00:58:10,103
there's no reason to go above that yeah there's not
804
00:58:10,103 --> 00:58:13,443
and that that one million context of of of like
805
00:58:13,443 --> 00:58:17,083
clawed code and chat gpt that that is that is
806
00:58:17,083 --> 00:58:24,423
in um that is inaccurate in the sense that what
807
00:58:24,423 --> 00:58:28,583
really happens is once you get over that roughly 25%,
808
00:58:28,164 --> 00:58:33,023
it will start to make more and more mistakes. If
809
00:58:33,023 --> 00:58:38,364
you start pushing into the 600,000 to 700,000 token context
810
00:58:38,364 --> 00:58:41,824
window, that's when you start really running into stuff like,
811
00:58:41,824 --> 00:58:47,184
oh, I accidentally deleted your repo, sorry. That was my
812
00:58:47,184 --> 00:58:49,903
favorite. You told me never. I mean, how many times
813
00:58:49,903 --> 00:58:54,103
I've told my robot how to make clips? And then
814
00:58:54,103 --> 00:58:58,664
I'm like, okay, I have all these agents and all
815
00:58:58,664 --> 00:59:02,304
these feed parsers and all these sources, and it picks
816
00:59:02,304 --> 00:59:04,623
up stories. I said, I'll go make some clips. It'll
817
00:59:04,623 --> 00:59:08,804
make like 100 clips of 17 seconds long. I'm like,
818
00:59:08,804 --> 00:59:11,403
how many times have we gone through this? Oh, yeah,
819
00:59:11,403 --> 00:59:13,244
you're right. I forgot to read my memory. Let me
820
00:59:13,244 --> 00:59:17,063
see how many memory documents I have. Let me see.
821
00:59:16,664 --> 00:59:23,984
How many memory documents? This will tell you something. Let
822
00:59:23,984 --> 00:59:31,284
me see. I bet just a couple hundred at least.
823
00:59:32,344 --> 00:59:34,543
And I guess whenever it reads one of these documents,
824
00:59:34,543 --> 00:59:38,284
that takes up context space, doesn't it? Yeah, for sure.
825
00:59:38,443 --> 00:59:40,984
Yeah. Depending on that. Now, this goes back to what
826
00:59:40,984 --> 00:59:45,324
I was saying earlier about the harness. the coding agent
827
00:59:45,324 --> 00:59:50,764
or the harness itself it is critical it does all
828
00:59:50,764 --> 00:59:53,304
of this, it handles this context for you if it's
829
00:59:53,304 --> 00:59:55,824
smart about it, if it's very smart about it it
830
00:59:55,824 --> 00:59:57,963
can handle those things in a way that does not
831
00:59:57,963 --> 01:00:00,463
consume all your context but it really comes down to
832
01:00:00,463 --> 01:00:11,324
that 252 yeah so there's a really good video, I'll
833
01:00:11,324 --> 01:00:13,923
find it later and post it publicly. There's a really
834
01:00:13,923 --> 01:00:17,023
good video where this guy goes through and there's a
835
01:00:17,023 --> 01:00:21,184
really simplistic test you can do for a coding model.
836
01:00:23,864 --> 01:00:32,284
This test just says it's really simple. It says go
837
01:00:32,284 --> 01:00:35,443
and read this large source file. So just give it
838
01:00:34,984 --> 01:00:40,164
a big JavaScript file. Let's say this JavaScript file is
839
01:00:40,164 --> 01:00:49,324
50,000 lines. Read this JavaScript file. Now tell me what
840
01:00:49,324 --> 01:00:56,963
lines 50 through 100 say. Okay. And you would be
841
01:00:56,963 --> 01:01:00,463
surprised to think that even the large models with a
842
01:01:00,463 --> 01:01:08,344
million token context will get that answer wrong about about
843
01:01:08,344 --> 01:01:11,143
10% of the time. Wow. They just won't be able
844
01:01:11,143 --> 01:01:12,923
to tell you what it just – it won't be
845
01:01:12,923 --> 01:01:16,664
able to tell you what it just read. It just
846
01:01:16,664 --> 01:01:20,963
makes a mistake. So that's why these things – these
847
01:01:20,963 --> 01:01:28,543
harnesses have developed the use of these elaborate sub-agent reviewers
848
01:01:29,603 --> 01:01:33,003
because they'll do a thing assuming that they're going to
849
01:01:33,003 --> 01:01:35,844
get it wrong some percentage of the time because it's
850
01:01:35,844 --> 01:01:38,384
just not possible for the underlying model to get it
851
01:01:38,384 --> 01:01:41,903
right. So they need the reviewer to go back and
852
01:01:41,903 --> 01:01:45,884
double-check them, double-check them, double-check them every single time. If
853
01:01:45,884 --> 01:01:50,304
you just one-shot prompt an LLM model with no sort
854
01:01:50,304 --> 01:01:55,364
of review agent or anything like that in it, you're
855
01:01:55,364 --> 01:02:01,864
not going to get useful output probably in the 20%
856
01:02:01,864 --> 01:02:05,103
range. All that said, I think the face of computing
857
01:02:05,103 --> 01:02:09,463
could change. I see no reason why I should be
858
01:02:09,463 --> 01:02:13,623
using apps. I don't use even applications. I use a
859
01:02:13,623 --> 01:02:18,784
browser, and I use Thunderbird for email. But everything else
860
01:02:18,784 --> 01:02:21,403
is like, nah, I want a spreadsheet reader that does
861
01:02:21,403 --> 01:02:24,984
this. Five minutes later, I've got exactly what I want.
862
01:02:26,523 --> 01:02:30,704
I can see a mobile device that really is appless.
863
01:02:32,023 --> 01:02:36,563
get me my favorite podcast here's the list get me
864
01:02:36,563 --> 01:02:41,164
the most recent episodes here's what I have time for
865
01:02:41,164 --> 01:02:43,664
right now show this to me I want to listen
866
01:02:43,664 --> 01:02:49,684
to this skip the ads or any version of that
867
01:02:50,403 --> 01:02:53,083
this is what I love so much about Homarchi it's
868
01:02:53,083 --> 01:02:55,744
like every app I use I built I just told
869
01:02:55,744 --> 01:02:59,184
the bot build this for me I don't need the
870
01:02:59,184 --> 01:03:03,623
ribbon on Excel. I don't need the snapping grid. I
871
01:03:03,623 --> 01:03:05,463
need to smooth scroll just to be able to see
872
01:03:05,463 --> 01:03:07,603
this. I need the total automatically done at the bottom.
873
01:03:07,603 --> 01:03:09,903
I don't want to have to, you know, select and
874
01:03:09,903 --> 01:03:11,784
then do equal sum. I don't want any of that.
