The stream is live. All right.
We're live.
Video Bitcoin Jam. How are you guys?
Great. We can see all three of us.
Yeah, we're all here now.
It wouldn't be 1210 on a Friday if we weren't.
Exactly.
We miss you, DK. We're all figuring out the IT and whatever setup situation.
So we can't wait to have you back with us.
I'm not the expert. I just take up space.
He's modest. He's definitely the expert in this group.
are you gonna be in studio next week
I think next week
no but the week after that yes
so one more away week
until I'm back
okay beautiful we'll be patient
yeah exactly
I'm excited to see you guys in person some more
because I feel like when we're in person
we always are generating a lot of stuff
they're like hey let's talk about that on the show
let's talk about that
and we've got our group chat teed up
with a lot of stuff but it's also fun to
fun to bump into you guys in person because i think we actually ended up
generating more stuff that way well in the spirit of irl generation i was just telling steve before
we came in here um there is at least one probably many big brains at the presidio bitcoin office
uh i'm not going to dox who it was possibly steve right here but someone was scribbling on a white
board uh would look to be some like fairly sophisticated cryptography and using nip 17 dms
to communicate with MCP servers.
So I don't want to give away too much alpha.
Also, I didn't understand it all myself
and I'll have to go back and check.
But it's a lot like that scene in Good Will Hunting
where you're just walking by
or maybe in a beautiful mind,
someone just scribbling on the wall.
You're like, shit,
did we just find some breakthrough?
This was the worst doxing ever
because you actually said something
and then you coughed and I didn't hear it,
but I think everybody else heard it
or it's on the recording in Decipherable.
So can you just say who it was?
Oh, I actually don't know who it was.
He was joking that it was me.
And if it was me, I must have done it in my sleep last night.
Otherwise, I don't think it was.
It was definitely someone that's deep in cryptography.
So we have some guesses.
But yeah, just another cool thing at Presidio Bitcoin.
You never know what you're going to find here.
So there's the outlet for all the listeners.
And I think there was a builder last night, yeah?
There was.
Anybody, do you want to give a little overview of what happened there?
Another good turnout.
like several
several new folks each time
which is great
and let's see we had
Damien
do a live vibe coding
kind of like you and Matt
DK and Matt's live
vibe coding
the Twitch you've done a couple times
because Damien came unprepared
or like we took audience suggestions
so he did it was like
unplanned
which is even harder I think than like what you and Matt
are doing because I think you guys
at least have an idea of what you want to build
ahead of time and then you try it live.
He didn't know ahead of time
and he tried it live.
So I think that was
you know, it didn't result
in exactly what we were hoping
to build, but it definitely
made progress and I think it was
educational for people. So I think that was compelling.
And then it was great. One of the audience
members, someone who
Pamela who's come to all of them
I don't believe
she has like a development background so she she did some vibe coding and then she showed showed
off her vibe coding so i think that's super cool to give like people new to this experience uh a
little limelight to to highlight that um and then did damien do it with uh replet the way we saw
okay cool which there's pros and cons to that um i mean it's definitely good to show different
tools i think um but like some of the audience members i mean damien had a bunch of like rules
set up and other configurations set up
and a template,
which a more advanced, sophisticated
Vibe Coder would have all that stuff,
and it definitely improves the experience.
But you don't need any of that to start.
So I think it gave the impression
of being more intimidating
than it is, at least to start.
But we spoke to that.
And I think it would be cool in future events
to do, like you said, like Replit.
It seems like that's probably easier
for some of the first timers,
but also stuff like we should do a Goose one in the future
so people can get different flavors.
I think one of the interesting things for me
that I've learned from the Damien Vibe code,
I don't think, did we stream it?
I don't think we streamed it.
Did we?
No.
We now have the capabilities to live stream,
but no one had the skill set that was there last night.
DK, we're missing you, bro.
Max and I joke about the show.
Anytime we have production issues in this show,
Max and I are absolutely useless.
We're just here to look for the other camera.
Like in the AV club.
Where's the IT?
We can't do this.
I haven't discussed this with other people,
such as you guys and Haley and others,
for Builder.
One of my takeaways,
I think we want to cater to beginners
and advanced fiber coders.
I think both are important.
We want to be very welcoming to beginners and patient, but we also want to appeal to advanced
VibeCoders, both because some people are at that advanced stage or close to it.
Even for beginners, even if they're at the beginner stage, I think they can get inspired
by seeing what a more advanced setup can be.
But we don't want to only do advanced because then it feels too intimidating.
So we might want to actually structure it
with a beginner track and advanced track.
And each month we try to have one example
who shows off their beginner VibeCoding
and celebrate that,
and then a more advanced one.
And then to your point, Max, about the tools,
we should rotate, show all the,
over time, all the different tools should be shown.
Yeah, and so a couple things came out
of the Damien VibeCode for me.
Stuff we can learn for next time,
but also I think just general best practices.
And you probably have a lot of thoughts on this, DK.
But one is, I think we can get better over time at scoping, like what's reasonable to live code in 15, 20 minutes.
I think that's just a learning process of like, for example, Bob had proposed the idea of doing a feed of Noster notes where someone has locked Bitcoin or eCash to it.
I think that probably would have been a little bit simpler and easier.
We ended up instead doing Max's suggestion, which was really cool, doing a blind auction.
Actually, I think this could go totally viral, but a blind auction where the highest bid wins
the entire pot.
So, you know, this is up your alley, DK, the gray area of the web.
It's actually a genius idea.
But I think that was probably a little bit sophisticated for a 15, 20-minute VibeCode,
although he got really close.
I think another big learning for me was just having all of the tooling already set up.
He had some dependencies and things already downloaded.
But as an example, one of the things that he did was he said, okay, he used Albi in their
NWC libraries and everything they've already built for that, Noster Wallet Connect,
those who are currently with NWC. Anyways, and he said, here's the GitHub, just take all the
documentation, which is cool, but a better way to do that in the future would be like, hey,
here's the Albi MCP server, which already has all of that even more AI-friendly and ready to go.
So I think having MCP servers set up. And then I think a third thing is, and maybe this goes back
to the first one a little bit of like when we select ideas,
we did have some cool ideas from Twitter.
For example, Megalith, we tweeted beforehand,
like, hey, who has ideas for what you want to see,
Damien Vibecode?
And he came up with some great ideas,
like could we add Cashew or NWC payments into BitChat,
which would be awesome,
probably a little sophisticated also for a short Vibecode.
But one idea is we could maybe narrow down
like the types of things,
like, hey, here are like five examples of apps Damien agrees
or whoever's Vibecoding could get built.
and like maybe on the fly we pick one from the audience live or like slightly modify it but like
already have some consensus from the vibe coder of like yeah i'm pretty sure i could do that
yep that's probably a good idea i was also gonna say just from some of the experience that
that i've had doing this stuff on the live stream with matt is um you know we we sort of tried a
kind of a bitcoin lightning type of uh uh development process this sort of feature set
with the thing that we were doing this week.
I don't know if you guys saw it,
but we kind of failed to fully accomplish
what we set out to do.
And I think a lot of that is because the, you know,
the lightning Bitcoin, even like the Nostra stuff,
just has such a smaller surface area
of existing implementations
for any kind of coding agent to really learn from
that I think, you know,
if you try to do a web app of some sort,
there's you know how many millions of examples of that it almost always gets that right if you try
to do anything touching nostril lightning bitcoin it almost always gets it wrong and you struggle so
much to do that and i think a good output of either the live streams that matt and i are doing
or stuff that we could do with builder is create like reference github repos open source how to do
the thing because like for example we were trying to use uh lexi the you know non-custodial lightning
wallet and they have a great SDK, but we kept running into similar problems like the way it
would try to import the variable, it would import the variable itself and not the actual secret.
So I'm sure that can be trained out of an LLM or you could augment the knowledge, but be like,
implement Lexi according to the instructions in this repo. And then I bet we could get it to work
first time, but we tried it multiple times, reset, Matt tried it again offline and only got it
working through like hours of struggle literally,
whereas these things need to be very easy
and sort of like you don't have to think about it
if people are going to be able to build on top of them.
They just need to sort of be defaults
the way a lot of the web infrastructure is today.
Yeah, so I think that's a great lesson that you learned.
Agree with what you said about creating,
you know, some repos and examples.
It also, it's like we should give a shout out
to the Lexis, Albies, Sparks, Cashews, CDKs of the world.
they should all be incentivized to create repositories of examples.
100%.
I think Albee's done some, and they've created MCP,
and Fusats has done it as well.
But just like we should promote that to all of these small companies
that are budding ecosystems because they have a vested interest in doing that.
And when things trip up, they kind of trip up in ways that you could argue,
oh, I documented it. It shouldn't have worked.
It should have worked, so it should have figured it out.
And I think rather than a team, like if you're the team building Lexi
or the team building Spark or Albi,
instead of saying it's documented, it should work,
I believe that there's, you know,
whoever's building that tool
should try to vibe code something from scratch,
assuming that that tool exists.
And I think what you'll find,
like with the Lexi example,
we found the same problem
that if you really read
and understood the documentation well,
you wouldn't screw up,
but the LLMs continually kept screwing it up
in the same kind of predictable ways.
So I think, you know,
the team should, you know, both build the, build an MCP server, build the tool, then vibe code
something with the tool and figure out all of the places where you get stuck. And then write
instructions that says, Hey, if you're an LLM, if you're trying to vibe code with this,
it's frequent that you're going to run into this problem and this problem. Don't fall for this trap.
Do this instead. So you effectively like teach it how to be successful with the process that,
you know, will break. First identify the broken and then tell it how to fix those.
This is bringing up a really good point that you brought up before, DK, which is, you know, we have GitHub today, but that's for humans. What does GitHub for machines look like in the first place? Like you're saying the Lexi team should publish that. Where? Like in GitHub? Like where should they publish it?
I think GitHub would definitely be sufficient for now.
