Episode 824 transcript

FLOSS-824

Jonathan: Hey folks, this week Doc joins me and we talk about personal AI. Sort of a wish list for what we want that to be and then some thoughts about how to get there. We look up a couple of projects that may get us there if you're willing to put the pieces together and more. It's a lot of fun, you don't want to miss it, so stay tuned.

This is Floss Weekly, episode 824, recorded Tuesday, March 11th.

Hey folks, it is time for Floss Weekly. That's the show about free Libre and open source software. I'm your host Jonathan Bennett. And today we've got a co host and a guest who are the same person. It's because we've got Mr. Doc Searles with us. today. And we were, we were scrambling for a guest today. And I said, well, I thought I had one, but then it turned out he couldn't do it today.

And Doc said, well, you know, I was supposed to be at scale and do a presentation and I didn't get to do it because I had some medical thing come up. I believe you said you're fine by the way. It was just one of those things.

Doc: Yeah.

Jonathan: Yep. And I said, come, let's do the, let's do the presentation you were going to do at scale.

Let's do it on the show. And he said, Let's do it. So what are we,

Doc: what are we talking about, Doc? So here we are. Well, the, at scale, there's a, there was also the QI summit. QI is an open source, um, project toward personal AI And I'm involved with it it has like seven or eight hundred volunteers at this point.

It's got some code mostly working on an OS. There, but I don't want to go into that because I don't know enough about it. And I think it's beside the kind of points that I wanted to make in the talk I was going to give there.

Sure.

But I couldn't do it, you know, so and and I thought well, I'll just give the talk here But I I ended up having this really interesting Conversation with chat GPT about what personally I is and should be There was a leading conversation in the sense that I I kind of urged in the directions.

I wanted to go You know it now Yeah,

Jonathan: the skeptic in me wants to say that having a conversation with one AI about another AI that's sort of gratuitous Navel gazing.

Doc: Well, it's in a way except the the The baby that produces the navel hasn't been born yet. So it's there's, I mean, personally, I, and I've said this a bunch of times, I think personal AI in 2025 is pretty much exactly where personal computing was.

50 years earlier in 1975. A really good idea? We don't have it yet. I mean, there's some examples of it out there. I think it's 75 by that time the Apple 1 was out and the Apple 2 was on its way, and in the next several years we had the TRS 80 and the Sinclair and the Osborne and a bunch of others.

But, It was, it was, it was hardly thinkable. And, and so we tended to think of personal computing that as well. How do we put a mainframe on your desktop? Right. And, and it's the same way now I'd say, well, how do we take corporate AI and make it personal for you? And then we're still thinking inside the corporate world, we're still thinking.

And we're getting a difference now, of course, is that there was no access to computing in 90, 95, 1975 rather nobody had any access to it unless they worked for a big company or something like that. And they were doing batch processing with cards and stuff like that and, oh, the Altair was out and you could.

Program it with switches.

And, you know, snap a tape, a paper tape or something. And that was personal computing. But that's what got Bill Gates going on it. Like he saw Altair and said, I have to do this. And he dropped out of Harvard to do it, and the rest is history. He did rather

Jonathan: well for himself. He did rather well for himself

Doc: with that.

And but the I think there's a sort of a paucity of imagination about, it's not even imagination, I think we're just not considering. we need from a personal AI that we're not going to get from the corporate kind. Starting with the fact that it's yours and it's private. The, the main thing for me is the data.

You, all of corporate AI has been trained on, on the entire web. Plus lots and lots of books lots of other things. It's a massive amount of stuff that is trained on the models are great They're not what they're going to be but they're you know, they've used that data and a lot of programming and logic to Do a really good job of speaking in English or whatever language you want to chose and making a lot of inferences and for one thing or another and Emulating humanity and and human conversation and stuff like that that we're all very familiar with and to the point where it's very You know, very useful.

And in fact, I think they've done a terrific job of leapfrogging Google. I mean, Google should have been here five years ago. They're not, they weren't, but we're, we've replaced this again. We're in the corporate world right now. We've replaced searching as if you're looking through a library with Q and A, with query, with queries, you, you don't need to look in the books in the library, you just ask the library.

You know, a question and, and it's because Sears goes and looks through the library and gives you an answer or a collection of answers that are quite credible and useful. And you go past that and say, great library, now, you know, do my term paper for me and it'll do that. Right. So, it's, it's very handy that way, but we have these sort of two modalities there, which is one is search and index.

And the other is ask it a question and and chat GPD kind of modally ask it a question, but now Meta and Microsoft and Anthropic and a bunch of others have come up with alternatives that are all roughly the same some are better than others. I like perplexity because it gives you sources.

But again, it's looking at a giant index and. And give, and answering questions. The key piece here for personal AI is, how do we do the same thing for our lives that corporate AI is doing for the world? And and our lives are. Our contacts, our calendars, all our health records, all our financial records, our obligations, our recurring payments when we bring the garbage and the recycling out to the curb what do we pay for that?

Who do we pay for that? Our travels. Where were we when we had lunch with so and so? Our, our work, you know, I mean, keeping records of our work, especially if, and you and I are both kind of solo operators in some ways, we have consulting businesses. When do we do such and such for so and so? What do I owe them?

What did they pay? When, how long did it take them? I mean, all this kind of stuff. And We don't have that yet, and we don't have it in coherent form, and an awful lot of the data that we would need is in the hands of people who are not us, okay? So for example you know, so, we're watching White Lotus and Reacher right now, and and we're watching them on our new Samsung TV, which has, and we have an Apple Gizmo that hangs off the side.

And how does, you know, and I don't remember where we were with either of these, you know, we haven't watched them in a couple months, how many episodes are we into this? I don't want to just do a Q& A on that. I want to look at something. I want to look at something that's like a spreadsheet that I can refine, say, okay, give me a list of all of the subscriptions that I have to streaming services, and that includes, in my case, SiriusXM on two cars and portable devices.

Plus Sonos, I've got that. I've got but all of these streaming services and, and when, when, when does it come up for renewal on this? When, I mean, all of these things depend to some degree and you're not knowing something, but the TV knows. All your new TVs come with spyware in them, you know, I mean, you need to find where the camera is on it and put a black tape over it because it's there, you know, I mean, and I was even looking up on ChatGPT or whatever, how do I turn off the surveillance on our new Samsung OLED TV and what they told me was current like three weeks ago but Samsung has changed it and now it's something else and they want to make it as hard as possible for you to turn off the surveillance.