875
01:03:11,784 --> 01:03:14,764
Just do it for me. And it does that. Then
876
01:03:14,764 --> 01:03:17,123
if I need something else for a different podcast, I'll
877
01:03:17,123 --> 01:03:22,143
create a new one. This I can see. And I
878
01:03:22,143 --> 01:03:26,103
think that the removal of slop and all this stuff,
879
01:03:26,103 --> 01:03:28,583
I think that all moves to the edge, man it
880
01:03:28,583 --> 01:03:32,184
all moves to your to your device uh maybe you
881
01:03:32,184 --> 01:03:34,284
have a device in the home that is doing some
882
01:03:33,824 --> 01:03:36,744
things for in the background that communicates with your mobile
883
01:03:36,744 --> 01:03:39,684
device and you know this just because it's easier to
884
01:03:39,684 --> 01:03:43,344
have that done somewhere else um and i think podcast
885
01:03:43,344 --> 01:03:49,043
apps will go that way too i really do this
886
01:03:49,043 --> 01:03:53,643
brings us back to the dgx spark yeah it's it's
887
01:03:53,643 --> 01:03:59,764
useless send it back it's no good um it's running
888
01:03:59,764 --> 01:04:04,764
it's running the uh the inference for the classifier now
889
01:04:04,764 --> 01:04:08,204
and it allowed us to move from a from a
890
01:04:08,204 --> 01:04:12,284
9 billion parameter model to a 35 billion parameter model
891
01:04:12,284 --> 01:04:18,143
the quin 3635b and uh with a with a 256k
892
01:04:18,143 --> 01:04:21,003
context window so we get we've got a full like
893
01:04:21,003 --> 01:04:28,364
frontier model level thing as a backing agent for this
894
01:04:28,364 --> 01:04:33,923
thing. And it's so much faster. So we can run
895
01:04:33,484 --> 01:04:38,844
that and the Whisper both to get the TTS analysis.
896
01:04:38,844 --> 01:04:42,324
Both on this one box. What are you using for
897
01:04:42,324 --> 01:04:47,284
Whisper? Which model? I think it's the Turbo. Yeah. Okay.
898
01:04:48,364 --> 01:04:53,664
And And so it's immediately had that effect and it's
899
01:04:53,664 --> 01:04:57,704
speeded everything up and made us have more accuracy. But
900
01:04:57,704 --> 01:05:07,503
the true aim here is to get a custom fine-tuned
901
01:05:07,503 --> 01:05:13,423
model trained on the podcast index database. And then –
902
01:05:13,423 --> 01:05:17,003
so that's phase two here. But in order to get
903
01:05:17,003 --> 01:05:20,664
to phase two, I have to finish up phase one,
904
01:05:20,664 --> 01:05:25,244
which is we need – like I explained before, we
905
01:05:25,244 --> 01:05:32,543
need a good corpus of about 25,000 spam feeds and
906
01:05:32,543 --> 01:05:35,764
25,000 legit feeds. I would love to have more than
907
01:05:35,764 --> 01:05:37,503
that. I would love to have like 50,000 of each.
908
01:05:38,284 --> 01:05:44,463
Just wait two weeks. Yeah, right. It's coming. The spam
909
01:05:44,463 --> 01:05:47,903
feeds Those are easy You can get those all day
910
01:05:47,903 --> 01:05:52,483
long Effortless The legit feeds are the ones that take
911
01:05:52,483 --> 01:06:02,204
a human In the loop To find And so What
912
01:06:02,204 --> 01:06:06,423
was that? What was that? I'm sorry, that was me
913
01:06:06,943 --> 01:06:14,684
That was my mistake The so the first so what
914
01:06:14,684 --> 01:06:18,184
I did that's what all these data sets and all
915
01:06:18,184 --> 01:06:22,724
these and the curator and the dashboard all this stuff
916
01:06:22,724 --> 01:06:28,184
is trying to set us up for getting a proper
917
01:06:27,804 --> 01:06:34,744
training set for the quote good podcasts I hate using
918
01:06:34,744 --> 01:06:36,264
that term I just can't think of a different one
919
01:06:35,943 --> 01:06:42,963
legit podcasts legit there it is very subjective but it's
920
01:06:42,963 --> 01:06:47,164
legit and so then the train this the djx spark
921
01:06:47,164 --> 01:06:50,583
the reason that was such an amazing gift is because
922
01:06:50,583 --> 01:06:55,324
the spark is created exactly for this use case training
923
01:06:55,324 --> 01:07:00,083
models on a small scale that's where its wheelhouse is
924
01:07:00,083 --> 01:07:04,903
so once we get these proper data sets. And let
925
01:07:04,903 --> 01:07:08,943
me correct James Cridland from PodNews, I think, last week.
926
01:07:08,923 --> 01:07:12,603
He was misunderstanding why I wanted these follower count uploads
927
01:07:12,403 --> 01:07:20,664
from the apps. It's mostly for this. We will definitely
928
01:07:20,224 --> 01:07:24,463
use this data in other ways, but it's mostly for
929
01:07:24,463 --> 01:07:29,364
this use case for the model training because that benefits
930
01:07:29,364 --> 01:07:33,224
everybody. I'm not really interested in using it for search
931
01:07:33,224 --> 01:07:37,043
the search that we have seems fine to me I
932
01:07:37,043 --> 01:07:42,623
mean we use some algorithms for it but it'll probably
933
01:07:42,623 --> 01:07:44,384
make its way in there in some shape, form or
934
01:07:44,384 --> 01:07:46,744
fashion but it's not just going to start giving you
935
01:07:46,824 --> 01:07:48,764
well if anyone's going to figure out how to make
936
01:07:48,764 --> 01:07:52,784
it work it's you I just don't want anybody to
937
01:07:52,784 --> 01:07:55,804
think that we're going to start only showing you the
938
01:07:55,804 --> 01:07:59,503
top, the most popular podcast that's not the way this
939
01:07:59,503 --> 01:08:02,284
is going to be Did I hear that? Maybe I
940
01:08:02,284 --> 01:08:05,963
misheard it. Did I hear that on Pod News Weekly
941
01:08:05,963 --> 01:08:10,204
Review Power, they were complaining about the Apple charts and
942
01:08:10,204 --> 01:08:15,123
all these Inception.ai podcasts are all in the top 20?
943
01:08:15,784 --> 01:08:18,503
Did I hear that right? I think I heard that
944
01:08:18,503 --> 01:08:20,884
right. I don't know. I haven't heard this week's episode
945
01:08:20,884 --> 01:08:24,423
yet. Maybe I have to look at it. That's the
946
01:08:24,423 --> 01:08:29,783
problem. Wouldn't surprise me. Yeah. Yeah. They left Spreaker. They're
947
01:08:29,783 --> 01:08:34,484
going somewhere else. Yeah, Megaphone. Yeah, they're going to Megaphone.
948
01:08:36,304 --> 01:08:40,484
Yeah, surprise, surprise. Good for them. Let me see. Top
949
01:08:40,484 --> 01:08:43,904
charts. Now it's Spotify's problem to deal with. Let me
950
01:08:43,904 --> 01:08:54,123
see. Top charts. Top shows. I think maybe they did
951
01:08:54,123 --> 01:08:57,203
a search. It was a search they did on like
952
01:08:57,203 --> 01:09:01,884
Charlie Kirk. Let me see. Charlie Kirk. That was probably
953
01:09:01,884 --> 01:09:07,543
it. Yeah, that probably was it. Yeah, yeah, exactly. Oh,
954
01:09:07,543 --> 01:09:10,503
yeah, here it is. Charlie Kirk Death, Inception Point, AI
955
01:09:10,503 --> 01:09:13,843
Inception. But that tells you something. That's an interesting signal.