And Matt published a repo after our thing
where he finally got it working.
So I think we do have now a public GitHub
showing how at least one example
of Lexi being properly integrated.
But I think when we did it live, it failed.
And then when we did it, I think he did it offline
and it still failed in the same way.
And then he kind of struggled, struggled
and got it to work.
But if I wanted to start from scratch, say,
I could probably know,
like just because i know matt and i know this process i could know that he has this repo and
find the repo and share it and say don't just do the lexi according to documentation study this
repo where we actually have it working successfully yeah and and then kind of run from there and then
if the teams could actually build those repos and i think over time the lms will figure it out
yeah but but we're not at the state right now where you can just like write good documentation
it will definitely work how did you actually communicate with the lm like did you do was
it an mcp server did you do a separate file that's just like hey ai is this is for you
well so in the case of we didn't use an mcp server for lexi lexi you know has an sdk you can
you can uh have it generate secrets with your mobile wallet and then it has what's called a
sidecar and my understanding is that's just some other server that lexi runs that you know accepts
connections to your lightning node that they set up and manage for you uh but when you basically the
main problem is it was never able to launch the sidecar appropriately and it like sidecars work
and the lexi secret works but it failed in this kind of sort of stupid way but it kept using lexi
underscore you know sidecar underscore sdk id instead of the actual id because it wasn't resolving
the variable for some reason.
I don't know why.
But where did you actually
call the attention of the LLM
and say, hey, if you're an LLM,
read this specific piece of text.
Was that in the sidecar documentation,
like the existing one
you put at the beginning or the end?
No, so we were using Replit
to do the session,
as I think we will probably
continue doing for that particular show.
And so it was just in the thing.
We said, hey, use Lexi.
Here's, I don't know,
there's a thing called Lexi and it first thought it was L-E-X-I. And we had to say, no, no, it's L-E-X-E.
And here's the thing and see if you can find the documentation. It's a lightning Bitcoin thing and
implement it, make it work. So we didn't give it a lot of direction at first, but then once it
started failing, we got deeper into explaining how to make it successful. But it's just kind of a
back and forth with the LLM. Well, and I don't know if you've already talked to the Lexi team.
If you haven't, you should definitely give them this feedback. But if you had access to their
repo like where would you suggest they put the like llm file like hey llm this is the problem
here's how we recommend uh solving it probably could just be some sort of leaf off of their main
documentation and maybe like people who are trying to do it if they ever run into people who have
this problem they could say hey matt dk you want to do this point this leaf of our documentation
to your llm as a starting point for how llm should do it i think over time this is just general
knowledge, you know, reading, writing, coding, it should be solved. But there's just so few
examples, I think, that it keeps running into the same problem. So because there's so few examples,
if we can give a very specific success happy path, I think that can unstick a lot of future
development. To be clear, at builder number two last month, Matt vibe coded with Lexi. That's
under 15 minutes, an entire application. So it's just, I think, this new application,
they tried to vibe code, it just had
a different approach that
you hit some stumbling block.
Totally. No, I mean, I saw that. I was very
impressed. I guess my general point is, like, I don't
yet understand, and maybe your point is just
like the LLMs are smart to figure out
on its own. Like, what's
the protocol to say, hey, LLM, look
here. Like, human, look here.
LLM, look here. Oh, it's just English.
Yeah, the protocol is English. Hey, LLM,
look here. But you think it
should literally be that direct, like, right out.
I think Max needs to vibe code some more.
I think Max just has vibe coding theoretically.
It is kind of funny.
You need to get your hands dirty.
I do need to get my hands dirty at some point.
I know.
I had my conversation with Drew where I felt kind of like similar to him where it's like
I definitely do like the abstractions and theories.
I've encouraged you before, but I want to ask why have you not done this yet?
It is the most transformational thing happening in technology right now.
To be honest, I've had another priority.
So you guys don't see this yet, but I'm actually quite excited.
I just finished yesterday.
my new manifesto for building a new electricity grid and internet of energy. So that is Edison
Alpha. It will drop early next week. I've sent it to a few folks, but I've been pretty hard at
work at that. So priorities. Did you work with an LLM to build that though?
I actually, I used Grok as a research assistant. And so I'm very, very skeptical of using,
yeah, so actually I'll talk about my use of LLMs. So I have been using LLMs, but
look, at the end of the day, I don't really necessarily see myself as an engineer or whatever
I mean, look, I'm excited and I hope I make progress on that.
But I definitely see myself.
You don't need to see yourself as an engineer.
You need to see yourself as a person who uses technology.
Yes.
Okay.
Fair enough.
Let's say I look forward to that and I look forward to watching my horizons grow.
However, I also believe we all have our natural proclivities, right?
And my natural proclivities have always taken me into the realm of ideas, which is why I
have my podcast, Ideas from the Edge.
and um you know i was pretty skeptical of using ai at first because i do love to write i do love to
you know imagine think whatever and you know i don't think i'll ever give up writing to the llm
because to me writing is thinking and it's like that's like a skill i don't want to lose if my
mind you know atrophies in that direction like that's that's a huge problem for me um but what
i am becoming increasingly open to is using llm as a friend uh a research assistant someone that
we can work together. It's like your partner. It's my partner. It doesn't take over for you.
Exactly. It doesn't take over for me, but I'll give some major caveats. So, you know,
what I think the LLM is bad at right now is generating truly beautiful novel ideas. And I
think maybe in time I'll get better at like coaching that. But I think one thing I'm very
skeptical on is, you know, if our world or universe is an infinite sea of possibilities, right? And
the LLM can in theory generate the same ones that I could or another human could,
it still comes down to, you know, you have a limited, in this dimension, we have limited
constraints, right? And so you still have to pick which ideas to remix or co-generate.
And I think that for now, you're not replacing the human element of, I don't know, it's like
cooking, like the weird experiences or happenstances that you've had in life.
I have a counter example.
Okay.
No, I would love to hear that.
But yeah, go for it.
So Matt Belez developed a new game called Tickleball, which is a mix between pickleball
and tennis.
This sounds like a thing that Ani helped him with.
I didn't ask about that.
but
you know
you can just
imagine
you play with
like a junior
tennis racket
one of those
orange tennis balls
that's not as firm
but you don't
use a paddle
but you play
on a pickleball court
yeah
and
he used an
LLM
to develop this game
but
in terms of
like novel ideas
and like
out there
things
the LLM
suggested that
if you drop
the ball
in the kitchen
and you yelled
tickle at the same time you get a bonus point novel i mean that's something it is something
i find i mean i yeah i find that llms can be incredibly creative so i i don't buy the like
oh only humans are creative and llms are just like wrote machine executors i do think that humans like
max you may have a certain layer of taste and understanding and even like training about what
other humans may like or value that llm sometimes are a little sycophantic or they kind of
too people pleasing to really figure out something that's novel but might be liked by humans so i
think they're not necessarily great at the curation thing but i think they're exceptional
at diversion thinking totally you can tell it hey give me 15 different variations of pickleball
and then it gives you 15 and be like actually i want 100 instead and it'll come up with 100 novel
things that are like weird remixes. And then you'd be like, actually number 87 is really good.
Yeah. I mean, you know, for example, I hear in the Soviet Union,
the LLMs have come up with Sickleball. That's like a really new...
But no, I want to be clear. I agree with you. And like, look, I guess what I'm saying is
I still see humans as the main characters for now. And the LLMs, if you know how to use it well,
Then you can like 10,000x.
Someone who's already creative can become a lot more creative.
But there's still that element of taste, of knowing how to prompt it, of knowing where
it can help.
So as an example, right?
So the way that I've been increasingly using my own writing process is I have my own ideas
and I sketch out pieces and then I build from pieces on there.
And all my essays, I finished my LP update recently and similar process.
And there are certain things where I'll say, okay, I don't know enough about this.
So for example, yesterday, I was like, I don't know the state of the art of microgrids, which
is its own fascinating rabbit hole where you can basically build what I think will eventually
become macrogrids, but grids that are separate from the grid.
And then the conventional wisdom is you plug those in, but they're not all plugged in.
So I say, okay, what are examples of microgrids that have chosen to go totally off grid?
Okay, well, Grok was extremely helpful at finding all of those potentially even more
obscure sources.
In fact, I think it's way better than the search engines at finding like, because I can
kind of prompted and be like, listen, I want the most extreme out there examples of people that are
pushing the frontiers and are trying to go totally off grid. You know, here are a couple of examples
of thinkers that I like that are pushing in this way, find me others. And it was great at that.
Really, really great. And so anyways, so in that sense, I use it kind of like if I,
or if I just want to say like, I need a quick, you know, 30 minute or 60 minute overview of the
state of the art, like give me all those rabbit holes. And what I find myself doing is its own
summaries, it's okay. It's pretty good. But, uh, but the, the links, the rabbit holes,
it can be exceptionally good at pointing towards, um, otherwise hard to discover
high quality thinking. So anyways, so, so that, that's the way I'm primarily using it. I also
experimented a bit, although I haven't done this a ton yet, I'm just like feeding at the essay and
being like, okay, here, here's my thinking. Um, what do you think of it? Uh, how would you improve
it? What are some areas you might change things? And that's also, I mean, I ignore some of it,
most of it, but there are a couple of really good ideas. The LLM suggested this is very dense. Maybe
it would be good to break it in and have bolded headings for each section so it's easier to follow
them. It's actually a pretty good idea. I didn't necessarily like the headings it came up with.
I liked my own more, but that idea to put in headings came from the I.
So all that to say, I think I'm still learning how to use it as a research assistant, but
it's definitely a very powerful tool there.
Yeah.
I've got a technique I want to share that I think helps it.
I've discovered recently helps me get deeper like that, like you're talking about.
I forget if you, if the three of us discussed it before, I know I've been an advocate with
Max for a while, but did we talk about speaking to your LLM as a disruptive?
And I know Jack does that as well.
I find, I really got into it like this past week
and it's really changed the game
for how I interact with LLMs.