Of course. And they all do this but that's that's another gripe but I'd rather have is show me what I've watched and when and there are countless shows and we don't even watch that much TV we all watch some that I don't remember. We'll watch two episodes, and wait a minute, we've seen this. You know, it's, you know, you go into that stuff, so it'd be nice to have that.

That's a fairly trivial example. But what's happening in the world right now is that old fashioned over the air TV that got replaced by cable TV and satellite TV, both, all of that is being replaced by subscription TV. Where For example, if you're a sports fan, you're, oh my gosh, you know, the NFL or the NBA could be on any one of five different services.

There are all kinds of conditionalities in there. We could use personal AI to solve this. Now we could go to ChatGBT and ask it questions about that and probably get adequate answers. We're not going to get personalized answers. The personalized, or if we get a personalized answer. It's good. I hate the term hallucinate.

I'm sorry, BS is the right term here because that's exactly what it is. It's making something up it hopes you believe, right? That's plausible sounding, but it is BS and And it does that, and it does it very innocently, like a butter wouldn't melt in its mouth when it does that, and But, but rather than critique what we have with corporate AI, let's start building personal AI starting with the data we need to be in control of our lives.

Not just know stuff about it, but control it. You know how, you know, now I'm old now, but I mean, even back in 2008 when I went, when I started in the Harvard medical system cause I was hanging out there at the time and I could get into it, and that's such, by the way, exclusive to Harvard. It's like I'm in the Indiana University system here and it's called IU Health and it has nothing to do with the university anymore.

It's a separate thing. I don't know if Harvard's like that now, but my point is. I could send a request to 19 different prior healthcare providers and get back data from them. What I got were scans of faxes and copies of scans of faxes. They're upside down, right side up. Sometimes it looked like they were done by Da Vinci because they were written backwards because they were like the mirror.

I mean, it was beyond useless. I mean, beyond useless. Anyway, my, my point about this, well, AI might be able to make sense out of this, right? Okay. Give me all that crap, there's copies of faxes of scans. Do OCR have a model that understands this kind of stuff? Apply to it. I would like to be able, I don't know if you've noticed this with Amazon if you buy stuff on Amazon, it kind of breaks out, if you look at your account records, by shipment.

But Your visa bill doesn't line up with that. The dollar amount you pay may be the same, but they're not the same because the visa bill says 45. 23 and you have, you know, a 13. 45 on one and 17. 65 on another. And you'd have to start doing algebra or something or make your own spreadsheet to figure this out.

Whereas NAI, smart enough to do this. Okay. I recognize that as an Amazon bill. I know these conditionalities that are embedded in this. I, I see this over here. These match up. Okay, we'll, we'll work that out. You know, our property. I have, I have books here in Indiana. In my new bookshelf, my new old bookshelf.

We have nothing new. We get it used. It's like this in Oklahoma too. I mean, I'm sure. If you go to a thrift shop in California, you're paying 10x what you'll pay in Oklahoma or Indiana. Yeah, that's true. It's just true. I mean, when you, it isn't the sticker shop, when you go to the coast, you get horrible sticker shop.

It's like, wait a minute, the dollar doesn't work here because this is much higher. And when you go from the coast to like we did in Indiana, it's like, Wait a minute. This, this state is on sale. Let's, let's live here. So that's what we're doing. But my point is that we, you know, I want to be able to take the phone and I want to point it at the bookshelf.

It's got very high resolution on the phones now. And I, and take a picture of the spines of those books, have pattern recognition happen and have. A list of all those books, right, and I do that in California where I have books, in New York where I have books, and Los Angeles where I have books, and shoot those, and here's a list of all the books and where they are, okay, I would like to know that, and, I mean, the list goes on, I mean, our travels, okay, Google Maps and Apple Maps and, and you know, All of those know where you've been.

They're, they're tracking you. Your car is tracking you. If you have a late model car, it has a cell phone in it. You don't even know the number of that cell phone. It's known by Toyota or Chevy or whoever it is, and they're busy selling information about you to insurance companies because that's an extra way they make money.

We need that data. We can use that data. We can make much better use of that data than the insurance companies. that they're selling, I'm sorry, that they're selling it to me, anyway, so I've got

Jonathan: a question for you then.

Doc: Go for

Jonathan: it. So some of these things that you're talking about like already exist, let's just say photos for instance.

So when I take a photo on my Android cell phone, it all goes up to Google Photos and then I can go to Google Photos and say, I want to see pictures of. Weather or I want to see pictures of fireworks or I want to see I want to see tech pictures computer pictures You know and it's got an AI it's got pattern recognition in there and it'll do that search and we'll get it back to you The problem well multiple problems But one of the problem that I have with that is the reason that Google does that is because they also have a clause in their Terms of Service that you give us the right to use your pictures in such and such way and they also use that data to train their AI, right?

So like there's strings attached. And then the other problem is, you know, that's one service. And then if I want to say, well, where have I been over the past two years, that's a completely different service. Those two don't talk to each other correctly. And I'm curious And they're not working for you. Well, that's the other thing.

They're not working for me. My data is the product. I am not the customer, right? And so the question is, how do we get there? Is there a, is there a path where we get from Google is the AI and I'm the product, to I own the AI and it's the product?

Doc: I think we start with the low hanging data fruit that is actually ours and we can, not already sitting out in clouds of various kinds.

So So I mean like the book example is one of them. Our own personal property is another. Our, our purchase records are another. Our contacts and calendars, even though most of our calendars and our email, I hate to, even that's the case are, you know, I mean, your email is yours, even if it's a Gmail, okay?

It's still yours. You could, you could take that. Thank you, SOTP and IMAP. I can copy that out.

Yep.

I can. I can, I can move it to some other service. I don't have to have it there. There's let's take the data that is. or enough hours and where the gating factor for using it does not require that we go into Google or that we shake down Chevy and Nissan for the data that they've collected about us.

That's more of a longterm thing. And then prove and then, and then prove the utility of that data to us individually. That makes us, you know, better human beings, citizens, customers, workers, Parents, whatever else is involved in that, you know, the, because there are many different, we all wear many different hats and play many different roles.