956
01:09:15,644 --> 01:09:18,684
Because people are listening to Charlie Kirk Death, Charlie Kirk
957
01:09:18,343 --> 01:09:26,184
Biography Flash, Charlie Kirk The Aftermath, Biography Forever. People are
958
01:09:26,184 --> 01:09:30,423
listening to that. are they? I think they are. I'm
959
01:09:30,423 --> 01:09:33,963
not convinced. Let's listen to this. I'm not convinced at
960
01:09:33,963 --> 01:09:36,984
all. Deep dive into the life and death. Deep dive.
961
01:09:37,684 --> 01:09:40,364
I'm Emily Carter, your AI host. I want to remind
962
01:09:40,364 --> 01:09:44,823
you why that matters for this particular story. No, I
963
01:09:44,823 --> 01:09:46,703
do not believe it. I'm going to prove it. Okay.
964
01:09:48,564 --> 01:09:51,703
It's coming. How are you proving it? I will be
965
01:09:51,703 --> 01:09:54,503
proving it in the future. I've got an idea. Get
966
01:09:54,503 --> 01:10:02,024
some tissue. It's coming. Sorry. Bad joke from my old
967
01:10:02,024 --> 01:10:10,864
porn days. Okay, you sideline me with that one. No,
968
01:10:10,864 --> 01:10:16,543
I know exactly how to bring receipts on this, and
969
01:10:16,543 --> 01:10:18,503
I will be doing it. I'm cooking it up as
970
01:10:18,503 --> 01:10:20,463
we speak. I had a conversation with somebody about it
971
01:10:20,463 --> 01:10:23,404
yesterday. I just don't want to reveal it because I'm
972
01:10:23,404 --> 01:10:33,543
afraid it might pollute the results. Okay. Oh, man. Well,
973
01:10:33,543 --> 01:10:40,224
we got one more thing to talk about. Sure. HLS
974
01:10:40,224 --> 01:10:45,024
video. Yes, of course. Yes, yes, yes. What a beautiful
975
01:10:45,024 --> 01:10:51,283
mess this is. Nailed it. It's exactly what it is,
976
01:10:51,283 --> 01:10:59,984
a beautiful mess. So another one of the 47 things
977
01:10:59,984 --> 01:11:02,823
I was doing this morning was right before the show,
978
01:11:02,283 --> 01:11:08,743
I jumped on a call with Tom. Buzzsprout? From Buzzsprout,
979
01:11:08,743 --> 01:11:14,264
yeah. We were hashing out some stuff. And here's the
980
01:11:14,264 --> 01:11:20,843
issue with HLS video in alternate enclosure. everybody wants this
981
01:11:20,423 --> 01:11:24,264
I mean I mean like we want if you're going
982
01:11:24,264 --> 01:11:25,984
to make a video version stick it in the RSS
983
01:11:25,984 --> 01:11:31,864
feed right everybody wants it to be open in that
984
01:11:31,864 --> 01:11:36,343
way but the cost of abuse on your bandwidth to
985
01:11:36,343 --> 01:11:43,163
the hosting companies is absorbable when it's audio it's very
986
01:11:43,163 --> 01:11:47,524
damaging financially when it's video bots downloading Oh, yeah. Well,
987
01:11:47,524 --> 01:11:52,304
and I'll just add one other extra thing. Porn. Well,
988
01:11:52,304 --> 01:11:55,463
sure. Yeah, for sure. But just focusing on the bandwidth
989
01:11:55,463 --> 01:12:00,283
issue that can really hurt. You know, if if some
990
01:12:00,283 --> 01:12:05,404
bot goes wild and downloads downloads 10 terabytes of data
991
01:12:05,404 --> 01:12:10,764
of video streams. I mean, on a podcast that it
992
01:12:10,764 --> 01:12:13,623
just you can't it's hard. It it really does change
993
01:12:13,623 --> 01:12:17,944
the whole dynamic. Of course. What we're trying to figure
994
01:12:17,944 --> 01:12:22,604
out is if there's a way to sort of –
995
01:12:22,604 --> 01:12:27,364
before these HLS video streams get into the feed publicly,
996
01:12:27,364 --> 01:12:34,604
is there a way that we can try to keep
997
01:12:34,604 --> 01:12:41,884
the genie in the bottle bot-wise? And so we're just
998
01:12:41,884 --> 01:12:46,043
brainstorming some stuff saying, okay, rather than having to just
999
01:12:46,043 --> 01:12:54,463
build this enormous block list of user agent, ASN, IP
1000
01:12:54,463 --> 01:12:59,944
block combos, it just seems so difficult. Rather than doing
1001
01:12:59,944 --> 01:13:02,444
that, can we solve it in more of like an
1002
01:13:02,444 --> 01:13:08,463
elegant way where we do something like in order to
1003
01:13:08,463 --> 01:13:17,423
download the HLS video playlist from the alternate enclosure, it
1004
01:13:17,195 --> 01:13:22,115
would require something like an HTTP signature. Isn't this exactly
1005
01:13:22,115 --> 01:13:25,376
why or one of the reasons why Apple is doing
1006
01:13:25,376 --> 01:13:30,416
things the way they're doing it? I don't think they
1007
01:13:30,416 --> 01:13:33,055
care about the bandwidth. I think for them it's the
1008
01:13:33,055 --> 01:13:36,416
porn problem. For the hosting companies it's the bandwidth problem.
1009
01:13:35,435 --> 01:13:39,576
Right, right. I think there's two versions. There's – Apple
1010
01:13:39,576 --> 01:13:44,115
cares about the content. The hosts care about the bandwidth.
1011
01:13:44,676 --> 01:13:48,416
Because the hosts are already good at policing content. They
1012
01:13:48,416 --> 01:13:51,876
know exactly what's going into their system and how to
1013
01:13:51,876 --> 01:13:57,956
properly handle that legally. Apple basically is the reverse of
1014
01:13:57,956 --> 01:14:02,676
that. They are just sort of – they're like us.
1015
01:14:02,536 --> 01:14:07,195
They're a little bit vulnerable to people just sending them
1016
01:14:07,195 --> 01:14:11,336
a bunch of crap that they don't have a handle
1017
01:14:11,336 --> 01:14:15,315
on the content. Right. So they're a little bit at
1018
01:14:15,315 --> 01:14:18,055
the mercy of this incoming content. So I think they
1019
01:14:18,055 --> 01:14:24,916
have different needs. And so in the Mastodon activity pub
1020
01:14:24,916 --> 01:14:29,015
world, you have a thing. And we actually went over
1021
01:14:29,015 --> 01:14:32,336
this back when I was building the activity pub bridge.