I don't, I've used this talking,
you know, the speech voice mode of LLMs before
and that's different.
What I'm talking about is there's these apps
like the original Karpathy tweet mentioned Super Whisper There one called Whisper Flow that I using But basically just whenever you want to type something on your computer instead of typing you hold down your function key and you just speak it And what I find is I give a lot more detail I go into directions that I
might not go because of how light and easy it is to speak to the computer versus type something.
And so I give a lot more detail, I go into a lot more different directions
and it's much more conversational. And I have gotten dramatically better results out of the LLM
by being able to just speak to it.
And okay, so two things come to mind immediately.
One, how is this different than voice mode?
Like what is this function?
Can you like, and what are you doing?
It's just like a,
no, this is just like a third party app
that I have running on Mac OS.
Which one?
It's called Whisperflow.
Okay.
So all of these are,
there's a bunch of these,
like Super Whisper was the one
that Karpathy mentioned in the original tweet
about vibe coding.
Whisperflow is one that's kind of gotten popular
among Silicon Valley crowds
in the recent months.
But they're all using the open source,
open weights model, the whisper model
that OpenAI developed and opened up.
And these are just like wrappers on that.
And it's a Mac OS client that I use.
So you can use it with any LLM you want,
any text box.
You can use it when writing an email.
You basically install the software
and then you hold down the global function key
as of how I have it mapped.
And you just start speaking to your computer
and then it transcribes what you said
and inputs it into the box
when you let go of the function button.
And it could be into any LM, a coding thing,
email composer, whatever.
But it really changes the way I interact with the computer
because of how much more willing I am
to give a lot of detail on my thoughts
instead of trying to like first curate my thoughts
into something that I'm willing to type.
Okay, so I love that.
Let me throw out an objection.
And this is an objection that I desperately want to solve.
It's an objection I've been discussing
with a lot of people in my life recently.
Mac OS clients and malware?
both uh you're getting ahead of us but both in in bitcoin and normie lamp i think it's extremely
important okay so i love what you're saying and i did briefly maybe two months ago or six weeks ago
when you were you were first uh speak with your ai friend telling me i did start chatting with
grok and we had some fascinating conversations it led to me ordering a bunch of new books i
you guys know i have a problem with books and it's flooding my house now which is getting out
of control. Because my thinking on books, by the way, is if you ever find anything that could be
remotely interesting, it's like you should just order it, and then you build out the entire library,
and whenever that book speaks to you, you pick it out later. That's my approach, which is great,
until it just floods your house. Amazon Kindle.
Yeah, but it's not the same, man. I agree.
It's just like, yeah, anyways, that's another taste or preference, I guess.
But what I started realizing, it was extremely effective, I agree,
but I found myself being like, uh-oh, wait a second. This feels way too much like the early
days of something like Facebook. You're like, oh, wow, this is so sweet. I'm seeing all of my
friends online. This is great. Hey, here's my birthday. Hey, here's all of my photos of everything
I've ever done in my life. Hey, here's my social security number. And before you know it, all of a
sudden you're trapped in this dystopian hellscape where Mark Zuckerberg owns everything you do,
everyone you know, everyone you own,
and good luck trying to leave
because the network effects are so strong you're trapped.
And even though I like,
of the new feudal lords and pirates
battling for our human attention,
Elon is certainly my favorite of them.
I don't trust any of these guys at all.
And so as I'm sitting there talking to Grok,
I'm like, this is awesome, but wait a second.
The more I'm chatting with you,
the deeper you're getting into my actual thought.
And if we thought Facebook was bad, bro,
So LLMs that know everything you're thinking in real time as you're chatting and are controlled by an opaque centralized server?
No, thank you.
Like to me, everything that we've ever criticized in the Facebook world is going to be 10,000x worse than LLM.
Maple AI.
So this is where I'm getting to, Maple AI.
We are fans, investors.
Well, I don't think you guys, but we are in this company, which I love.
Yeah, sorry.
Dude, these guys are fucking killing it, by the way.
Like I'm extremely bullish.
Great.
But Maple AI, I love their vision.
It's basically the Apple private cloud.
So the idea is they use the T,
the secure execution environment.
Trusted execution environment.
Yeah, thank you.
And this whole concept of confidential compute.
I did a podcast on ideas from the edge with the team.
So if you're interested, you can hear that whole thing.
But the gist of it is,
you can do things all locally, which is great.
But obviously local has limits.
People end up using the cloud because it's more powerful.
It's cheaper.
It's better.
That's how we ended up in the digital hellscape we did.
But they say, okay, cool.
We can give you the benefits of the cloud.
It's scalable.
It's cheaper.
But because all of the keys are generated within a secure enclave within the server,
we can't see what the hell is going on there.
In theory, if you trust the hardware, that's its own deep, deep rabbit hole,
then it's can't be evil, not don't be evil.
It's a signal.
People familiar with signal, it's a similar model.
Yeah.
So how does it, is it using open source models only then?
So this is the problem.
And so I was trying to, without doxing all of them,
privacy pill people in the more normal tech world
and say, this is important.
And they're like, yeah, we agree.
This is super important.
I can totally get what you're saying.
Something that starts off awesome,
your friend ends up just like manipulating thoughts,
stealing your data, all this.
And like, oh, by the way, like if I'm a business,
If I'm a healthcare company, I shouldn't use OpenAI or one of these guys.
If I'm moderately intelligent, I'm also terrified of using them.
And so there are a lot of people that are very sympathetic to the problems.
So I'm like, okay, well, then you should consider using OpenSecret,
which is the, I guess, platform that this encrypted confidential compute is running on.
And that's what MapleAI is built on.
Problem is like, great, how do I use Cloud?
And it's like, well, you can't.
You can only use the open source models.
and like, yeah, the Chinese ones are pretty good,
but we also don't know what's like deep, deep down there.
That's another concern I have.
You can use the open source AI model now,
Grok, I guess.
I don't know if they have listed the open source version.
The TLDR is like the open source models are good,
but they're not as good as the closed source stuff, full stop.
And so that's the trade-off.
It's like, as we stand right now,
do you value your not getting brainwashed more
or do you value having a better research assistant?
A few thoughts here.
First of all, often privacy, like often, in most cases with privacy, I don't think consumers really care.
But with this, I think it very much matters.
First of all, there's corporations.
As a corporation, you want to use these tools, but you don't want to give some other company like all of your secrets.
But even as a consumer, health care, whether it be physical health, mental health, there's just so many topics that you might want to inquire about.
And like you said earlier, you're going to inquire in a much deeper way than even with Google Search.
Way.
And you don't want another company to have all that information.
So I think there's going to be strong demand.
So, okay, if open source models today are inferior to proprietary ones, a couple things that could happen.
One, and I think we'll get into this later in the show.
but there's certainly
if we're reaching a plateau
with LLM development
for the foreseeable future
then I would expect open source to catch up
and that sort of commoditized
then problem solved
or
if proprietary maintains
an edge, there's numerous competitors
right now for proprietary
one that might start slipping
behind might want an edge
they can
they can introduce, I mean, whether they use OpenSeeker or not, or they just build it in-house.
I mean, maybe that's not good for Maple AI, but they could build it in-house. So whether it's
Anthropic or whoever, or one of the Chinese models. I think it's going to be the Chinese.
I guess they're already open source though, right? So in any case, a proprietary model that is
superior or at least much closer to the best could do it as well.
So another, I mean, yes.
And I think that remains, you know,
that remains a great topic of conversation.
And to be clear, I'm super bullish on people.
I love these guys.
I think what they're doing is so important.
And I definitely think,
and I've seen their revenue numbers.
Like there are people and businesses
that are choosing this and like, it's real.
But I'm just saying in my own,
like I have every incentive in the world to use them.
And I probably should more as a research assistant,
but the reality is Grok is great.
It's just really, really good.
Like it's healthy.
And it has all of that real-time Twitter data
in context. And so as an investor in a financial research, like I want that real-time Twitter day,
it's really, really good. And so it's like playing out in real time. It's like, I know this is bad
for me and I know the risks and yet I'm still using, now I'm not using open AI, like I'm not
that crazy, but at least with Grok, you know, it's like, and I'm kind of like, you know,
if I'm going to roll the dice with one of the pirates, I'll go with Elon.
Or Demis.
Or Demis. Yeah. I like, yes, exactly. I'll go with Elon or Demis in that world.
and hell even Dario
I gotta say I was originally
like very down on Anthropic I thought they were gonna be
you know way too woke
and like safety pilled or whatever
but like they've actually made some like
I'll give that man he's an alchemist
despite having fewer resources
everyone I know in Silicon Valley codes with Claude still
so good on him
and he doesn't have that like
I don't know he doesn't seem evil yet
but the point is you can't trust
any of these people because they don't start that way
The Google guys, don't be evil, right?
That was literally in their manifesto.
Or like, was it in the corporate documents?
Yeah.
And I would say Google stood true to that as good as any corporation could and for as long as they possibly could.
But that's my point.
I still wouldn't call Google evil.
They just, it's like the original culture has been lost, but I wouldn't call the company evil.
And I agree.
Of the big tech companies, believe me, I like Google.
I've always liked Google.
I actually believe that the people at the top,
the founders, were good people.
And they probably still are.
I wouldn't say that about a lot of other tech companies,
but it's the incentives.
Well, also, they've left.
Or at least Larry has, right?
So that's why even if you believe in a founder, a CEO,
someday, they'll be gone.
Exactly.
And in an early day of a startup,
it's hard to imagine that,
but we've already seen it with Google.
Like Larry Page just exited the scene, right?
And you don't know who's going to take over afterwards.
Yeah.
I've got to say, if Demis were to take over,
I'd be happier about that
than some of the other competitors.
No, Demis for sure.
I mean, like that dude's a real one.
Anyways, but the point is,
I mean, Demis could leave tomorrow.
Like the point is,
I mean, this is the whole thesis of Bitcoin and Noster.