But I mean, you know, I mean, even like on the parental side, you know, you know, what sports teams are the kids on? What are their grades? What are they doing in school? Where, where, you know, where are they? When did they do this? Right. There's a list of their friends. When are their birthdays? I mean, there's that kind of stuff that's of interest to us, but not necessarily to the whole world.

But anyway, once we prove some of that out, then we can go after the higher fruit. Sure.

Jonathan: I'm trying to, I'm trying to figure out, I guess, the form factor? Like, what, what makes sense? So what, what, what would this look like? Are we talking about, you know, Western digital or Synology building a, a NAS? A little, you know, a home use desktop NAS, network to stack storage, that also has a GPU in it?

And then you put all your data in that, and it's going to also index it, and you've got your own little AI that lives inside that desktop hard drive that you can ask questions of? Is that sort of the, the form factor? That is my current fantasy.

Doc: That's my current fantasy, actually. It's I wouldn't call it a fantasy.

That kind of exaggerates you know, what, what it might be. I think, I think we need our own, You know, it's not, I mean, let's say that what, I'm not sure everything I'm talking about, I've been talking about, requires all that much compute. I'm not really sure it does. But let's, let's say it does, it requires a lot of compute.

And the, and the you know, the, the hardware that you have in your laptop isn't going to cut it. You know, I'd, I'd want a separate device. When you, I mean, you could. Certainly get from Synology or any one of those companies, you know, some kind of box that'll sit out there. I imagine somebody will make an appliance at some point that'll do the same thing, that'll have GPUs in it that are optimized for, for AI kind of work.

But in a way though, we're before the beginning of this, right? All of this stuff is on the table. That's why I'm just sort of focused on Actually, before we even get to how the processing is done, let's look at what it's working with. And, and by working with it, I just mean our lives. I mean, some people have almost no property, or they rent it all, and they don't care about the property.

And other people, that's just an enormous part of their lives. And with other people Travel is almost everything or it's kids or whatever else or work. I mean you work all the time, but We go from but you know, most of us go from one job to another And what do we want to take with us? Is it only in LinkedIn where you're basically?

You know, exaggerating or you know, whatever to those people. I mean, it's, I mean, LinkedIn, I mean, if you're looking at a way to share employment history and, or even know what you've done in the world, what a horrible interface to do that. It's certainly, I mean, we're all social. To me, my, you know, the contact, the contacts I have on my phone and my computer are far more a platform for.

Being social than anything I have in what's called social media. I mean, I mean take Twitter. I mean, I, you know, I followed, you know, a few thousand people on Twitter back when I was active on it. I don't know who most of those people were. I don't remember at all. You know, I sorted them out. Oh, these are journalists.

These are all my open source contacts for Linux journal when I was doing that. It was an enormous number of people. And, but that was, that was on Twitter and it was a list on Twitter. I don't even know those lists are still there. I've, I've no idea, I've just haven't been much on Twitter in, in recent years.

And then, you know, Blue Sky and the rest of it is kind of trying to replicate this really inadequate, horrible writing platform that we had with Twitter, and, and do the whole thing over again. It's like, wait a minute, oh my God, it's like, we could do better than that. But my point is that I, I actually think that if we hit, if we're on top of our lives at home.

We are going to be better at doing the things that we do as people, you know, whether it's this as simple as knowing who else to go to church with. I mean, it's all, all this stuff is, is, is personal for us and it matters to us, but it's not, it not only isn't, but shouldn't be of that much interest to.

The Googles of the world, except they're just trying to give you better advertising, which I also think is a flawed model that's going to die in the long run, too. We just haven't, it hasn't died as fast as I wanted it to, but it's just, it's a pretty lousy way to run an economy.

Jonathan: Yeah, oh I've thought about that.

One of the, one of the depressing conclusions that I've come to is pretty much as long as we've had technology, it's been, it's been paid for by advertising money. I mean, that's how they made the soap operas back on the radio back in the 30s. This, this show is sponsored by Clabber Baking Soda.

Doc: Yeah, what, what I love about podcasting right now is, A, I mean, my favorite line about podcasting is wherever you get your

podcasts.

It turns out RSS is something everybody could use. It costs nothing. And and the other thing is I've got a little thing on every different podcast app I could use that says, Go forward 30 seconds, you know, and I can skip over that stuff. It still helps pay for it. But we had the same thing with, you know, VCRs and DVRs and we could skip over the ads on those too.

We just spool stuff and skip over it. But I, this is a side thing, but I, it, it always bothers me when somebody says, you're not saying it, I'm not saying you said it, but I hear this a lot, you know, the internet is paid for by advertising. No, it's not. Google and Facebook are paid for by advertising. They are not the internet.

The internet runs a TCP IP. If you look at the entities that pull the wiring through, we're now on a two two gigabit fiber connection here, by the way, this is very cool. It's brand new. But I'm not quite on it. It's sphinctered right now through a Wi Fi hotspot that will do more than 600, 600 megs.

Never mind that. I, I don't, I don't have the router hooked up yet that I'm going to get, but I'm debating which one it's going to be. But but the The, you know, I'm paying gigabit now, Indiana for that. Okay. They're, I'm not, and they're not paid for by advertising. They're paid for by rate payers. Right.

Before that I had Xfinity. I was a rate payer for Xfinity. Xfinity pulled the cable. The coaxial cable that I used and they had mostly cable TV on that. They changed their business model to internet, you know, primarily, it used to be cable TV with internet gravy. Now it's internet with cable TV gravy, but it's, but it's still rate paying either way and, and, and all the biggest operators.

There's no longer a phone system in there that is all about billing every, across every border crossing. That's, that's the great thing that TCPIP did. It's like, I mean, suddenly all of a sudden all the phone and cable companies are looking at each other saying, holy shit, we don't have to pay each other for passage.

Because it's not, because the TCPIP doesn't do that. And that, I mean, that to me is one of the greatest open source successes in, in, in world history. And same, same thing with HTTP, you know, we did, Adobe wasn't telling us how to, how to, how to write, you know, there's this open standard where you can just write in HTML and that's, that is fine.

Anyway, um, I think that there's, I mean, I think something analogous is going to happen. At the personal level, when, once we, whether, whether we have those boxes, does the box come first? Does what we do in the box come first? I don't know, I know, I mean, Apple is building into their, you know, M2, Chipsets that some GPU ish kind of stuff, but it's all for their purposes And and what they have right now, and I'm using Apple stuff here.