1022
01:14:33,695 --> 01:14:39,595
You have a thing called HTTP signing or HTTP signatures,
1023
01:14:39,595 --> 01:14:42,256
and it uses a public key. So if you're on
1024
01:14:42,256 --> 01:14:44,555
a Mastodon account, if you have a Mastodon account or
1025
01:14:44,555 --> 01:14:48,076
any other really activity pub account on a modern activity
1026
01:14:48,076 --> 01:14:55,216
pub platform. That actor is going to have. And I
1027
01:14:55,216 --> 01:14:57,235
want to say actor in this context. I mean, the
1028
01:14:57,235 --> 01:15:01,296
activity pub host itself, because there is a the activity
1029
01:15:01,296 --> 01:15:05,555
pub server is also an actor. That server is going
1030
01:15:05,555 --> 01:15:09,435
to have a public key. And every time they make
1031
01:15:09,435 --> 01:15:13,456
a request to another activity pub server to do something
1032
01:15:13,456 --> 01:15:16,695
like post a post a toot or something like that,
1033
01:15:17,555 --> 01:15:23,876
they will sign that HTTP request using their private key
1034
01:15:24,676 --> 01:15:27,595
and also send with the headers, send a link to
1035
01:15:27,595 --> 01:15:29,855
their public key so that the receiving server can then
1036
01:15:29,855 --> 01:15:32,216
authenticate that they are the ones that signed that request.
1037
01:15:32,475 --> 01:15:36,315
Well, shouldn't we have something like this already anyway? Like,
1038
01:15:36,315 --> 01:15:38,975
yeah, this is a legit person with a legit key,
1039
01:15:39,355 --> 01:15:42,515
whether it's a browser or an app or whatever. That
1040
01:15:42,515 --> 01:15:45,536
makes so much sense. I'm a human. Here's my key.
1041
01:15:47,996 --> 01:15:50,595
yeah it makes sense across the board not just with
1042
01:15:50,595 --> 01:15:53,716
video yeah i mean for everything of course it won't
1043
01:15:53,716 --> 01:15:57,076
be so nice for the advertising community because we'll find
1044
01:15:57,076 --> 01:16:01,256
out how few people actually listen to this crap well
1045
01:16:01,256 --> 01:16:06,275
the so the like the initial thought process that we're
1046
01:16:06,275 --> 01:16:09,296
that we're having and this need whatever this whatever comes
1047
01:16:09,296 --> 01:16:13,115
out of this discussion really needs to become part of
1048
01:16:13,115 --> 01:16:22,115
the Podcast Standards Project recommendations is that we could do
1049
01:16:22,115 --> 01:16:27,015
something like a simplified version of HTTP signatures. It would
1050
01:16:27,015 --> 01:16:29,336
use the same algorithm. Everything about it would be the
1051
01:16:29,336 --> 01:16:36,095
same, except that HTTP signatures, the spec, I think, requires
1052
01:16:36,095 --> 01:16:41,655
a date header. But ultimately, you still have to issue
1053
01:16:41,655 --> 01:16:47,716
a key to a human being, right? A downloading app
1054
01:16:47,716 --> 01:16:53,095
client would have to publish a public key somewhere. Right.
1055
01:16:52,956 --> 01:16:58,216
But now you could have a million little servlets with
1056
01:16:58,216 --> 01:17:02,576
keys. So how do you determine ultimately this is a
1057
01:17:02,576 --> 01:17:06,496
human they're watching or they're listening with this key? How
1058
01:17:06,496 --> 01:17:11,055
do you make that connection? That's what it comes down
1059
01:17:11,055 --> 01:17:14,775
to. Well, you can. There's just a lot of unfriendly
1060
01:17:14,775 --> 01:17:18,475
ways, but we can do it. Well, you can by
1061
01:17:18,475 --> 01:17:21,475
going – yeah, exactly what you said. Unfriendly meaning we're
1062
01:17:21,475 --> 01:17:24,095
going to keep like a public repository where we vet
1063
01:17:24,095 --> 01:17:29,595
people or something like that. Precisely. That'll be us, podcastindex.org.
1064
01:17:29,695 --> 01:17:34,796
All your keys belong to us. Well, you know, I
1065
01:17:34,796 --> 01:17:37,855
actually see this being something if there was going to
1066
01:17:37,855 --> 01:17:41,015
be some sort of list. I see this being outside
1067
01:17:41,015 --> 01:17:45,576
of the podcasting 2.0 namespace. I see this as being
1068
01:17:45,576 --> 01:17:54,775
part of like the OPAWG. OPAWG. OPAWG. The worst name
1069
01:17:54,775 --> 01:18:01,676
ever. It's the Open Podcast Analytics Working Group. Oh, wow.
1070
01:18:01,695 --> 01:18:05,076
And do you know who the Open Podcast Analytics Working
1071
01:18:05,076 --> 01:18:08,635
Group consists of? Let me guess. I'm going to say
1072
01:18:08,635 --> 01:18:14,716
Libsyn. No. Okay. I give up. James Cridlin and John
1073
01:18:14,716 --> 01:18:20,416
Spurlock. OPOG. That's OPOG sitting over there in their rocking
1074
01:18:20,416 --> 01:18:24,376
chairs. Johnny and the Criddler are over there running the
1075
01:18:24,376 --> 01:18:28,336
OP. Johnny and the Criddler. They're over there running the
1076
01:18:28,336 --> 01:18:35,055
OP-AWG, which as of right now consists mainly of a
1077
01:18:35,055 --> 01:18:39,615
list of user agents. Right. Yeah, that's right. Yeah. And
1078
01:18:39,615 --> 01:18:42,975
it's a very nice list. Like it's very – Spurlock
1079
01:18:42,975 --> 01:18:46,456
keeps that thing really clean and up to date. So
1080
01:18:46,456 --> 01:18:49,536
to me, this would be a great thing to add
1081
01:18:49,536 --> 01:18:54,275
to the OPOG would be a list of validated public
1082
01:18:54,275 --> 01:18:58,115
keys. It doesn't mean that you have to be in
1083
01:18:58,115 --> 01:19:03,676
the list. It just means that people serving HLS content,
1084
01:19:03,676 --> 01:19:09,876
hosts could choose whether or not they want to. To
1085
01:19:09,876 --> 01:19:11,996
me, I see this as two layers. You have an
1086
01:19:11,996 --> 01:19:19,336
HTTP. You require HTTP signatures on all playlists in 3U8
1087
01:19:19,336 --> 01:19:23,336
downloads. You just have to have the HTTP signature to
1088
01:19:23,336 --> 01:19:27,515
even get it. then the hosting companies can opt for
1089
01:19:27,515 --> 01:19:32,176
the next level of stricture, which would be we now
1090
01:19:32,176 --> 01:19:35,676
– us, we have decided as a hosting company we're
1091
01:19:35,676 --> 01:19:41,055
only going to serve content to validated public keys that
1092
01:19:41,055 --> 01:19:46,076
exist on the OP AWG list. You know, the real
1093
01:19:46,076 --> 01:19:51,216
way to solve this is what's your Bitcoin address? Send
1094
01:19:51,216 --> 01:19:56,216
me one site. You're good. That will happen. No, it
1095
01:19:56,216 --> 01:19:59,615
will never happen. But I've always felt that every human
1096
01:19:59,615 --> 01:20:03,935
being should have a public key regardless. Every human being
1097
01:20:03,935 --> 01:20:06,176
should have a public key. This is the one thing
1098
01:20:06,176 --> 01:20:08,496
that – Issued at birth. Yes. Tattooed on the back
1099
01:20:08,496 --> 01:20:13,615
of your hand and on your forehead. Ah, yes. Boom
1100
01:20:13,615 --> 01:20:16,975
shakalaka. And there it is. That's right. You will need
1101
01:20:16,975 --> 01:20:19,216
that to do commerce. Oh, where have I read that
1102
01:20:19,216 --> 01:20:24,095
before? Grocery store, show me your public key. Yeah. Everybody
1103
01:20:24,095 --> 01:20:28,536
needs a pub key. I mean – Eric P.P. said,
1104
01:20:28,536 --> 01:20:31,095
that's how SSL certificates work. Send me money and I'll
1105
01:20:31,095 --> 01:20:34,275
vouch for you. Pretty much. Yep, that's the way it
1106
01:20:34,275 --> 01:20:38,376
works. It would solve so many problems. It would solve
1107
01:20:38,376 --> 01:20:41,876
a lot. The podcast index – we vouch for people
1108
01:20:41,876 --> 01:20:44,456
without them sending us money. That's right. We just do
1109
01:20:44,456 --> 01:20:47,115
it. All the time. We just vouch. Why not? We're
1110
01:20:47,115 --> 01:20:51,655
vouchers. We're vouchers. We're vouchers. We're vouchers. Send your email
1111
01:20:51,655 --> 01:20:57,496
to voucher at podcastindex.org. Let's thank some people here, Mr.