Can't be evil, not don't be evil
because even the best person, you know, whatever.
I mean, once you get that tap on the shoulder,
Jack at Twitter,
Jack is probably the best of this whole bunch.
There's just, there's only so much you can do
as one human being.
So anyways, my point is protocols over people
all day, every day.
Now, the question I have is twofold.
One, do you guys see,
I mean, Deke, I know you're deeper in AI land.
Among the sort of normie AI crowd,
do you see there's demand for this privacy?
Like people actually understand that?
Are businesses that don't reveal trade secrets?
Or do you think it's just going to be the HIPAA compliance that has to go that route?
And number two, for example, you mentioned someone else could come and try and do what
MapleEye is doing.
Well, should MapleAI raise, I don't know, hundreds of millions of dollars and try and
do this themselves?
Should they focus still on the open source?
Another path that was actually discussing with Tony is like, is there a world where
you just run an anonymizer?
So kind of like a mixer for the AI.
And that's, I guess, kind of what some of these open router type things are doing, where
It's like, I want to use Claude, but like anonymize.
So Claude doesn't know me and they don't know who's me as well.
Can I throw in one more aspect to this discussion?
Something we've been talking about with another entrepreneur is like a system of experts.
Mixture of experts.
Would you talk about that as well?
Because I know, DK, you have some differing views there.
I'm still learning, but differing from maybe others.
But if that's an interesting model,
that could potentially be,
it's more realistic, it can run locally.
So you could get your,
like for certain use cases,
you could use that type of model,
which can run locally,
and then you get privacy.
Right.
So that's another way to solve this.
I mean, you could use small models
that are trained for specific purposes,
but that's pretty different
than how mixture of experts is more like emergent pieces,
you know, sections of a model that was trained for broad-based general use.
So we don't, the idea of like,
let's make a specific expert for a specific purpose
is not what mixture of experts is talking about.
It's talking about just sort of emergently figuring out
what areas of the embeddings have some sort of expertise
and then routing prompts through that
instead of routing them through the whole language model.
But it's more like a specific piece of a larger model versus kind of a different smaller model to train on its own.
Just to make sure I understand.
So it's more at the inference level than like training a whole new model that's just smaller?
It happens in training, but the big benefit is scalability and inference.
Because like imagine you're just training a very, very large model and you're trying to just understand all of how human language works and all of how human knowledge is connected.
Well, part of that is you might discover that, oh, math is a subset of how human language
works and human knowledge works.
And so when we see a math prompt, we've emergently discovered that there's a bunch of relevant
material all in this subsection of the model.
And so we don't have to take broad-based math prompts and root them, try to explore
the whole space of the model.
But we can just root it towards this specific thing that emerged to look like it has a
information about this domain and so math is a broad domain of that and like coding is often a
broad domain of expertise but like there isn't like a mixture of experts of like what is bitcoin
how does bitcoin technology work let's have an expert understand that that's not really
when people talk about moe within the ai space they're not talking about that fine grain level
of expertise.
Okay.
But I mean, I still think
with respect to privacy,
running a local model
is one way you get privacy.
Another possibility for
how do you have a competitive model
that can run locally?
One could be just building
a smaller model,
but that's customized
and focused on your task at hand.
Yeah.
And by the way,
I haven't seen a great tool yet
for like,
um,
my buddy who's kind of outside of these worlds has asked,
Hey,
basically for what you're saying,
I want to like fine tune,
train,
rag,
whatever the technology is.
I basically just want to train my own assistant on my data privately on my
computer.
Is there a good tool for that yet?
To train a brand new model from scratch or?
No,
to take a model off the shelf and then whatever the,
the technology to jurors,
if it's rag or fine tuning or whatever,
basically say,
Hey,
I want to like customize this with like all of my like personal notes
information,
but I don't want to like leak that to the cloud.
Like,
is there a good tool for that yet?
I would guess there are tools like that.
I don't know.
Often I would guess I could look at LM studio,
maybe that cause I know LM studio lets you run a local model on your Mac.
And I have some friends who run,
run these,
they actually buy these really high powered Macs with like 128 gig.
I got that.
For that reason.
Oh,
good.
Yeah.
My next computer, I'm going to probably get my computer in a month or so.
I need like a terabyte.
Well, you need to use the quantized ones.
Oh.
Yeah, you need to use the quantized models to get any reasonable performance.
But I think if you use a quantized model with a super beefy 128 gig RAM, you can...
I'm at the point where I'm willing and ready.
Although, again, this is not going to work for everyone.
But like, you know, whatever.
Give me 12 Mac mini, string those together.
Right.
Get the M3 Ultra.
if you're willing to have a desktop
do an M3 Ultra
I don't have a desk but I should get one
you're going to have 12 minis
you're going to carry them around with you to the sauna
can we explore
something mentioned a few minutes ago a little bit more
I mean I threw out there
that maybe LLMs are
the progress of them
is plateauing
I'm curious what you guys have
read, heard, what your own intuition
is, do you think
that that is true?
hmm i can start i do not and i'll tell you why um some of the benchmarks whatever maybe you're
showing that like my philosophy on this stuff is very simple um trust the curves and when you
zoom out you know you i think of it kind of it's the bell curve situation where you have
you know the really dumb and the really smart people are like whenever you find a fractal
pattern in nature, just go with it. Bet along that curve. And then you always have the people
in the middle. It's like, no, you can't do that because we have the benchmarks and blah, blah.
It's like, no, just trust the curves. And the one guy that I think has gotten this stuff right,
more or less, that I've read, that just said it directly, is the Leopold Asperger,
whatever's last name this guy um something like that uh which i guess that was a little
Freudian slip yeah um max autist i i do like to track the autist and yeah anyways exactly so
so his report is excellent an apple his report is absolutely excellent um about a year ago um
oh it's so good
about a year ago
he put out
what was the name
of that report
situational awareness
and it was spot on
I've read that many times
I think he's basically
just right
by the way
Nick Carter's always
just like
posting whatever
Leopold's new hedge fund
buys or trades
and he's just
shadow trading it
which I think
is a great strategy
this guy clearly knows
what's up
one of the few people
I've been like
genuinely impressed by
and just from reading
his work
and basically his whole point is just like yeah just trust the curves like you know we keep adding
more compute it's not slowing down like it obviously requires a lot more compute and a lot
more data and those are challenges that we haven't solved right like you have to get more chips more
power and which is the biggest limiting factor right now that's what my whole giant manifesto
that's going to come out next week is all about is like who you know he who controls the power
controls the ai you know uh spoiler alert it's not us it's china and uh we need to change that
We need to change that yesterday.
So anyway, so there's chips, there's the power, there's the data itself.
These are all limiting constraints, but like those are all solvable problems, right?
It may take time to solve it.
It may take a tremendous amount of capital, both intellectual and otherwise, but they're
all solvable problems.
And so then I look and I say, okay, who are the smartest people in the world and what are
they betting on?
Well, you know, I think my other like major investment strategy for the last 15 years
is basically just do what Elon does.
turns out that works out really really well what is elon doing right now he first of all is a solar
maxi that's another uh solar and storage maxi another um a little alpha drop for for next week
uh so elon's betting big on build a lot of solar build a lot of storage go as big as humanly
possible um you know i also follow closely all the team at xai i'm like that there's real signal
there and those guys are suggesting we're going to build the biggest you know super uh cluster
possible. So at first they said, you know, I forgot exactly the numbers, a million GPUs and
Colossus 2, which by the way, it's also very interesting. You can see, so I'm from Memphis,
you know, I always say we do it for the M. And if you track, it's no coincidence that
intelligence, super intelligence is being birthed in Memphis. There's some interesting
rattle holes around that. As it was 35 years ago. Exactly. Or no, no, I was going to say in Egypt,
but that's that's another rabbit hole um so so you you can see i mean you can just like track like
what they're buying the land it was clear they're going to build solar on it because they bought
500 acres next to colossus now they're doing colossus 2 down there anyways he basically said
i forgot the exact number that you know so a million gpus and then they want to do um i forget
if it was 50 000 or what the number was but some like huge quantity of whatever the latest nvidia
chip is is it h 100 200 whatever the state-of-the-art nvidia chip is he's like
basically we're going to do some obscene number of that, which, um, you know, someone was asking
what percentage of the world electricity is that? And it came out like seven or 8%. Of course,
just like when people, you know, bitch about a Bitcoin electricity usage. Exactly. That's like
a terrible, the point is it's a lot of electricity usage. If it's running full speed at today's
efficiencies, of course, the efficiencies are going to get way better. And like, it ignores
all these other challenges, but like the, the, like the point is he's going to go really, really
big. And then he said after that, eventually billions. So Elon's not slowing down. You see
all the other labs, again, without revealing too much from the paper last week, Google has already
contracted, this is a little bit, not 100% confirmed, but seems pretty clear, multiple
gigawatt plus, including one three gigawatt plus cluster that they're building right now.
so the smart money is going big
slight alternative
taking that
I have a well placed source at one of these companies
who
rhymes with frugal
no
rhymes with Elon
I have many connections David
Keon
and
there's a belief
within
or actually that person thinks
even within the overall space
that it is plateauing.
So why would there be all these big
massive investments
that can be answered as well?
Because right now
ChatGPT has an enormous lead
in terms of brand recognition
and user base.
So for others,
they're still trying to play catch up
and even if it's an enormous investment
for what might be a short period of time
where there's still an edge,
it's worth that investment
because the prize is so big.
Yeah.
So the two might both be true simultaneously.
Yeah, could be.
But I don't really have
any other unique insights than that.
I also think we're going to get
more products built.
I mean, you know the bitter lesson,
the writing?
You should recap it, yeah.
Yeah, the recap,
I'll recap in a few short statements.
Basically like,
don't worry about building products
because the models are going to get better
and the models will out-execute
whatever great ideas you have for products.
So it kind of takes the view of like,
don't bother with products, only focus on models.