I hate to say but there it is Their Apple intelligence is all candy. There's nothing nutritive in it at all It's I mean I not not as far as I could tell and and what there may be this Nutritive is that they've got a kind of chat GPT back in there's no imagination about what you can do As an individual when they're probably among the bigs the best position to do something with that Yeah, but they're not going to because they're I don't know why they're just be there who they are But I think I really I mean, here's an interesting thought experiment what would have happened if AT& T had opened Unix In 1983 or in 1982 or one, you know when, when it literally, it was, it was Ms.

Doss, there's a CPM, I mean, an Ms. Doss beat CPM because Doss is cheaper. You know, Gary Kal wanted to charge you a thousand dollars a box or some crazy thing like that, and somebody will come in and say, no, you're wrong. SRLs, . I probably have wrong. So anybody who's listening and correct me after the fact, but , uh, there's.

You know, but they wanted to charge for operating systems, but what if, what if AT& T had a brain back then and said, you know what? We should make Unix free and open. What would have happened? Oh yeah. Right? Holy, holy Christmas. I, well, I think there's a similar moment right now for open source personal AI.

Yeah. We don't have open source in corporate AI. That's not there. Open AI had that sort of mission in the first place and then they. Screw that, and

Jonathan: Yeah, well, so there Boy, a lot of different directions, so I'm going to go with that. There are some open source AIs. Although, for various definitions of what it means for an AI to be open source, right?

But like, for example, DeepSeek, all of the models on that is available under the MIT license. You can download, now you need a little bit of a Horsepower y video card to do it. Yeah. Or an accelerator, but you can download the DeepSeq model and run it locally, which, you know, in and of itself is really interesting.

I have been playing around, not with not with those sort of LLM models, but I've been playing around a lot with image generation. Because I find that really fascinating. Yeah. And I run that. The first thing I found was a website where you could do image generation there. And you know, one of the first things that I was looking at doing is, like, creating characters for tabletop roleplaying games.

That was something I was into and I thought, well, you know, if you could make a portrait that was, cause I, I, I had this whole digital system for doing it for, for playing like a tabletop game virtually. And it came to me like, well, if you could make a portrait, that would be really cool. And so I got into that idea.

And then, you know, here recently I got to look and it's like, well, I've got a reasonably decent video card in my desktop. How much of this is available in, in, you know, open source, where you can actually use it locally? And I found that there are, they're like, Hugging Face is one of the big names.

Hugging Face is there you go. Yes, yes, it's, it's a whole bunch of open source models, and you can run them locally. And then they've got plugins too, and so one of the plugins they've got is a a, a plugin, I forget what it's called, but it'll, you can give it Pictures and it will learn to recognize a face and then you can say okay now Give and people use this for nefarious purposes, right?

Don't do that. That's not what i'm talking about But you can say okay. I want to see a you know, show me a picture of A barbarian standing on the field of battle.

Doc: Yeah

Jonathan: and put my face on it, right? You can do that sort of thing. You can do it locally on your own video card and so what i'm thinking about with that is You talk about the other revolutions like we're we've we're all here Enjoying the fruit of the personal computer revolution.

Well, how did that start? Well that started with just a few people that thought hey What what happens if we take this this nifty new chip from intel and we put it into a little tiny box with with? Switches on the front and they built some of those and you had a little niche of people that said that's the coolest thing I've ever seen here take my money and the next thing you know, you know, we've got Dell and IBM, IBM, the IBM PC and eventually, you know, Dell and HP and everybody wants to make them.

I think maybe we're at the same point with personal AI where right now you have just a small group of enthusiasts and they're in this niche and in some ways, maybe we're waiting for. the next IBM to come and say, well, what if we turn this into a product? You know, what if we make this personal AI thing into a box or, you know, do something that makes sense and put it on people's phones?

Doc: Well, an interesting thing that chat GPT does in these dialogues is it answers every question with a question at the end. It says, well, have you thought about this? Like, you know, what, what is it going to take to make demand happen for this? And that was one of the questions it had, I think. And. And I said, we need the invention that mothers the necessity, right?

That's, you know, we need the thing, you know, I remember it was actually with the, I mean, I had a VIC 20 briefly, but which Lin has also had, and it went somewhere with him and never did with me, but the, but I remember when I saw the Osborne, the Osborne looked affordable and I thought, Oh my God, I have that, you know, it's like, it's a.

You take one look at it and you have to have it. I mean, one reason that we're using iPhones today in this household is my wife took one look at the original iPhone and said, I can work with that. Yeah. You know, I mean a funny thing about her is, is it. She, when she was in the third grade, I think she was second or third grade, she's at this Catholic school and she said, she remember looking at the nun and pointing at the nun with her, with her pencil and her head saying to herself, kids like seven years old, I can work with this.

That's her mind, right? That's great. I, I, I came to that at about age 30, you know. But Yeah. Yeah. Yeah. But that's, that's, that's what we need. I mean, I think that's, that's one reason I think we may need the box. We may need the box that is a Linux box that's independent of, of Apple and Microsoft and everybody else that's full of GPUs or whatever else it needs that you could suddenly throw a bunch of data in and have fun with it and do cool stuff that's AI ish.

But probably, I mean, with, I mean, just put another card in your desktop, I suppose, if you have, have one of those where you still have back planes in some worlds, you know, if you have that, you can do that. But it's, we, we, we need some things, I think, that will spark imagination and, you know, toward what we can do here.

You know, everything

Jonathan: you've, you've talked about, it, it kind of, it strikes me as really the problem we're talking about is search indexing. But for our stuff, not for the internet. And in some cases, this is indexing physical things. In some cases, it's indexing digital things. It almost seems like the big problem that we're trying to solve here is just a personalized index.

And I know, you know, like, even in Even Linux desktops like KDE. We've had three or four different file indexing tools, and they've all been terrible They've all caused problems, right? But like that's sort of what this boils down to is a really really good Indexing tool and then plug that into an AI somewhere which again is not much more than a good search engine and say hey I want to see my receipts that match this criteria.

You put it in natural language, very much, very much like how Google has worked for 20 years. Right, yeah,

Doc: no, the natural language, well understood at this point, having a sense of that. So, a couple thoughts about that. First, what Google did and if we go back to 1998 when you were two years old, I was 11.