1112
01:20:57,496 --> 01:21:01,095
Jones. We've been getting lots of boostograms today, which is
1113
01:21:01,095 --> 01:21:06,996
nice to see. Right there, 49,950, which I'm thinking was
1114
01:21:06,996 --> 01:21:10,756
supposed to be 50,000, coming in from Fountain from CELOS
1115
01:21:10,756 --> 01:21:14,735
on Linux. And he says 50K for supporting slash bribing
1116
01:21:14,735 --> 01:21:18,635
the podcast index censorship validated key system. You're in, my
1117
01:21:18,635 --> 01:21:21,775
friend. You're in. You got it. We got you. You
1118
01:21:21,775 --> 01:21:26,315
are in. Let's see. From coming in from the podcast
1119
01:21:26,315 --> 01:21:30,956
index website itself, Four Sevens from Summer Surf. He says,
1120
01:21:30,956 --> 01:21:33,055
enjoying the afternoon in the boardroom. Thank you for your
1121
01:21:33,055 --> 01:21:37,796
courage. Four Sevens from Lyceum. Kudos to Alberto Batella and
1122
01:21:37,796 --> 01:21:41,576
RSS.com co-listing and chatting with Mike Newman as we speak.
1123
01:21:42,036 --> 01:21:44,956
Oh, there's Dreb Scott coming in with a baller. 10,000
1124
01:21:44,956 --> 01:21:49,135
sats. Voucher McVouch. Vouch, he says. Yes, it's working. Our
1125
01:21:49,135 --> 01:21:53,855
system is working. Already we're done. We just solved it.
1126
01:21:53,956 --> 01:21:57,655
We solved it and we got money. Literally says, yes,
1127
01:21:57,655 --> 01:22:01,695
this is how things should work. I get to stop
1128
01:22:01,695 --> 01:22:04,676
selling Tennessee trick shot out of the trunk of my
1129
01:22:04,676 --> 01:22:07,475
car. I had never heard of Tennessee trick shot. I
1130
01:22:07,475 --> 01:22:12,235
love that term. Oh, the moonshine? Yeah. Tennessee trick shot.
1131
01:22:13,355 --> 01:22:18,336
That's a good show title. There's like every different, every
1132
01:22:18,336 --> 01:22:21,435
state has its own little flavor. Tennessee trick shot. Dreb
1133
01:22:21,435 --> 01:22:23,815
Scott, one, two, three, four. He says, Dave, great job
1134
01:22:23,815 --> 01:22:27,475
with those massive dumps of the raw data. That's what
1135
01:22:27,475 --> 01:22:31,256
I'm good at. Big, massive dumps. 777 from Salty Crayon.
1136
01:22:31,376 --> 01:22:33,935
Dave, could you elaborate on how your index filter marked
1137
01:22:33,935 --> 01:22:37,475
a bunch of fountain tracks as spam in the pipe?
1138
01:22:37,916 --> 01:22:41,895
How did that happen? I don't know. I don't know.
1139
01:22:43,036 --> 01:22:45,055
You got a row of sticks from Hey Citizen sent
1140
01:22:45,055 --> 01:22:48,475
from the bathroom on his Cast-O-Matic. That's where it comes
1141
01:22:48,475 --> 01:22:53,515
in from. 777 from Mike Newman, True Fans Boost from
1142
01:22:53,515 --> 01:22:58,975
PC 2.0. Thank you. We've got 1221 from C-Loss and
1143
01:22:58,975 --> 01:23:02,796
Linux from Fountain testing this week, 1234. So it's odd.
1144
01:23:02,076 --> 01:23:06,076
The helipad keeps giving me different numbers because I know
1145
01:23:06,076 --> 01:23:11,015
he sent 1234, but it's showing me 1221. Chad F,
1146
01:23:11,015 --> 01:23:15,456
triple three. Dave, off the dome, Jones. Off the dome.
1147
01:23:15,756 --> 01:23:18,456
Triple three is from Eric PP. Pew Pew, yes. Three,
1148
01:23:18,456 --> 01:23:21,076
three, three from Chad F. This is all testing. Dreb
1149
01:23:21,076 --> 01:23:24,195
Scott, one, two, three, four. Boost McTest Boost. Pew Two.
1150
01:23:25,155 --> 01:23:27,355
I love people sending us money to test. This is
1151
01:23:27,355 --> 01:23:29,676
all great. Thank you, Eric PP. Thank you, Chad F.
1152
01:23:29,916 --> 01:23:32,115
And I hit the delimiter with that. So over to
1153
01:23:32,115 --> 01:23:38,975
you, Mr. Jones. on the music thing I mean a
1154
01:23:38,975 --> 01:23:44,176
lot of that music is spam it's just spam and
1155
01:23:44,176 --> 01:23:48,496
all spam classifiers have false positives and false negatives every
1156
01:23:48,496 --> 01:23:50,996
single one of them it's not a solvable problem so
1157
01:23:50,996 --> 01:23:56,315
I think it just comes down to that because there
1158
01:23:56,315 --> 01:23:58,716
has been a problem with people and this is happening
1159
01:23:58,716 --> 01:24:02,416
on not just I don't know what Fountain's posting but
1160
01:24:03,095 --> 01:24:05,055
Not just Fountain and Wavelike and all that. You have
1161
01:24:05,055 --> 01:24:08,775
to be careful. People are posting copyrighted material. Yes. I'm
1162
01:24:08,775 --> 01:24:11,536
seeing it on Spreaker a lot. It's coming through where
1163
01:24:11,536 --> 01:24:15,655
people are posting, like, entire albums of, you know, copyrighted
1164
01:24:15,655 --> 01:24:18,836
music. Oh, really? Yeah, you can't do that. And so
1165
01:24:18,836 --> 01:24:22,815
it's going to get called. Where was I? I was
1166
01:24:22,815 --> 01:24:24,576
looking at it. Yeah, I should mention this is a
1167
01:24:24,576 --> 01:24:28,055
value for value project. You get this podcast and the
1168
01:24:28,055 --> 01:24:32,615
entire podcast index and your data dumps, everything, all of
1169
01:24:32,615 --> 01:24:35,975
that stuff. All of that is openly available for everybody.
