More Podcasts I've Appeared In

Mostly AI Arguments

I have the honor of being the 200th Jim Rutt show episode! We do a deep dive into LLM-native media and the future of content.

A highlight for importance:

Jim: Yeah, that is interesting. You know, again, I think it’s summed up my idea that these LLMs will empower the periphery, because today the periphery does not have the literary skills or the money to produce content at the quality of the New York Times. But with LLMs, they can approach it, at least reach the level where most readers won’t be able to tell the difference, and hence will be able to bring new ideas into play from the periphery, not just the stale old crap from the mainstream media.

Brian: Yeah. And what’s very exciting as well is that I think that in many ways, the story of the Internet is the story of unbundling, right? It’s the story of having, you know, you started the clearest story is with something like Netflix, although I think that’s a rather unfortunate ending. In some ways, and in some ways not. Okay, I’ll tell like two versions of the story.

And I think that one part has led to a good ending and part is led to a bad ending. So the story goes as follows, you know, you had the big cable companies, all of them were buying up these huge conglomerations of channels and really people were paying for tons of things that they weren’t actually watching. And this was just the most efficient way to run things in the television age, because there was just no simpler way to kind of help people select.

And then as the Internet came along, that technology arrived that wave selecting arrived and then people moved to streaming, people moved to online pay per play or you know, different kind of streaming services that were much more individuated. And then as that moved along, we had two endings. One ending is the route that Netflix eventually took, which was kind of emulating the original TV kind of bundling model.

So you know, you bundled everything together just in a new different order, you know, it’s probably better than not to actually rearrange the bundles and have them more modernized, but not the best ending. The other way is something like YouTube, where you had a very fractionalized environment, but that could crosslink. So essentially, what I mean by that is that you have, it’s impossible to watch all of the videos on YouTube. You know, there are like billions of hours uploaded on that thing.

But there are essentially regions within YouTube that people watch. There are things that are similar to each other in idea space, you know, this is something that actually can be visualized directly with something like AI. And these bundles in idea space is very easy to travel between them. But there are also, you know, possibilities of traveling across from you can go through a brand new video in a brand new space. If you just, you know, you know, go on YouTube and search up something that you’ve never looked at before. And it’s very different from anything you’ve looked at before. But you can also build these kind of implicit links.

You can build this much more complex map. So whereas like a human recommender, you know, this is the problem of the original cable TV people, whereas a human recommender could not really tell you, you know, you have these interests, right? But here is something that you never looked at that, you know, quite frankly, many of the people who have the similar interests as you might not even like, but because of the exact combination of interests that you have, you might like this new thing.

To have a kind of political discovery mechanism to have a kind of multi dimensional, you know, not just red versus blue, not just, you know, pre packaged demographics, TV guide kind of system. I think it’s a huge improvement over what we have. And I’m interested to see if, first of all, if you agree with that, that’s actually better. And whether you think it’s likely.

A highlight for fun:

Brian: So there was this YouTuber, I forget the name right now, who uploads like AI voice covers of songs. And there was this one AI voice cover of a song that has since been removed. I have no idea why this is my, this was my single favorite AI voice cover.

This channel removed it. And the reason why it was my favorite AI voice cover is that like, it kind of broke strategically. Like this was a song that was kind of like originally also performed by like a very cute girl. It was supposed to be like an AI voice cover by like a different like fictional character. And it had like voice cracks and it had like just like mistakes in the song. But the mistakes made the song better.

Jim: Okay. I love it.

Brian: Yeah. Yeah. And so I’m thinking like, oh, this is like, this is the advent of AI. This is like, I’m writing an article on this maybe, you know, like this is the expansion into new variables that like quite frankly, like humans don’t have the balls to like mess around with that. And the author just deleted it. I have no idea why, you know, this is honestly, like in my opinion, you know, still like arguably the best work of AI art that I have ever been exposed to. And it’s just gone. It’s just vanished. And I can’t find it on archive either. It’s just gone from all the archive sites.

Anyways, the song in question is Tabun by Yoasobi, covered by “Hu Tao” on this channel. Send nice requests for him to reupload the song please.

Last week I also went on the FAI’s podcast, the Dynamist.

This is an extension of my article in Pirate Wires.

The Costs Of Europe's GDPR Regime

A representative quote:

European politicians advertised GDPR as a way to protect the privacy of European citizens. Did it increase the security of European companies and prevent hackers from stealing data? Nope. That would require technological innovations and code fixes, something bureaucrats are incapable of producing. Did it curtail state surveillance powers? Certainly not. Instead, their citizens got annoying cookie banners and useless compliance paperwork. GDPR ended up being a program that cut checks to bureaucrats, raised costs for companies, and killed half of new app entries. 

The EU rugpulled its citizens. They promised one thing and delivered the opposite.

My favorite part of this podcast was the questions about a tech theory of change. It’s true that tech hasn’t had much advancement in terms of coherent political strategy, outside of “recall the people who hate us and love criminals”. That simple formula might be just what we need in the current situation, though.

The third outside media piece is with Simone and Malcolm Collins, who have each been on this podcast before.

We did a serious episode:

This was the interview in which I fence off a lot of bad AI risk arguments, as well as the uniformly bad “AI Ethics” people and identify what I think the good AI risk arguments are.

We also did a less serious episode.

I rarely talk about dating advice. I’m not sure I give any coherent theory here, this episode mostly consisted of me describing the wild things zoomer friends are up to at any given point in time. Still if you want extended FTNW content, here it is.