Thank you very much. But I mean, back then the, the understanding of the web before Google came up with its index, and this is the Yahoo model,

but

the others came at it the same way

was

that this is, It's a Linux, this is a Unix directory, right? And it has directory paths and it's, it's all files and paths.

That's what the web is. It's all files on paths. That's what a universal resource locator is that I'm going to locate that. It's in a place. It's in a, it's a file on a computer somewhere. And I'm going to catalog it. That was the original idea. We're going to catalog this, and that's where Yahoo came from.

We're going to catalog it. They hired people to like basically look at the web as a, as a library, and what Google did instead was saying, we are going to look at all of this as unstructured. We're going to, we're just going to, we're going to, we're going to, we're going to make our own catalog, but it's not, A card catalog like the library, it is going to be this index of, of, of data that comes from these links, these locations, but we'll get you back to those locations by looking through this index.

So where I'm going with that is, I'm not sure if I take all of, I may be wrong about this, I'm just thinking out loud. If I take all of my, you know, health travel work. contacts calendar, schedule, property and look at it like, or have a, an AI or whatever feeds the ai, whatever the base pile of data that le, that the AI is gonna look at.

Mm-hmm .

And look at it as, this is all unstructured actually. And I'll leave it up to the AI to figure out what's a photo and, and what's a bill. And know the difference or at least have enough association so it can recognize the difference. And work that out for me, in which case that's kind of like a search index.

But it might, but I'm thinking there might be some other breed here that's not either the catalog model. Or, meaning the, you know, the Unix path model, nor the pile of data index model that Google pioneered. It's something else, and I don't, I'm not technical enough to go to where that might be, but I suspect that unconstraining ourselves from those two models might be better than saying, let's just do it like, A search index, but there's probably ways of indexing and ways of cataloging and ways of making sense of data that I don't know when I'm making shit up right now, so.

Jonathan: You know, so I'm struck by this question. And of course. Google knows the answer or more more accurately a bunch of nerds on reddit know the answer and that is Can you can we even do this now with pictures? Could I? Upload all of my picture. No not upload Sorry, could I dump all of my pictures on a folder on my computer and then start something that runs?

Probably on my GPU locally that'll go through And tag, and give me a description of each of these. And ideally try to do some, some OCR and actually get data off of it. And there is at least one project that I'm immediately coming up with, it's LLMII. LLMII. It's the LLM index or no image indexer. And I will, oh, cool.

I will have to try this out because like, obviously there's more, there's more data here than just images. That's a, that in and of itself is a really good starting point. And yeah, and I'm curious, I, I really wonder whether we have. To, to, to do, let's, let's, again, let's just say just images. Do we have the pieces out there to be able to do this?

Do we already have the pieces out there to say index? All of these photos that I give you that may include scans of receipts that may include, you know, scans of bills, pictures I've taken with my phone, the pictures of my bookshelf here, my, my local L-L-M-I-I, my, my local LLM powered in, in image indexer.

Wow. That's hard to say. Mm-hmm . Take all this data, ingest it, and then is there another piece that may even be DeepSeq, you know, you could, because you can run the, like, like we said, you can run the DeepSeq, DeepSeq model locally, can you then connect the two, and be able to query the one, and let it use the pictures as part of its data set to look at, and it may be that those pieces are already out there, and there's just not yet a guide that somebody has written on how to make it happen.

Doc: I think so you're probably familiar with LM studio. Are you familiar with that when you had LM studios? Basically lets you run lots of different models just and I don't think it it runs on Linux, but it's not open source I don't think because the service but it's a way to say I want to run D I'm gonna run deep seek on this one.

I want to run this llama on that one. I want to you know, I got that kind of thing I'm sure what you're talking about exists in some ways. What we need is the listeners to the show, you know, to, to come up with the, the form of this that is user friendly, that's, that's muggle friendly. It's not just for wizards, it's for muggles.

Well, that's

Jonathan: always, that's always the challenge, right?

Doc: Yeah. Yeah.

Jonathan: I know. I mean, I, how many, I mean,

Doc: I've been, I was around this for, since 1996, okay. So. What is it, like 30, 29 years, okay, that you know, well, just, just open a shell and do these things, right? So. And 99. x percent of people aren't going to do that.

And just, so

Jonathan: just buy a Raspberry Pi and install this on it and then log into your router and forward ports and then go buy a DNS address and boom, you're running your own website and everybody else. You want me to do what's a raspberry? You want me to bake a Raspberry Pi?

Doc: Yeah, exactly. Exactly. Want me to close my windows?

How will I have to walk around the house? Yeah. But yeah, I mean, we, you know, we. We need, we need the invention that mothers that necessity and I'm sure most of the you know, I mean as I was saying earlier the the the reason you know that the resemblance between now and 1975 ends with the simple fact that What we didn't have in 1975 was the power of mainframes at all, you know, it wasn't available.

So we had to like go from the bottom up and build everything from stolen parts, as Wozniak did from his work at HP. And we're not there now. We can, you know, all the mainframe stuff is being, you know, going bleh out to us. Thank you, China, for DeepSea, you know, it's fantastic, you know, so, so we have so much more to work with there, but I think they're, you know, I think the, the main thing to realize is that we're going to have so much more market activity when we're done.

All the individuals are far more equipped than they are now to do things that they can't do now. And I mean, that's what happened with PCs. It's like, I mean, if, if you go back to like 1982 and asks an MIS director, because they called IT directors that then you know, ask your MIS director, could you mind if we bring some PCs into this company and say, no, no way, we have mainframes.

We have guys in white coats on raised floors. We can, we will do it our way. And then within a year or two, They're all running PCs all over the company because it turned out that the workers could do more with PCs than they could with the mainframe and it's There's we we need a similar moment here where and it's not just inside enterprises because in a way that's a bad example Is it I mean?

it's because Bob Frankston and and Dan Bricklin came up with spreadsheets so they could do math work, you know that business changed utterly because we had spreadsheets now, right and You know, there's there's You know, we need people Scratching personal itches to pull and basically to pull their lives together how do I how do I make a better sense out of my life than I'm making right now and And and we have to and once but we have to prove To The, the big makers of the world that we can do more with our data and data about us than they can.