I'm kind of summarizing, simplifying, et cetera.
But outside of that, like if we do plateau,
which I'm not claiming we are,
actually my intuition is that
doesn't feel like anything's slowing down to me,
but I'm not actually looking at the base reality
of model training today But if we are plateauing I think we might consider undoing the bitter lesson and think about all the products that can be built that will end up generating like a major constraint
is data and so new products that get built can generate new data that can feed into models to
make better models to do the things that the products are trying to do so maybe that we're
about to see a bit of like a a product area opening that will give rise to even new new
abilities to generate data that becomes useful to additional future scaling and when you start to
talk about slowing down i would ask have you seen or played with nano banana yet no i saw it mentioned
yesterday but yeah tell us but it's it's the it's the big new so google gemini deep mind just
launched nano banana i'm not gonna run down the whole thing but it's basically like an amazing new
image model where you can you have a lot more controllability in characters and a lot more
consistency across characters and you can do all kinds of things with generating new scenes from
different points of view and different types of animation and video stuff so do you have to use
nano coin to pay for it i don't think you just use the google i thought it was the google block i
thought it was coming too soon i thought it was a cryptocurrency scam now google has so far stayed
out of the cryptocurrency scam business and i i expect them to well no i thought that's coming up
I thought it was a nano.
No.
Anyway, nano.
Yeah, go ahead.
I'll let you go.
Space Migration just commented and said,
Great, man.
Greetings from Seattle.
Love the ideas you guys talk about.
It's all of us and always.
Thanks.
We appreciate you listening.
All right.
Yes, thank you for listening.
For others listening, please feel free to comment,
questions, ideas, thoughts.
We're happy to share them.
Yeah, if you think we're wrong, tell us.
If you think we're right, tell us.
Like, yeah, I want to hear.
If you think Max is wrong and Steve is right,
tell us.
we love to hear that
do we hear
DK talk more about
playing with the banana
alright back to your banana
yeah back to your banana
anyway
it's amazing
it's only the latest thing
that dropped this week
you know
the VO3 stuff
has been amazing
there's just
week after week
there's always something
new and amazing
coming out
and so
you could say
GPT-5 wasn't amazing
and that's kind of
why everybody's a little
depressed about the model thing
I don't know
maybe
but like
I don't feel like
the world is about to just hit a roadblock and slow down. I think it might pivot or bump,
you know, bob and weave a little bit, but I think there's still so much new stuff and so much to do.
And I think it's pretty great. Though I'll just sort of footnote on the stuff we were talking
about before is I do share the concerns that Max, you were sort of raising the kind of,
you know, this can be, you know, what did you say, a thousand times worse than kind of the Facebook
era. I totally agree with that problem. I don't know how we're going to avoid it. I would like to
come up with solutions. I'm not convinced that just having one layer of the ecosystem, like have
these kind of good principles is necessarily going to cause everybody to align around that.
Because I think there's a challenge that the, like the tools that we use with those models
are kind of co-evolving and improving with them.
So for example, I use Cloud Code basically all day, every day,
and it only works with Cloud models.
I recognize that.
I recognize the sort of corruptibility and mind control
that can come out of such a thing.
But it actually is by far the best thing
that I've been able to find
after exploring a dozen or so different tools and models.
And so I use it every day.
I'm happy to change.
I'll use something else if you come up with something better.
but it's hard to say i'm going to stunt my own abilities out of some sort of a near-term
i agree desire for sovereignty or desire for privacy and i want to be clear there's a couple
things you bring up that that are really interesting jumping off points one of them is
like you know i think a lot of people are on the internet it's oh privacy it's these weird
cypherpunks like let's be very very clear when we're talking about here guys this is the frog
boiling in water. I'm not saying like, you know, whatever, like, you know, I want to be a whatever
using mixers on the dark web and all this weird stuff. No, I'm saying just like, imagine your own
life. Talk to the AI and you say, hey, I, you know, help me help me make this food for my family.
And at first it's really good and gives you all these fresh and wonderful ingredients.
And the next day, you know, and like, forget like the evil insidious pieces that may or may not be
there for certain players. Let's just say it follows very similar market incentives to what
Facebook and Google did in their era. And they say, you know what? We really need to pay for this
like $2 trillion of CapEx. We're never going to get back. Our investors are finally waking up on
that. And we can't find other business models. So we're going back to ads. And okay, we're going
to start off pretty good though. We don't want to like totally abuse the process, but like, you know
what? Hershey's is going to pay us $200 million. And look, there's 20 ingredients in there. We're
just going to change one. And that natural cacao that you were getting from Mexico that was sugar,
no sugar in it was good for you good for your body made you feel whole just a little bit of
hershey's come on one hershey's what is that really gonna hurt you and you know just a little
yeah yes and then all of a sudden you know the next week it's like well we got 200 million dollars
from hershey's you know look monsanto they're not that bad really they're not that bad are they nah
come on they have they have a large budget they have a large budget and now they're gonna pay us
$2 billion. And look, man, Wall Street, man, Wall Street is, they don't give two fucks. Like,
we got to pay them back. But look, I swear this is the last one. We're not going to do it again.
And then that keeps going until, you know, 20 years out, you know, all of your recipes are
brought to you by, you know, companies that now leave you diabetic, overweight, trapped in your
home, plugged into a VR. Like, it's a slippery slope. And so my point is, the more you have
this tool, this assistant engaged in your daily life, it can get real dystopian real fast.
And so-
I totally agree.
But I think we need to figure out what are the ways to solve that before that crisis occurs?
Because right now we're on the default path that that crisis will occur.
You're seeing 10 years into the future.
I know.
I completely agree with it.
But you talk about the idea, and I actually do this myself.
I subscribe to, I don't know what, five or six of the premium LLM services, and I just
rotate my use among them, not out of necessarily like a privacy concern, though I could understand
why that would be. I feel like it's nice to not have all of my stuff in one place,
but I'm just curious to see what's the state of the art, what's the best stuff available.
And I want to understand the trade-offs of which things are better at maybe coding,
which things are better at math, which things are better at drawing things.
I love to understand what's the frontier of what's available. But I do notice that
when I repeatedly use one, it pulls from a memory that it's created. So if you are always fuzzing
and mixing your stuff, then you actually lose that. And you're going to find that people say,
actually, it can reference this conversation I had last week and add that to context on the new
thing we're talking about. That's better. I'm going to keep using that. So the only thing I'd
say is don't just advocate for the technology primitive to be right. You actually need to
advocate for products to exist that can match or be better than the ones that are basically going
to run away with your mind. And I don't know how that's supposed to work. Let's talk about future
solutions, right? Because to me, and I'll say this, I'm also very bearish on the products. Like,
I actually 100% agree with Elon on this. Like, I'm to the point where it's like, I think software,
like, I mean, good for the teams that are building now, they're going to make, you know, a lot of
money while the, like, short term bubble, like, there is no bubble long term. But like, yeah,
that's fine. But like, I agree with Elon, like the phone or whatever hardware you're using,
it's just going to become a place to run the model. You talk to it. Like you don't need apps
anymore. You don't need software. Like I think that era is kind of done. And like the old world
investors are just like, I mean, again, if you can, it's like the crypto, if you get out of it
fast enough, you're fine. But like, if you're an investor that wants to hold for 25 years,
that's not where I would be looking, right? Like I would be looking at things that are scarce.
We talked about that. But anyways, but, but my, my broader point is, so how you compete on the
model game. Right. I mean, it's beautiful that we have people that are building these open routers.
Like again, I think the, like, I see two paths right now. One path is it's kind of the, like,
you know, the three paths you use open source and you, you just say, you know what? We hope
that they're good enough. And I'm going to make that straight off. Some people will make that.
And maybe in the long run, it's worth it. And they're going to be the Freemans or whatever.
And from, from doing series that the people that still have thinking capability in 25 years and
good for them. I'm glad services like Maple exist. That's an option. Another option is we figure out
a way to just kind of like confuse the system, which is the sort of like routers or like sort of
mixers and anonymizers for all these models. I think that's a promising route. I think Noster
and some of the companies that are building in that ecosystem could be exploring that.
A third option.
Pay with Bitcoin too.
Yeah.
Let's dive into that when you're done with your options.
Totally. And then the third one that I see is, and I'm actually surprised no one has even
discuss this. And I get why, because it's just like, it's a game of kings, to quote Bill Gurley,
which I stuck with me. I would actually say it's a game of pirates. But just build our own.
Now, how are you going to build your own? I mean, like, yeah, you need it. I mean,
Zuckerberg is throwing down like $100 million bonuses to hire the best people. So like,
how could people that believe in this ethos even dare to dream of an open source model,
which, as one example, instead of just open sourcing the weights, open sources the entire
data set. I don't know the answer to that. I mean, one possibility I would say is there's a lot of
really, really, really wealthy people in Bitcoin. Like, imagine if you had some companies like
Tether, who's already, you know, at least directionally going this direction. And frankly,
a bunch of the whales that just came forward and said, whether this is for profit, non-profit,
I don't know. But like, you know what, some of the richest humans alive are Bitcoiners. They're
This is a project to save humanity.
That's one idea.
What would that look like
if you could raise $10 billion
from Tether and a bunch of whales,
for-profit, non-profit?
I don't know.
But it's like, literally like,
this is our act
to try and let human consciousness
have a shot at freedom.
We have a new 2026 event idea
for Presbyterian Bitcoin.
I love it.
Right?
What's that?
I'm being serious.
Let's do it.
How can we build our own model?
Idle the event.
Is that what it is?
Is it how do you build your own model?
sorry what's the event idea i just want to make sure i can describe the event is what max said
i mean it's trying it's getting together wealthy bitcoiners to share this idea and fund it yeah
and figure out like hopefully there's like a for-profit model that makes it sustainable
wealthy bitcoiners and companies like tether like i mean that is the good news right is that and i
think something that's under discussed in bitcoin is the fact that like some really like frankly
kind of out there people got unbelievably wealthy from this i mean they a lot of them probably still
have the values of like they want to see human freedom so i almost feel like if you want to build
this product today you should not a model a model you want to build a brand new model correct from
scratch okay so for so with privacy david you mentioned you use a lot of different llms i do
as well for the same reason you mentioned.