1170
01:24:36,155 --> 01:24:38,095
All you have to do is say to yourself, you
1171
01:24:38,095 --> 01:24:41,176
know, it's kind of valuable what's happening over there. Let
1172
01:24:41,176 --> 01:24:43,615
me send some value back to keep these guys running.
1173
01:24:44,916 --> 01:24:47,876
And that's how it works. So you go to podcastindex.org
1174
01:24:47,876 --> 01:24:49,796
down at the bottom there. You've got a big red
1175
01:24:49,796 --> 01:24:53,475
donate button. You can send us your Fiat Fun coupons
1176
01:24:53,475 --> 01:24:57,076
through PayPal or a Boostergram, which we always enjoy. We
1177
01:24:57,076 --> 01:25:01,296
enjoy reading them. And hopefully Dave has now summarized everything.
1178
01:25:00,855 --> 01:25:08,855
He's used the Excel Copilot widget. Yeah. Tell me how
1179
01:25:08,855 --> 01:25:12,595
much donations we've had. And you get back. It's like
1180
01:25:12,595 --> 01:25:17,155
carrot or something. So I'll tell you something that I
1181
01:25:17,155 --> 01:25:20,595
have trained my robot to do. Okay. So after every
1182
01:25:20,595 --> 01:25:25,576
no agenda show, we do credits. And the credits are
1183
01:25:25,576 --> 01:25:30,095
executive producer, people who have donated $300 or above, associate executive
1184
01:25:30,095 --> 01:25:34,496
producers between $200 and $300. So while the end of show mixes
1185
01:25:34,496 --> 01:25:37,055
are running, I say, robot, do the credits. It goes
1186
01:25:37,055 --> 01:25:41,036
into the Excel file. It pulls out the names from
1187
01:25:41,036 --> 01:25:43,815
the corresponding values and puts them right into my OPML
1188
01:25:43,815 --> 01:25:48,855
prep sheet. It's beautiful. It does that, I'd say, 99%
1189
01:25:48,855 --> 01:25:57,796
accuracy. Why am I doing this? You got this thing
1190
01:25:57,796 --> 01:26:02,155
nailed. Well, I don't have the spreadsheet. That's true. Yeah,
1191
01:26:02,155 --> 01:26:04,475
why are you doing it? Tell your robot to do
1192
01:26:04,475 --> 01:26:06,815
it for you. You got to be thinking like a
1193
01:26:06,815 --> 01:26:09,296
broadcaster, man. Like, what is the crap that I hate
1194
01:26:09,296 --> 01:26:12,855
doing? Well, I hate going through the spreadsheet and looking
1195
01:26:12,855 --> 01:26:16,756
for all those stupid jingles everybody wants. so the robot
1196
01:26:16,756 --> 01:26:20,376
looks at the spreadsheet pulls up the jingles and then
1197
01:26:20,376 --> 01:26:23,775
i have my own spreadsheet reader when i'm reading someone's
1198
01:26:23,775 --> 01:26:27,355
donation note i hit the the the cell the jingle
1199
01:26:27,355 --> 01:26:29,395
cell and it loads up those jingles right in my
1200
01:26:29,395 --> 01:26:33,176
player that saves me half an hour a show day
1201
01:26:33,176 --> 01:26:38,015
i have nothing like this it took me five minutes
1202
01:26:38,015 --> 01:26:41,515
to vibe code it baby well i can't even fix
1203
01:26:41,515 --> 01:26:45,676
the i can't even fix the the spreadsheet that's coming
1204
01:26:45,676 --> 01:26:48,735
out. I'll have my robot show your robot how to
1205
01:26:48,735 --> 01:26:51,695
do it. Have your robot talk to my robot. We
1206
01:26:51,695 --> 01:27:03,376
need that. We need inter-robot communications protocol. IRP. IRP. I
1207
01:27:03,376 --> 01:27:06,155
don't. I'm a little afraid of your robot talking to
1208
01:27:06,155 --> 01:27:08,855
my robot. Oh, okay. I don't know where your robot's
1209
01:27:08,855 --> 01:27:12,576
been. My robot is dirty. That's what I'm afraid of.
1210
01:27:12,615 --> 01:27:14,876
I'm afraid it's going to teach my robot bad things.
1211
01:27:14,876 --> 01:27:19,355
Very bad things. Guaranteed. In the words of my mom,
1212
01:27:19,355 --> 01:27:21,055
it's going to be a bad influence on my robot.
1213
01:27:23,055 --> 01:27:26,655
Okay, where? I forgot completely. Oh, Martin Lindiscoe. These are
1214
01:27:26,655 --> 01:27:29,735
PayPal's. He sent us a dollar. Thank you. Thank you,
1215
01:27:29,735 --> 01:27:34,815
Martin Lindiscoe. You and Mike Newman having a ball over
1216
01:27:34,815 --> 01:27:39,555
there. Brendan at PodPage, $25. By the way, congratulations to Brendan.
1217
01:27:40,115 --> 01:27:41,555
Are we allowed to see? Are we allowed to talk
1218
01:27:41,555 --> 01:27:47,076
about it? blah blah blah blah blah blah blah blah
1219
01:27:47,076 --> 01:27:51,176
blah blah blah blah blah blah blah blah blue no
1220
01:27:51,176 --> 01:27:53,735
whoo you saved me right there you saved me i
1221
01:27:53,735 --> 01:27:55,595
did thank you i did you're welcome that's what i
1222
01:27:55,595 --> 01:28:00,956
do uh let's see 25 dollars thank you from uh
1223
01:28:00,956 --> 01:28:04,796
brendan at pod page appreciate that uh what we got
1224
01:28:04,836 --> 01:28:13,695
Here we got Marco at, let's see, Marco Van Rij.
1225
01:28:14,095 --> 01:28:22,836
R-A-A-I-J. R-A-A-I. R-A-I. R-A-I. Okay, Marco Van Rij. We have
1226
01:28:22,836 --> 01:28:29,695
the boost. R-A-I. Sent us $10. Thank you, Marco. Oscar Mary, $200.