We don't have that right now. I mean, the example you gave earlier about, well, geez, you know, I could dump all my photos into, into Google photos and I can query against that. I mean, it works the same way with Apple, you know, give me clouds or give me, you know, whatever. And they do facial recognition. You'd say, this is Joe and, and it'll say, here are all the photos with Joe.

You know, but again, it's in their system. It's using their, you know, their off world intelligence to, to make sense of that, where, but there's some kind of breakthrough we need on our side that It isn't so much that it proves it to the world, it proves it to ourselves, and then we generalize from there.

You know, I just think there's so much that happens starting with individuals that can be generalized rather than starting with corporations that could be individualized.

Jonathan: Most of the, most of the big breakthroughs and the world changing things have kind of worked both ways. Like they start, usually the very, very beginning is with individuals, where somebody has an idea, they make a, they make a proof of concept.

And then you, you get some company that sees it and turns it into a product. And so it kind of starts on one extreme and then it zips all the way over to the other extreme. Yeah, I know. And then the candle sort of burns from both ends. And you know, the next thing you know, everybody's got a computer on their desk.

Doc: Right, exactly, exactly. And they have to have it. I mean, it's, it's I mean, it's amazing to me that. Almost everybody is walking around with a 500 or more phone in their pockets, right? And but they're, they're extensions of ourselves, you know, we need them to extend ourselves. But then again, they're also tentacles of Google and Apple.

So that's another problem that's not as well recognized as it needs to be. I mean, you know, and Apple glosses it a bit by saying, we give you privacy except with us, you know, but that's in certain, certain ways that we're not fully explaining. And

Jonathan: Yeah. Fast. Fascinating stuff. I assume you, speaking of Apple, I assume you, you have watched the the, the UK snooping charter and its repercussions for Apple and all of that?

Yeah,

Doc: it, they did the wrong thing. I think that they should have, I think they should have told the uk No, we're not gonna do that. We're just not. And and seen what happened, but they didn't. I think

Jonathan: that's, I think that's kind of what they did, though.

Doc: Did they? I don't know. I haven't, I haven't followed it that closely.

I mean, I know that, I mean, didn't the UK, the UK wanted backdoors or something like that?

Jonathan: So, so the, the issue is iCloud backups and Apple rolled this feature out where you could have end to end, like actually truly 100 percent encrypted iCloud backups. So when, you know, you took a picture on your phone, it got encrypted on your phone.

It got sent to the iCloud server, still encrypted, and Apple doesn't have the encryption key to decrypt it. It's only on your phone. Right. And so this was a new feature that they rolled out. They had a fancy name for it, like a extended encryption or extended security. I forget exactly what they called it.

And the UK said, that's a really nice feature you have there, but we're going to make you put a backdoor in it. We want to be able to decrypt these iCloud backups. And that was a couple of months ago, apparently that they, they notified them of that and Apple pushed back on it. And then the order got leaked, right?

Like this was a secret order. It got leaked. By Apple, obviously. And then Apple said, okay, in order to comply, because they are required under the law to comply with the order, we're just going to disable this feature. That's right. For UK users. And so, on one hand, yes, they did, like, decrease the security of UK users, but on the other hand, they didn't actually put the back door in, which You know?

Right. One of the, one of the important things to remember here is if you put a backdoor in your software, it's there for everybody. Right? Not just for your UK users. And the way the, the way the Snooper chart, snoopers charter, and the order was written you know, it, it did not even tell them. Make sure this is only for UK users.

No, no, no, the order said for everyone. And so apple is basically as far as I read the situation apple is taking the first step of If you're going to make us do that, we're just not going to do any business in the uk

Doc: Yeah. Yeah. And

Jonathan: that, you know, that's a, that's a pretty hard stance to take. And they're not there all the way, like they're taking just the smallest step in that direction that they can.

But that's, that's where this is inevitably leads. If the UK government does not back down Apple, apple has this option of saying, okay, fine. We don't have any brick and mortar stores. We don't sell any devices there. We don't have a, a Nexus in the uk and therefore we're not liable to follow any of your laws.

Doc: Yeah, except they have a lot of stores in the UK. Well, they

Jonathan: do at the moment, yeah.

Doc: Yeah, I don't think they'll I mean, it would be interesting if they pulled out I mean, um, Google pulled out of China at one point. Yeah. And it was a gigantic deal, because they didn't want to do what China wanted them to do.

This was a while back. I doubt, I doubt they would do that, but I don't know. That's an interesting question. I've I've, I've always been more fascinated and knowledgeable about the weird things that Apple does. You know, I mean, like, I don't know why they actually have this thing on their apps where it says you can ask the app not to track.

Why not tell it you're not going to track? Just prevent it. You know, just prevent it. Tell them. Tell, don't ask. Tell them. But they don't. They ask and they say, well, what does that mean? I mean, it means they don't have to Obey your request. It's a request. It's not a demand, you know, but they advertise it like, hey, look, I blew up these spies.

They all turned into vapor. No, you didn't. No, you asked them not to spy. They're still intact. You know, all those molecules go here, you know. It didn't make sense to me. You

Jonathan: think you, you think you dropped the Moab on them? No, no, you just put a sticky note on your door. That's all you just did. Exactly.

Exactly. Yeah.

Doc: Yeah. Yeah, it was, I dunno. So

Jonathan: the with the, with the backdoor thing one of the. He's actually a cryptographer, but I followed his thoughts on it. He was one of the guys that broke the story, I think, and wrote, you would ask me that now, wouldn't you? I'm sure I can. His name is, his name is he.

I don't remember. He's a, he's a professor and a cryptographer, but he, he had this idea that I thought, I don't know that it's going to happen, particularly not in our current, like polarized. Political climate, but it was a brilliant idea and that is We should just pass a law in the u. s That says that u. s companies are not allowed to add but add back doors at the requests of other governments

Doc: Yeah,

Jonathan: and that would that would pretty much take care of it.

And you know, whenever there was a Conflict in a case like this you would suddenly have the u. s government as a party to the conflict That would sort of change everything interesting thought

Doc: Having hung out in a lot of universities, I'm, I'm always struck how It's basically because they have law schools, you know that The answer is policy.

What is the question? Right? That's almost where they always come from. We we need laws here and regulations and I would rather have standards and practices and and And let the world take care of that, you know, not that we don't need laws. Obviously we need to be able to drive on the right and stop on red and stuff like that.