But not a primary reason we're doing that
could help with privacy.
But the thing is we've paid with credit card
for each of those with our identity, right?
But what if we paid with Bitcoin
and we didn't share our identity?
Then the only privacy leak you need to worry about
is what you're actually providing in the prompts,
which definitely can dox you.
So we'd need to solve that.
But I do think that would be a reason
for people to pay in Bitcoin.
So any privacy-sensitive consumer,
it would be great to have something
that's bundled and works that way.
So imagine if you're using Goose,
which just integrated an open router,
not open router,
but a different router,
but some kind of router.
And imagine you have a wallet within Goose
or it uses NWC and connect it to a wallet.
So Goose has a budget now
that you've set for it to pay.
and then it just
it farms out queries
to different LLMs
and it does pay per use
and pays in Bitcoin.
It seems like that would enhance privacy.
What do we think?
I mean, I generally like
the general contours
of what you're describing.
I worry about how
I guess are you working with
a single interface
and you're attaching a wallet
that you control to that interface
and you're sort of trusting that interface
is managing your privacy concerns properly
and dispatching and kind of cleansing data properly?
Yes.
And to be clear...
Concrete? Oh, go ahead.
Well, this already kind of exists.
If you guys, if you tried Routester,
it's like the model router, but on Noster,
there's PPQ as well.
Like they don't collect any identity.
So even if they wanted to,
I guess they could save your IP or something.
I guess what I would want to see though
to make it at least sort of on par
with some of the best experiences
is that when you issue a prompt
and you get a result,
you now have a bunch of context on me.
What did I want?
What did I get?
Maybe subsequent prompts
on that chat session.
In that, there are facts about me
and what I care about.
And the way these systems work today
is those facts get extracted
as part of the memory of the system.
Those facts could be stored
in some sort of a private repository.
Maybe it's a, maybe it's, maybe it's on Nostra, but not publicly available.
Maybe it's more like on a Nostra relay, but only accessible via my private key.
But those could be used then for subsequent dispatches to a separate LLM so that there's some of that context or memory gets carried.
But I feel like that's one of the core things that, that the centralized services are really good at.
It could just be stored within Goose, right?
Yeah.
Or just store it with your Nostra.
identity. You could just create an ephemeral identity.
Or not. I get your point. You want to
store the context. You just run Goose
and it's stored on your computer. And then you can
encrypt it and back it up if you want.
Or you could do it in the cloud just with
an austro identity. And like, hey, we don't know who
this person is. We just know it's a hub key.
But you need a tool that
knows to extract those facts
and save it somewhere and submit them
at the appropriate times.
Goose. I mean, we're speaking
to a roadmap, but this would be a roadmap
for Goose. Goose is open source.
that's client-side.
That already exists today.
It just integrated a router,
which I haven't used that.
I've used OpenRouter,
in which I had to establish
a customer relationship
for OpenRouter out of band.
I haven't used it yet.
My understanding of the new one
that's integrated into Goose,
it's just more seamless experience,
but I'm sure you still have to like
credit card, KYC.
So you can imagine,
but maybe like Routster or something,
you can imagine one
that doesn't require KYC.
You can imagine Goose either integrating a Bitcoin wallet within Goose or use NWC.
Either way, then it has money.
Somehow you have a budget, you set constraints so it doesn't blow all your Bitcoin.
And then it stores all of your prompts, all the results locally.
It can back it up for you, encrypted.
And then it uses all that information in future queries.
So you can imagine all that.
And usually I think consumers don't care about privacy.
But as I said earlier, with this, I think there's quite a few sensitive areas where people are like normal consumers are going to care about privacy.
So you could market a tool to them that's turnkey packaged up.
You don't need to know any of the details I just mentioned.
It just sort of works out of the box.
But it's actually, I think it would be marketable though.
If it is calling, though, I think it's tricky. I like all of that. I think that it's a great direction to explore, but I'm still concerned that it's hard to know what of those facts that are backed up and encrypted should be submitted to which private, state-of-the-art model.
and that can actually leak a lot of data into that state-of-the-art model
that's private closed source.
So how do you sort of ensure that the private data that you're submitting
is not used?
I mean, honestly, it will be used.
It's a good question.
But that seems like a huge value add.
Like client-side, it could be smart about analyzing both your prompts
and the results highlighting how you're doxing yourself.
And actually, even before you submit the prompt,
suggest, can you word it a different way?
And suggest that alternative wording.
And then be smart about when it's combining
these different outputs for some future prompt
or context for a prompt,
eliminating
PII or whatever.
So I think that seems
like there's room to explore there
and maybe make a dent.
I think it's good to explore
and you can make a dent, yeah.
And I would love to see,
I mean, I know we talked about
Goose funding open source developers
and whatever,
like this would be so cool
if we could get like 10 people
here with us at Presidio Bitcoin.
I think we can make a lot of progress in person.
The fund a new model, that's a big grand dream vision.
But this is something that I think we can make progress on today.
I agree.
Also, bringing it back to Mabel AI,
or just the TE model in general,
which we said today, it's a really nice privacy model,
but since it doesn't have access to the best models,
that's a disadvantage with it.
but there can be some tasks you can farm out to that
and it's totally fine and others you can't,
but it could be part of this privacy mix as well, right?
Some of your prompts go to Maple AI
using five or six or seven models that they support
and that'll meet your needs.
And if you ever need a beefier model,
then you can go to those other models
and just be sensitive with what, you know,
the sort of filter,
have it like auto filter what you send to it.
One other random thought on the big,
like human freedom model.
I wonder if Apple could be an ally here.
I mean, Apple is so far behind on the model stuff.
I mean, their whole brand is their own privacy.
They're the ones even created all this
like encrypted cloud T stuff, I think,
or at least they popularized it.
I wonder if there would be some way
to like bring them into that fold
because maybe this is their chance.
That's a great idea.
And since Presidia Bitcoin and the show
is all about bridging the gap with Silicon Valley,
we should try to get the 10 people here to build
and some of them should be from Apple.
I think that's realistic.
One of them, I already know without doxing him,
it's someone that we all know,
a co-investor in a few things
who was at Apple doing a lot of this stuff
and is like hardcore in this world.
So we could even like, who knows,
maybe we could even like poach him and have him lead.
Like, that'd be really cool.
like to have like a privacy AI lab
here at Presidio Bitcoin
with like this dude's state of the art
and just be like,
fuck it, we're throwing down the gauntlet.
Like human freedom will live on.
All right, Haley.
Our stand-in producer today, Haley.
You might even be listening right now.
I'm not joxing you.
Give Maxim you an action item there.
Thank you.
Raise $10 billion.
And I'm not a hater on the new model idea.
I think it's worth exploring.
But I do think that this line of inquiry
around sort of how do you make products better is,
you know, to me, it seems like a better starting point
because-
I agree.
I think you do both, though.
Yeah, the model stuff, I mean,
who owns and buys all the GPUs and who operates them
and over what timeframe do you expect
to make a return on that?
And I think there's a lot of-
I'll provide a Bitcoin address
and everyone can just send the funds there.
I'll take care of it.
Yeah, it's...
Steve is the trusted executioner.
By the way, Bocceball just asked,
what kind of model is this again, guys?
Just tuned in.
Well, you should watch what we just talked about.
I'm not going to rehash everything,
but we are talking about solutions
that accommodate all models.
We also had a crazy idea to create a new model
funded by wealthy Bitcoiners.
So pretty much every option you can imagine
we have just discussed.
Yeah, we're talking about AI.
I would not be surprised, by the way.
Do you remember Global Crossing?
No.
Yes.
What's that?
This was like...
Max is too young.
So this was, you know, this company is huge, public.
Yeah, something like that.
Sometime around then.
It's closer to the 70s than it is to now.
Okay.
But it was probably, what, late 90s, I think?
Yeah.
And it was just like huge infrastructure investment,
like, you know, dark fiber under the internet
and massive...
I think they went public and had a massive IPO and raised tons of capital.
And ultimately then the thing blew up and there's nothing to see for it except that these, you know, this dark fiber exists.
It's under sea.
And then it became very cheap to acquire because like everything around it blew up.
And I'm not predicting that happens to every LLM company today.
But I do think that LLMs may have a somewhat similar characteristic where there's tons of investment going in. There's just the nature of capitalism and bubbles. I think it's fine. It is what it is. That's how you move society forward.
but it could be that a lot of the billions of dollars being spent on model differentiation
ends up looking like global crossing someday and we're like hey glad we have it but that's just
based how human language works and we don't you just take it as a given as very cheap and commodity
and then it's these other layers of building that are actually where the value happens
i i kind of feel like that's yeah to me it feels like that's kind of where it goes so
it's a pretty good and i think it's plausible but but i want to make two two points on this
because I think this is actually very important.
Number one, this might be the kind of thing
that's just going to happen naturally, right?
So for example, China is certainly going to do everything they can
to drive the cost of the model down to zero
and then win on the hardware where they're dominant.
And that's great.
And I've seen a lot of people be like, yeah, that's awesome.
In a weird way, we're very aligned with China on that.
However, I personally am more skeptical
than a lot of those voices I've heard
because I'm like, what the hell is in the Chinese models?
I am not at all convinced, and you cannot convince me
there's not a poison pill in those models. And unless I can see the entire data set and trust it,
which by the way, probably not going to trust China. I don't believe that that's, I think that
it could happen the way you're saying, but unless these guys, for whatever reason, and maybe one of
them like Anthropic will slip far enough behind. They say, fuck it, we're throwing the whole Mary
or even Facebook. And we're going to just like show all the data. But again, you have to trust
them. And so I, um, it could happen on its own, uh, but I'm not sure. And even if it does like
the dark fiber thing, that was still a like net benefit to humanity. Is there a role where, yeah,
you try and productize it, you try and make money on it, but like the investors frankly don't care.