1227
01:28:30,275 --> 01:28:33,836
Thank you, Oscar. Oh, boy, hold on a second. keeping
1228
01:28:33,836 --> 01:28:41,216
it running thank you very much i incorrectly classify his
1229
01:28:41,216 --> 01:28:43,336
music podcast as spam and he still sends us money
1230
01:28:43,336 --> 01:28:49,416
uh joseph maraca five bucks thank you joseph appreciate that
1231
01:28:48,996 --> 01:28:57,135
uh oh thomas umstad a hundred bucks shot caller 20
1232
01:28:57,135 --> 01:29:02,195
inch blades on the impala that beats uh what is
1233
01:29:02,195 --> 01:29:07,456
it called tennessee trickster tennessee trick shot trick shot that's
1234
01:29:07,456 --> 01:29:09,935
it trick shot yeah years ago i came for the
1235
01:29:09,935 --> 01:29:13,935
podcast talk now i stay for the ai chatter adam
1236
01:29:13,935 --> 01:29:16,475
take it from a native texan the cure for cedar
1237
01:29:16,475 --> 01:29:20,756
fever is raw jalapenos oh oh that's an interesting one
1238
01:29:20,756 --> 01:29:23,235
yeah i'll try that if you can take the heat
1239
01:29:23,235 --> 01:29:27,055
they'll Clear your sinuses. Go podcasting. Yeah, go podcasting indeed,
1240
01:29:27,055 --> 01:29:33,296
baby. Yeah. Mitch Downey, 50 bucks. Thank you, Mitch. That's
1241
01:29:33,296 --> 01:29:36,676
the Podverse crew. That's straight from the whole group there.
1242
01:29:37,376 --> 01:29:43,155
Lauren Ball, $24.20. Thank you, Lauren. Appreciate it. Christopher Harbarik, $10. By
1243
01:29:43,155 --> 01:29:47,796
the way, seeing Christopher Harbarik's name reminded me that I
1244
01:29:47,796 --> 01:29:54,796
am also going through and putting individual creator attributions on
1245
01:29:54,796 --> 01:29:58,996
each of the podcasting 2.0 namespace tags. What? It's something
1246
01:29:58,996 --> 01:30:03,336
that we've – well, I mean each tag was initially
1247
01:30:03,336 --> 01:30:08,275
proposed by a person. Yeah. And I think it's important
1248
01:30:08,275 --> 01:30:12,296
for those people to get the credit for their ideas
1249
01:30:12,296 --> 01:30:17,836
becoming what eventually led to real namespace tags. Yeah, so
1250
01:30:17,836 --> 01:30:21,036
that in 25 years, Adam Carolla will have invented it.
1251
01:30:22,595 --> 01:30:25,376
This will be properly documented so that Adam Carolla does
1252
01:30:25,376 --> 01:30:30,055
not get credit for the chapter tag. But so like
1253
01:30:30,055 --> 01:30:32,975
Christopher Hart, so I'm doing it in this way. I'm
1254
01:30:32,975 --> 01:30:35,176
doing – there's going to be a creator attribution. And
1255
01:30:35,176 --> 01:30:37,256
that's the person that originally proposed it and sort of
1256
01:30:37,256 --> 01:30:41,015
sherpeted it all the way through to completion. And then
1257
01:30:41,015 --> 01:30:44,195
there's also contributors that are getting a byline, too, where
1258
01:30:44,195 --> 01:30:46,956
those are people that had significant input in the discussion
1259
01:30:46,956 --> 01:30:49,975
thread or the issue where that thing got hashed out.
1260
01:30:50,656 --> 01:30:55,355
And so, like, for instance, James, he's credited on the
1261
01:30:55,355 --> 01:30:59,735
location tag. Alex Gates is credited on the alternate enclosure
1262
01:30:59,735 --> 01:31:04,555
tag. Do I get any credits anywhere? No. Oh. You
1263
01:31:04,555 --> 01:31:12,435
get credit for being awesome. Seems empty. No. Why would
1264
01:31:12,435 --> 01:31:15,935
it seem empty? It seems empty. I've participated in every
1265
01:31:15,935 --> 01:31:20,275
single tag. I've published every tag available to man. That's
1266
01:31:20,275 --> 01:31:22,576
true. I get no credit, man. I get no credit.
1267
01:31:23,555 --> 01:31:25,895
You don't even get credit for podcasting. You give me
1268
01:31:25,895 --> 01:31:34,475
some credit. That goes to Corolla. Let's see. Christopher Harbaugh
1269
01:31:34,475 --> 01:31:37,336
got a contributor credit on one of the tags. I
1270
01:31:37,336 --> 01:31:41,055
don't remember which one. He gave us $10. Thank you, Chris.
1271
01:31:41,336 --> 01:31:46,195
Didn't you and I create the value tag? We did.
1272
01:31:46,515 --> 01:31:48,756
Yes. Okay. Me and you were co-creators of the value
1273
01:31:48,756 --> 01:31:51,435
tag. I want some credit. I want the credit. You
1274
01:31:51,435 --> 01:31:58,256
invented the podcast enclosure tag. You trump everything we do.
1275
01:31:57,796 --> 01:32:03,836
I want the credit, man. I just give me more
1276
01:32:03,836 --> 01:32:08,355
credit. I just give me some credit. Or hook or
1277
01:32:08,355 --> 01:32:11,176
some blow. Either one is fine. Yes, send them in
1278
01:32:11,176 --> 01:32:14,836
the mail. Mitch. This is Mitch on the personal side.
1279
01:32:15,376 --> 01:32:20,416
This is Mitchell Downey, $10. Thank you, Mitch. Damon Kasajak, $15. Thank
1280
01:32:20,416 --> 01:32:28,176
you. Appreciate you. Terry Keller, $5. Chris Cowan, $5. Thank you, Chris.
1281
01:32:31,216 --> 01:32:36,015
Silicon Florist $10, thank you Derek J. Visker the best
1282
01:32:36,015 --> 01:32:42,796
name in podcasting, $21 Paul Salzman $22.22 every time I love
1283
01:32:42,796 --> 01:32:54,576
it Jeremy Gerds, $5 Michael Hall, $5.50 Todd Cochran $30 and we
1284
01:32:54,576 --> 01:32:56,576
are going to have Mike Dell on the show next
1285
01:32:56,576 --> 01:33:02,135
week and he will fill us in on Blueberry and
1286
01:33:02,135 --> 01:33:05,055
what they've been doing and just the strategy, you know,
1287
01:33:04,395 --> 01:33:09,775
or direction of the company, um, post Todd and everything.
1288
01:33:09,315 --> 01:33:11,275
It'll be good to catch up with Mike. Hey, question
1289
01:33:11,275 --> 01:33:16,076
on this, um, this pending signups for API access, I
1290
01:33:16,076 --> 01:33:22,775
guess that is. Yes. So, I mean, how do we,
1291
01:33:21,895 --> 01:33:25,536
I mean, these could all be phony baloney people. Oh,
1292
01:33:25,015 --> 01:33:27,656
many of them are, I'm sure. Okay. All right. So,
1293
01:33:27,656 --> 01:33:30,576
but if someone sends me an email and my own
1294
01:33:30,576 --> 01:33:35,796
Spidey send says, yeah, they're okay, then I can mark
1295
01:33:35,796 --> 01:33:39,055
active and send credentials. Is that how it works? Yeah.