I'm not kind of full libertarian on all that stuff, but I, there's a, but I, I just see so much more opportunity where we're not starting with regulation. If we, I always like regulation to be the cart that follows the horse rather than the cart in front of the horse. Even I mean like right now with AI, I just think all AI regulation is just not even going to happen.

It's. You know, and now at least in the U. S. we're, you know, we have a, an administration that, that, I don't know, it's not worth, not worth going into, but but I mean, every, everybody I know who wants policy to happen is basically looking at their hands right now, it's like, I guess not for the next four years, you know, it's sort of, so, yes. Matthew Green. And I'm not saying I favor that, by the way. I don't have a political position. Yes.

Jonathan: Yes, I understand. Matthew, Matthew Green was the is the cryptographer. He's the, okay. Yeah. Yeah. And he's got a. Cryptographyengineering. com is his website and he's got thoughts on this and a bunch of other things.

I've, he's one of the, one of the voices that I follow. But yeah, he has the suggestion that we just need to pass a law in the United States that and here's the thing. Here's the thing that I really liked about this. Like if you could get that idea before the right people that's something that in theory should make sense to everybody, right?

We will not allow U. S. companies to add encryption backdoors at the behest of other governments. And that's specifically the way that he put it. And it's like, that seems like a, a, a win no matter which side of the aisle you're Yeah, I guess the company

Doc: can now say, well, we're a U. S. company. We can't do that.

Yeah. You know, and the U. S. has, has this law that we're operating, you know, we're registered in Delaware, Texas, wherever it is now. And yeah, that would, I mean, that makes sense. And I would hope that it would appeal to You know to both sides in Washington, but who knows? I mean, that's I've given up betting on any of that.

Jonathan: Indeed. It's kind of like horse racing, right? What's, what's the quick, to be able to win a small fortune doing it, what do you have to do? Well, you have to invest in a large, yes. Yes. That's how betting on all that works. Goodness. All right, Doc. I feel like we've I feel like we've covered this fairly well, sort of our,

Doc: well, it's, I should add, I mean, it's so early.

It's, I mean, that's part of my point with this is that we're early enough with personal AI that at least of the kind that I envision that that's on the PC model, it's personal computing model. The important fact about which is, or aspect of which is that it's yours. That's basically it. When it's personal, it's yours.

We're just completely early with that. We'll just, we'll see where it goes. Mm-hmm . Or we'll make it go where we'll see it goes that place a better thing.

Jonathan: That's, that's the part that intrigues me the most. That's why I wanted to have you talk to you about this, because we are, we're in the position now where those of us that are sort of the, well, the programmers, those that are researchers, that's those that are working on open source projects we're still kind of in the driver's seat on this thing.

In a way, in the direction that we want it to go for personal, because nobody, none of the big companies right now seem to be working on that aspect. I mean, sure, you've got, you know, OpenAI with ChatGPT. They've got this idea of, oh, well, as you talk to ChatGPT, it remembers your conversations, and therefore the AI becomes personal.

But that's not really what we're talking about.

Doc: Yeah, I mean, we outnumber them, whatever them are. That's also true. I mean, I'm reminded of what, Bill Joyce said at Sun Microsystems back when they were a thing because it was so fond of calling itself smart about everything, he said, most of the smart people in the world don't work here.

They work somewhere else or on their own. And there are a lot of them. There are only some of us. And that's, and that's sort of, I mean, to me, that was, it was always the most interesting thing about, about Linux and all the open source development is that there's just a load of people out there doing the whole thing.

Right. So, so. I mean, I mean, it's, I mean, even what you were saying earlier, well, isn't this already being done here or there or there? Go to Hugging Face. Look at all this stuff happening there. What a brilliant site that is just to have that list. It's massive. It's massive. And you know, so it's just. I mean, I think there's just a, there's a lot to play with right now.

You know, and as the models get better, you know, we can use them personally, we can use them locally. Thank you for your model. We'll just work with that. I, I just think it's really early in the whole thing, whatever that thing is.

Jonathan: Well, I am definitely going to look at the LLMII. I will actually reach out to these guys and see if they want to do an interview as well.

LLMII. Yeah, it's, it's to take your images and go through and index them, add tags to them, and you know, try to figure out what is in there. Do it on your own local machine, and that's I get

Doc: Luthier's Mercantile International, so but then if I had images no, I get stock images, and so, well, okay, well, I'll look it up.

Jonathan: I will add the I'll add the link to the show notes. It's on, it's on GitHub.

Doc: And yeah. But take a look at LM Studio too, because it's Yeah, I pulled that one up. They've

Jonathan: got they say that their, their models and their CLI are all open source. And then the, the GUI, the fancy looking thing that you actually run locally is not.

Right. Yeah. But yeah, that is, that is pretty

Doc: interesting as well. Yeah, I mean, I, I, I, I, somebody demonstrated that to me when I was in New York a couple months ago. And it was pretty remarkable. I said, well, I'll yank this one out, I'll put this one in, I'll yank that one out, I'll put this other one in, see what it says, you know, and have it, I'll have to use this one to ingest all this stuff and Pretty interesting.

Yeah, interesting.

Jonathan: Yeah, for sure. All right, is there anything, we kind of, we kind of talked about your plug for the whole, for the whole show, but is there anything else that you wanted to plug? Oh my gosh.

Doc: Well, I'll, I'll plug KWAI, K W A A I dot A I. It's an all volunteer thing. Yeah, A A I dot A I. They now have a new user interface where my face rotates among some others of people that are also unpaid volunteers, you know.

But you know, a fun thing is that it, it is, you know, that there are there are three significant organizations that have base their work on, at least to some degree, on stuff I've written. And they're one of them. Consumer Reports is to some degree with their future plans. And and Tim Berners Lee's Solid Project, you know, so, which Tim himself told me was inspired.

This book I wrote that was a worst seller except for the fact that he bought it, which is like, okay, I don't know if he bought it, but he had it. And You know, good, good for that. Yeah. So you know, I'm, and, and, and it doesn't mean I'm right about anything, by the way. It doesn't mean that I, I said some stuff.