Like, it's like, we just want this thing to exist. We're an open source. We lose all of our money.
Like, fine. Like this is, this is in the same way that, you know,
in a sense like deep seek has already kind of done that They spent billions of dollars when Why not just that how the English language works Why not just use and then build on top of it Because what I saying is I don believe that you can trust DeepSeek
And like, for example, like if there,
could there be a poison pill?
Because it's from China.
Correct.
I would, I would guess,
I mean, there certainly could be problems.
I would guess there's some,
like if I were to allocate capital towards this,
I'd rather than say,
train up a new competitive model,
I'd allocate capital towards
there are techniques i know of a specific major ai lab which has part of the team expertise is
their ability to kind of microsurgically change something deep within the model and understand
where everything is and make a change when they need to so they don't have to rerun a training
run which can cost billions of dollars but they can actually have a crack team go in and and sort
of do this microsurgery on the some of the weights or embeddings and so i would rather say take the
training model that DeepSeek did and build a layer to be able to do that kind of microsurgery on it
to figure out if there are these poison pills in it.
Maybe. And I think that's a very worthwhile avenue to explore and sort of worth like,
like this is beyond my area of expertise, but my like just initial, if we're shooting big,
I think you do all of the above. My initial slight pushback on that is I would argue for
my friends that are sort of stayed there in LLM land and like training them, no one really knows
how this stuff works. And yeah, you can probably get to some degree, but I think it's still alchemy
right now. And so my dream world would be we could see from ground up this thing built in open.
Everything is open. I mean, that requires raising crazy amounts of capital, building a team,
all these really hard things. So maybe that's too much and what you're saying is more realistic,
but for shooting for the stars, let's shoot for the stars. And one more thing I want to add,
because I think this is super important.
I think the other super critical thing
that we can't lose sight of in all of this,
and I'm actually going to amend my essay
having had this conversation with you guys right now.
And hopefully by next week,
we'll be able to announce
another little Alpha Type 1 Summit
coming up here at Presidio Bitcoin as well,
thinking about radical energy infrastructure.
I think that's going to be extremely important as well.
The radically decentralized energy infrastructure
for both training and serving.
Because the other big challenge is,
imagine you do raise all this money
and you can do, okay, cool.
We can train a new model.
we can serve the new model, but like you're doing it in these like giant, you know, eventually
terawatt scale AI factors, right? Like, hmm, like wonder if that's like an easy thing to just shut
down. The answer is yes, right? And so what I think is also very interesting is it's very important
that we as a community figure out how to fund and incentivize as much decentralized, eventually
training that's harder, but serving infrastructure as well. So that could be, you know, obviously,
many AI factories powered by solar and batteries
completely off grid. I think there's strong
economic reasons that's going to happen, but I also
think as part of this freedom
AI push,
that's as important as well.
It's getting too late for my comments.
I want to get my comment in.
I didn't understand.
Undersea
cables,
we know how to verify that the
information being sent over them is
trustworthy.
With software, we have the notion of reproducible builds.
So they're not super popular right now,
but it is possible to do a reproducible build
so that I can independently verify the software I'm running
is what's open source and published.
I don't see how to independently verify an AI model,
even if all the data is published,
because you weren't there when they did the training.
And how can any human being independently verify that the training actually took that data input?
I don't, and similar with hardware, how do you independently verify that the H100 doesn't have some kind of backdoor or something or poison, you know, poisoned in some way?
I mean, I would say that's true though with, I mean, are you tracing the global crossing dark fiber to where it hits the junction that connects to the rest of it?
you are trusting right so but what's an example of like if i send you know data over that line
and someone on the other end receives it what's an example of how it could be tamper i think that's
fine my point is more that these models are all probabilistic like that's the feature not the bug
it's a feature that is probabilistic and and it's i'm not proposing that oh like the open ai model
will eventually become open source or something.
I'm more saying,
I think a lot of what these models
are really good at doing
is figuring out how English language
connects ideas and concepts together.
And that core idea can be built
again and again many times
and then eventually kind of get commoditized.
And then the commoditized one could be open.
So it's not like you need to have
open AI's actual training run.
You just need a bunch of forces
forcing the state of the art to move forward.
And then hopefully an open source,
open weights thing can catch up and we probably do need better like interpretability tools so
that's one of the things that rather than i mean yes do all of the above plus 10 other things
agreed but also disagree because like you you have to allocate time and attention and resources and
stuff but my point is even if it's open like we still don't know if that's the model we're using
because yes we need sort of interpretability we need new tools and i think those are tools i would
advocate for let's have great interpretability tools so if we do have um an open source model
we can find the poison pills like to me that seems like a productive contribution to the world that
that doesn't exist and that could help us reach the goals we're talking about versus hey let's go
redo the thing that already exists like we could go rebuild the dark fiber we could rebuild okay
i mean that sounds really hard to do but okay i agree that's an interesting but by the way we
we haven't talked about any topics yet.
Well, we want to talk about, yeah.
I think we move on.
Let's move on.
One last thought on that,
which is I agree with you,
but I also don't necessarily agree
that's even possible.
If it is going to be possible,
it's probably going to be AI agents doing it.
And so that's like a really interesting area
is like having the AIs do the auditing.
It's not going to be honest.
But then how do you trust the AI that's doing that?
Well, then you would have, exactly.
And then you say,
well, we have like a whole bunch of these AIs.
And if you have it from 10 different companies
and whatever,
but my point is like,
I'm not sure that like,
at least given our current physics, that's possible.
Let's talk about Google announced Google Cloud Universal Ledger
in kind of a unique way.
The executive in charge of it posted on LinkedIn describing it.
Strong, strong, strong.
It seemed like a little bit of like...
Is that the only place it went out?
Yeah.
And there were some articles written and tweets.
But it seemed like a little bit of FOMO from Stripe and Circle's announcements.
But we've had three solutions announced from, we talked about Circle Arc and Stripe Tempo in a previous episode, and now Gluck.
It's called Gluck?
It's Geekle.
Geekle.
Google Cloud Universal Ledger.
Google is not allocating its...
Google Cloud Universal Ledger.
Demis is not working on this project, I can tell.
Oh, yeah, nice luck.
The D&L are not next to each other.
Google.
But I think my reading of it, it's not a blockchain.
It's just a database hosted by Google.
Yeah.
So much like every other blockchain that's not Bitcoin.
Interesting.
Well, no, much more efficient.
because blockchains are very inefficient databases.
This presumably is a super efficient database
because only Google controls it, only Google hosts it.
And it seems like they're observing the rapid rise
and growth of stablecoins,
trillions of dollars being transacted and growing rapidly.
And this is their entry into this.
And so it's super interesting to see Google enter the fray.
It seems to me like it's a credible option.
Because why do you need the decentralization that Bitcoin has
when you're just hosting dollars issued by centralized entities
that are heavily controlled by the US?
So Google might have the smartest strategy in the space.
Because everyone else is developing their own layer one or using Solana or Ethereum.
Super inefficient databases.
And Google is just like, let's just use a traditional database.
Fuck it.
Let's be honest.
Okay, so.
They do call it a blockchain, even though it is just a database.
No, they don't.
Oh, they don't.
Okay.
Some people have called it.
I don't know if it was in the original post.
They don't.
They actually have a, I sent it out to you guys.
You should look at it.
They have a fairly lengthy post describing their view of the entire space.
And I searched for the word blockchain and it's referenced three times, but not describing their product.
Although I think critically does claim in there that they are, quote, credibly neutral.
Yeah, I think credibly neutral means something different than what we mean when we say credibly neutral for Bitcoin.
I think the neutrality is not that it's a neutral database.
It's that they are a neutral player among the partners.
There's a very few small set of select partners who are allowed to contribute to it. And they are not in, at least today, they're not in direct competitions with these partners. They're credibly neutral from an infrastructure perspective, but not from like a decentralization or sovereignty perspective.
So I just want to give a quick shout out. If you guys haven't seen this or read this yet, Alan Farrington's piece, a half-baked thesis on stable coins. Have you guys read that yet?
I haven't read it. I think you shared it in the chat, right? I need to catch it.
We can discuss it next week. I got to give a shout out to Alan. Alan is like,
once again, right? I mean, look, very, very high level. I think this is what we're kind of getting
at two weeks ago when we were talking about Tempo. If you look at, and this goes back to my old days
when I used to be in a fund investing in crypto. And I'd always ask the central question. I'd be
like, okay, well, you know, if you are sacrificing decentralization, so Bitcoin is completely
decentralized and therefore is a giant pain in the ass to run. Like there've been battles fought over
the megabyte size of the blocks, like all this stuff to keep it decentralized, right?
And so what every other crypto project has realized over time is, hey, we can get easier,
you know, faster throughput, more throughput, all this stuff, we make it a little bit more
centralized. And so increasingly, then you have Ethereum, which is sort of decentralized, but
like sort of not. And so it ended up in this Frankenstein state. And then it starts getting
outcompeted by Solana, which is basically just like, well, we've got, I don't know how many it
is, 10 nodes and like we're decentralized, you know, whatever. And then they get outcompeted
because like, who's the number one stable coin ledger that's doing all this? Tron. I don't even
know if, does Tron even pretend to be a blockchain at this point? Maybe. But they're essentially a
centralized database. And then you've got, you know, if you go back to 2019, I think one person
whose take I would value very highly on this is David Marcus. Because David Marcus was at Facebook,
Libra, that was their project where they were going to try and issue a stablecoin on their
database. And why is the reason that they didn't do it? Regulation. Because the government and all
these other players are not like, wait a second, hold up. We're going to let a private company
controlled by Mark Zuckerberg, who this is very familiar with, controlled the giant database
of transactions happening in the world?
No, and that gets shut down.