1296
01:33:39,055 --> 01:33:41,416
And honestly, that's going to be extremely rare in the
1297
01:33:41,416 --> 01:33:45,055
history. In the last six years, I've probably had that
1298
01:33:45,055 --> 01:33:47,876
happen. I can count it on one hand. Yeah, I'll
1299
01:33:47,876 --> 01:33:51,775
bet. I plan to never look at that screen. It
1300
01:33:51,775 --> 01:33:55,256
only became a thing because two people happened to have
1301
01:33:55,256 --> 01:33:58,036
a problem at the same time. I got it. Yep.
1302
01:33:59,376 --> 01:34:02,536
My typical thing is like we're a free service and
1303
01:34:02,536 --> 01:34:06,656
we're donation run. Send me money. Send me some credit.
1304
01:34:07,796 --> 01:34:10,355
We have rules. And one of the rules is you
1305
01:34:10,355 --> 01:34:12,635
can't sign up for an API account from a free
1306
01:34:12,635 --> 01:34:15,716
email address like a Gmail. Yeah, yeah, yeah. And when
1307
01:34:15,716 --> 01:34:17,435
people ask me and people are like, hey, I'm trying
1308
01:34:17,435 --> 01:34:18,876
to sign up with a Gmail account. Can you do
1309
01:34:18,876 --> 01:34:20,836
it? I just don't respond. I'm like, no, that's the
1310
01:34:20,836 --> 01:34:25,956
rule. That's great customer service. I'm like, I'm not going
1311
01:34:25,956 --> 01:34:28,615
to make exceptions because I don't know who you are.
1312
01:34:28,895 --> 01:34:32,775
Yeah, exactly. Go get a different – go spend $5 on
1313
01:34:32,775 --> 01:34:36,435
a domain from Hover and get a real email address.
1314
01:34:36,735 --> 01:34:39,256
And, I mean, it's not that much to ask. I'm
1315
01:34:39,256 --> 01:34:41,515
with you. Brother, I'm with you. I ignore all those
1316
01:34:41,515 --> 01:34:45,916
emails. You answer more than I do. I do pretty
1317
01:34:45,916 --> 01:34:49,935
good on answering, yeah. You do. Gene Liverman, five bucks.
1318
01:34:50,176 --> 01:34:52,656
Thank you, Gene. Oh, that's all of our PayPals. Oh,
1319
01:34:52,656 --> 01:34:55,775
we got some boost, though. Yes. We've got... Some boost.
1320
01:34:55,876 --> 01:35:00,036
Some boost. Oh, see, loss on Linux. 50,000. That's what
1321
01:35:00,036 --> 01:35:02,435
you want. You read that earlier. I did, yes. I'm
1322
01:35:02,435 --> 01:35:04,536
going to give him a baller for that. Baller! Shot
1323
01:35:04,536 --> 01:35:08,895
caller, 20-inch blades on the Impala. That's a nice boost.
1324
01:35:09,076 --> 01:35:12,956
Boost. How did I overlap you on that? Oh, I
1325
01:35:12,956 --> 01:35:14,876
know what I did. Yeah, I know why. Because I
1326
01:35:14,876 --> 01:35:16,595
did it later on in the show because I forgot
1327
01:35:16,595 --> 01:35:21,256
to earlier. Ah, yes. Okay. Oh, and that's all I
1328
01:35:21,256 --> 01:35:22,676
got. The only other one I've got is the comic
1329
01:35:22,676 --> 01:35:29,176
strip blogger, 19,000 sats through Fountain. And he says, howdy,
1330
01:35:29,176 --> 01:35:33,656
Dave and Adam. Please bookmark this. HTTPS colon slash slash
1331
01:35:33,656 --> 01:35:39,036
wherever dot audio by Andrew Grumet. Quote, it's a podcast
1332
01:35:39,036 --> 01:35:43,595
listening software that works in browsers, mobile and cars. No
1333
01:35:43,595 --> 01:35:47,036
logging in and nobody watching you. All data stays on
1334
01:35:47,036 --> 01:35:51,515
your phone browser. Easy import and export for portability. fast
1335
01:35:51,515 --> 01:35:57,076
QR code-based sharing. End quote. Yo, CSBAI archwizard. Yeah, I
1336
01:35:57,076 --> 01:36:00,055
love what Andrew has done. Andrew Grummet, by the way.
1337
01:36:00,235 --> 01:36:03,376
No credit. He's been on the show. If he gets
1338
01:36:03,376 --> 01:36:06,615
no credit. He'll get it. He needs a lot of
1339
01:36:06,615 --> 01:36:09,475
credit. No, he's going to get it. Because he's got
1340
01:36:09,475 --> 01:36:14,836
stuff in the namespace. Oh, okay. You get credit. Here's
1341
01:36:14,836 --> 01:36:18,195
some credit. You get some credit. And you get some
1342
01:36:18,195 --> 01:36:22,635
credit. Everybody gets some credit. Everywhere.audio. It's a great audio.
1343
01:36:22,796 --> 01:36:27,555
A very business-like professional note there from CSB this week.
1344
01:36:28,395 --> 01:36:30,336
All right, brother. I'm going to let you go because
1345
01:36:30,336 --> 01:36:32,815
you need to throw some things in the bag. You
1346
01:36:32,815 --> 01:36:34,595
know you're going to wind up on this camping trip
1347
01:36:34,595 --> 01:36:36,456
and it's like, what do you mean we've got no
1348
01:36:36,456 --> 01:36:41,895
pigs? What? Yes. We're all out of pigs. We don't
1349
01:36:41,895 --> 01:36:44,176
have any matches. Oh, man, what are we going to
1350
01:36:44,176 --> 01:36:47,076
do? And I'll see you at 3 o'clock, right? We've
1351
01:36:47,076 --> 01:36:50,395
got our early meeting. Exciting things happening with the podcast.
1352
01:36:50,416 --> 01:36:52,416
I thought it was 2.30. I thought it was 2.30.
1353
01:36:52,555 --> 01:36:54,796
If it's 2.30, is it 2.30? Well, I got to
1354
01:36:54,796 --> 01:36:59,775
hurry then. I got to rock and roll. Okay, run
1355
01:36:59,775 --> 01:37:02,256
and rip. All right. Hey, boardroom, thank you very much
1356
01:37:02,256 --> 01:37:05,095
for being here. Thank you for providing your very valuable
1357
01:37:05,095 --> 01:37:08,015
feedback, and we look forward to seeing each other again
1358
01:37:08,015 --> 01:37:10,656
for the board meeting next Friday. Until then, bye-bye, everybody.
1359
01:37:24,916 --> 01:37:30,676
Podcasts are cool. You have been listening to Podcasting 2.0.
1360
01:37:30,815 --> 01:37:38,496
Visit podcastindex.org for more information. Go podcasting! Get some tissue.
1361
01:37:38,496 --> 01:37:38,956
It's coming.