Anybody can write a book. Yeah, exactly. Anybody can write a book, you know, just get an AI to write your book for you. So it sounds so generic, by the way, I've done all kinds of stuff with AI images. It's so interesting to me, just a quickie, quick party thought that. You know, six, eight months ago, being able to come up with an AI image for something that was so brilliant and fantastic.

And now it's so cliched. It's like, you see them and you know, that was done by an AI. Yes. And so that didn't take very long. No, no, it

Jonathan: didn't. So I'll, I'll get your final prediction then. What's, what's the next thing after AI? What's going to be the next flash in the pan? Are we going back to

Doc: cryptocurrency or?

No, I mean it's, I mean, I, I do think I'm I'm really scared of the strategic Bitcoin reserve that our current administration came up with, with help from Elon Musk. Not only because I worry about lose, the dollar losing. It's it's a reserve currency status. I think that would be a bad thing for the world And but I think it raises the possibility of that So and I say that based on nothing other than my own but I it's just like how is this not a good thing?

It might be not a good thing that way, but I don't know. As for what's coming. I mean

Well, I'll tell you one thing. We, we need, we need words other than AI, because it's not artificial. It is not intelligence. It's a collection of other capacities, and we anthropomorphize this stuff. We say, oh, it's trained and it learned. No, it didn't. We use those terms because they make sense to us, but that's not what actually happened.

And I, I sort of see come, in coming years, multiple Two, three, and four letter acronyms that, that mean these other things that these machines do, you know, and or non machines and software, whatever, you know but, but I don't know. I mean, I, I, I, I think actually one big thing I think will happen, and I just say it only because of motorized bicycles, is that there could be a lot more people traveling around on those, you know, I like playing with those.

I think it's a better way to get around in a city or even a town. They're pretty handy and they're, I think we just see a lot of change around that. It's not self driving cars that are going to change everything. I think it's going to be motorized, you know, motorized bicycles, but. Self driving cars, that's, if, I mean, go to San Francisco, holy crap, I mean, they're everywhere.

And it changes the way traffic works, I mean, it literally does, like, oh, these things obey the lights, okay, I mean, it's sort of like that.

Jonathan: Oh, that's funny. That's great. So I'm starting to see them here in, you know, basically the middle of nowhere, Oklahoma. We've got several. It used to, I remember taking a trip and going, wow, it's a Tesla.

And the guy I was with was like, I saw like five of those on my way here. That's the first one I've ever seen in person. And the other day I went to the doctor and there's a Cybertruck sitting there. I'm like, oh, cool. It's the That's one of

Doc: the 2, 000 that got sold? Yeah.

Jonathan: Not a whole lot of those out there yet.

Doc: But yeah, we'll see. Aaron Lawton. Wow, wow. Yeah, well, why not? You know, go play with it. Sure. I mean, I, I'm a, I mean, Tesla is going from new hat to old hat rather quickly. And and it hasn't I mean, I think in a certain way it could end up being like the Volkswagen. Every Volkswagen bug sold between like 1952 and 1970 was the same.

I mean, it looked the same. It changed a lot on the inside. But but they were basically one design. They just kind of kept going like that. Yeah. Okay. Tesla has a good It is in a good position, I think, to normalize the way electric cars work. But I don't know. I don't, I have a hard time figuring it out.

Figuring, figuring out, I just think that there's a weird a weird a weird moment in time with that company.

Jonathan: Yes. If we, if we could really actually read those tea leaves successfully, we would, we would be millionaires from stock market trading and all of that stuff. So I know it's like,

Doc: I mean, if, if buying Bitcoin had been easier for me way back when I thought of doing it, it's like.

Yes. How many of us think the same thing? Right? Oh my

Jonathan: god. I, I, I distinctly remember thinking, oh man, I wish I had a couple hundred extra bucks so I could buy some of these bitcoins. I

Doc: know. Right. Yeah. And I, and there are people we know. I mean, john, our producer on Twitter in the past, he had a whole bunch of Bitcoin, doesn't know where it is.

Oh. You know, and I know other people who say the same thing, well, I, I have it. I think I did a Xerox copy of the

key or something like that,

but I don't know where that is. Okay. Yep. Yep. Yep.

Jonathan: All right. Last two questions I'm going to ask you before I let you go. And that is, what is your favorite text editor and scripting language?

Doc: Oh boy. All Oh, I guess, I mean, it is, this is, it's funny because I was thinking today, I really need a text editor for this one and I'm not sure. I mean, I, you know, back in the latest journal, I use VI. So there was that, you know, and But for scripting, nothing. I mean, I don't do any of it, so it's like, it doesn't, it, it, it's, it, it's sort of like, you know, what's, what are your favorite skis?

Well, I don't ski anymore, so I don't know. It's like, been a long time. Yep, yep, I understand that. My favorite is whatever somebody else uses for me. I'm at that stage. Yep, there you go. All right. Hey,

Jonathan: thank you for being here. Appreciate you coming in at the last minute. Thank you too.

Doc: I miss this thing. It's always a fun thing to do.

Oh yeah, yeah. I'm glad you've kept it going.

Jonathan: I am too, and I'm, you know, I'm super glad that I've gotten you, and even Randall, in the rotation of co hosts. That's great you brought Randall back. Yeah, we've had a lot of fun with that. We've had a lot of fun with both of you.

Doc: The old hand at this. Both of you guys

Jonathan: have been a lot of fun to have back in, so we will definitely do it again.

Maybe we'll have both of you on the same show at some point. That would be interesting.

Doc: Oh, that'd be interesting. That's never happened. We've, we've hung out, we hung out on boats together a lot, a thousand years ago, when he was on every cruise that ever was. Yeah. I'd love to talk to him about that actually, like, what was it about cruises for you?

Jonathan: Maybe, maybe for the thousandth show or the 1024th show we'll have both you guys on. That'll be fun. Oh,

Doc: that'd be great.

Jonathan: Yeah, that'd be great. Let's do it. All right. Thank you, man. We'll see you next time. Thanks. Yeah. All right. If you want to find more of my stuff, there is, of course, Hackaday. It's where the security column goes live every Friday morning.

And we appreciate Hackaday being the new home of, not new, not so new anymore, but the home of Floss Weekly. I've also got that other show, the Untitled Linux Show, that's still over at Twit. Have a lot of fun there if you want to find that one. And we appreciate everybody that's here. to catch us live and those that get us on the download and we will see you next week on Floss Weekly.