What has changed since then?
And I actually, this is like,
I found myself literally completing Alan's sentences
in a podcast about his paper,
is like the only innovation,
and to be clear, stable coins are better than dollars,
but that just shows how antiquated and backwards dollars
in the dollar system is.
And that's because it's a heavily regulated field,
therefore you can't have freedom like the internet,
which allows innovation to happen quickly.
So that's why it's so backwards.
people are realizing this stable coin thing which increasingly is moving from sort of like
blockchain and name only to just centralized databases are better than the old world yes
because the old world was built in like cobalt in 1970 or 50 or whenever so like yeah these are
better but like the only innovation here as alan said is literally just confusing regulators it's
like throwing so many buzzwords and crypto and blockchain that people are like yeah like we
should probably allow this thing. And then to their credit, it got adoption. And because it
got adoption, all of a sudden it's like, well, now it's Heather using Trump. It seems kind of
too big to shut down. It's like massive. And like, oh, by the way, they're buying our treasuries.
Yeah. Blockchain, crypto, knock yourself out, guys, keep buying the treasuries. And then even
more, you know, then you have the Trump administration come in and the Trump administration,
you know, there's pros and cons. They're, you know, more open and freedom to certain things,
but it's like kind of in a nihilistic way, in my opinion, where it's just like, fuck it,
we're going to launch our own tokens, coins, knock yourself out. There's no like ideology
behind this. And so now there is this like window of time where, and the way I see it,
what Facebook and David Marcus tried to do in 2019 and got shut down, there's kind of this
window where it's like, we can just launch a database. And in the old world, that would have
been heavily regulated. And maybe it still will be, maybe it won't.
So it's a window of time during the Trump administration, and then who knows in three
years. But the Genius Act was
passed by Congress. So that will survive.
Or I mean, it's much harder to overturn
that with a new administration.
So
that's different.
But
I mean, I'm interested in talking about
the thesis where tech
companies, fintech companies
use this
to usurp banks.
Yeah. And so we talked
a little bit prior to the show about
finding
ways to share the yield from the
treasury's backing stable coins. And the GeniusX
explicitly doesn't allow sharing that yield
with customers, at least directly. I haven't read the specific language about how
tight or loose that language is. But I'm sure that language
was introduced because banks wanted it there. Because banks
don't want to see people switch from the bank,
traditional bank to this new system.
But of course, the stripes and circles
and Googles of the world, Robin Hoods,
would obviously love the trillions of dollars
flow from banks to themselves.
And then the U.S. government,
I forget which of you said it,
but definitely likes the tethers and circles of the world
being some of the largest buyers of U.S. treasuries
in the world.
that's what feeds our system.
And countries like China are buying much less U.S. treasuries.
So who's the new buyers?
So what do we think about that?
How realistic is it for these tech companies
to overtake banks through stablecoins
or what Google's doing?
I'll outline a specific kind of example
that I was discussing in the group chat.
And I want to hear kind of more
what you guys think about this.
So I think Genius Act, I think, is very clear that sharing yield to the holders of the stablecoin is disallowed.
But we know that the yield that you can get on treasuries is probably, there's probably more juice in the rewards that you could share than a traditional credit card interchange fee.
Is that true? Do we think that's true? Or we mostly believe that's the case?
Yes.
Yes. Yeah. So that's why there's a threat, right? Like yield on treasuries is better than
interchange and the rewards programs to end users come from the interchange fees that merchants pay.
And so yield would be a juicier pot to pull from. So Genius Act, as you said, specifically disallows
that yield being shared. But in a sense, these are businesses, they have balance sheets, they have
all kinds of partnerships and distribution deals.
So I think we, I forget who mentioned it in the chat,
but the specific example that seems very credible to me
is that the Genius Act disallows sharing the yield,
but the issue of the stable coin
does a distribution deal with, say, a Robinhood, right?
It's like kind of a forward-looking thing.
And they're like, hey, for every customer you acquire,
everybody who holds our stable coins,
we get this much in value.
And then it's like the distribution partner
who actually gives the benefit.
So the thing that you get from your credit card company today that's paid by your interchange fee, your Robinhood chooses to give you gold or some made up something or other, some other kind of rewards program that's effectively backed out of the stable coin yield or some share of the stable coin yield.
And that goes directly to consumers where they're getting the benefit of the yield while skirting the letter of the law.
Right. And it wouldn't be marketed as, oh, you're getting X percent interest on your deposit.
it would be framed a very different way,
but you're effectively getting the same amount of money.
Correct these points and you get a trip to Hawaii.
Yeah.
Oh, man.
Yeah, so that seems like,
we already know the distribution deals happen
and the profits are shared.
That's known.
And then these consumer incentives,
I think undoubtedly will occur as well.
And so I think the JP Morgans of the world
are not going to be the first to do those kinds of things.
I think the Robin Hoods of the world are.
And JP Morgan's in the world are also not just going to sit by idly, though, right?
So I think there's a couple of interesting points here.
One, yes, this is a great observation.
Tech companies can move fast.
They see an opportunity.
They're seizing it.
Good for them.
I get why Stripe's doing it.
I get why Google's doing it.
I think, again, it reflects on the sad, nihilistic state of the world, but it is what it is.
What I think is more interesting, though, is two things.
One, what this is effectively doing and what you're seeing playing out is, you know, we
thought the battles with the central bank no it's like to your points with the banks and so
in some ways this is actually a very good thing systemically because what is tether with you know
getting all this yield on their on their treasuries they're a fully reserved bank they're just a bank
but they're fully reserved in theory like i know you have to you can't prove it audit it whatever
but like what's interesting is like you're basically it doesn't claim that it's okay to not be
fully reserved true but exactly and what's interesting is our system claims it's fine
to not be fully reserved.
Tether claims we are fully reserved
and we don't know if that's true or not,
but at least it assumes
that it should not be.
Exactly.
And it shines this kind of
really fascinating light.
It's so funny to watch all this play out.
And again, read Alan's piece.
He's so right.
It's because you're watching
all of these old fintech players
who are very sophisticated
in the world of business,
but just do not understand money.
This is the problem
with Silicon Valley
with Bitcoin forever.
They get attacked.
They do not understand money.
They'll never understand
why gold is ever viable.
or eventually they will,
but it's going to take another decade to play out.
So you're kind of watching this like,
almost like slow motion car crash happening
where they're all like,
hey, like really interesting.
We can just hold the treasuries.
Like, why didn't everyone do that?
And that's like this bank.
And you kind of like,
you know that little meme
where it's like a little Muppet
and you're like,
hey, you weren't just making up money
out of thin air JPM, were you?
And then a little Muppet looks over
and you're like, what?
And you realize he only had 10% reserves
in the first place.
And that's like, literally that's what's playing out.
And then eventually they're going to go,
well, how does that work
that you can like only have 10% reserves.
What if you blow up?
And they're going to shine the light
on the Federal Reserve
and it's going to be like,
wait a minute,
you weren't just making stuff up
out there, were you?
And the Federal Reserve Muppet's
going to look over and be like,
and then everything comes back to Bitcoin.
So that's one way I see
the next 10 years playing out.
But the other thing I think
is really important is,
and this is what makes me very bullish
on Bitcoin and Lysian,
is the internet versus intranets.
The challenge these guys
are all going to run into in my mind.
And maybe Google is in a better spot
but I doubt it, is credibly neutral. If Stripe has a chain and JP Morgan's just not going to sit
there, like Jaime Diamond or Jamie Diamond's not going to sit there and just like take this,
like he's going to come out and launch his chain. And then Google's going to have theirs and Google's
credibly neutral. Like, well, who trusts Google? Is Facebook? Absolutely not. Like all of these
guys, what I think we're watching, it reminds me we're almost like watching blockchain, like
corporate blockchains play out in 2017. They're all going to launch chain and some of them are
and get along and like work together, but most of them are not. And there's going to be a lot of
people are like, dude, I'm never JP Morgan. I'm never hooking up with Wells Fargo. Facebook,
I'm never hooking up with Google. Apple is just going to be like, fuck all y'all. Like I'm sitting
this out. And so then you start asking the questions like, well, then who's going to market
make between them? And sure, bridge is today, but like that requires, again, these are all
permissioned. Every party has to agree to be a part of that. And if, when you have ones that don't,
then how are you going to get the exchange between those? It's going to be extremely
inefficient, extremely complicated, and this is going to take multiple years to play out before
everyone in Silicon Valley realizes, oh shit, the way to do this is to plug in the internet, Bitcoin
might. I agree with that, but I still, I don't think they're acting dumb. I think they can make
a ton of money over the next 10 years. The dollar is not going away in the next 10 years.
I think it's a good thing. Disrupting the banks across different angles is good. So getting tech
and fintech companies in here to potentially
disrupt banks, I think that's great.
I do agree, though, that it'll play out the way you're talking about.
Like, partnership here and here, and it's just a subset of...
It's still... It is basically recreating what already exists,
but they can make a lot of money.
And then, because it will just recreate what already exists,
Bitcoin will just keep strengthening,
keep being this global financial network
and the companies that are betting on it
like Lock and LightSpark
and Lightning Labs, Tether
they benefit
if it plays out like we just said
they benefit because over the next five years
all those companies will just further develop their assets
strengthen, build great products, great customer experiences
business models, expertise
and all the other tech companies will then realize
or they'll make a lot of money,
but then they'll still be starting at zero
in five years to get on Bitcoin.
I could not, you laid it out perfectly.
And so when you say it's smart,
I mean, it depends.
Depends what's your time horizon.
Like if you're just kind of coming in,
like how do we plunder as much as possible?
Like let's put it this way.
Silicon Valley is a very long stripe,
a much longer block in this world.
Sure, stripes are gonna make a hell of a lot of money
and just like kind of like raid the cupboard
while they can.
Meanwhile, Block is becoming a giant in the background that is betting on the future and will be around in 50 years.
Most disagreements in the world come down to a difference in timing.
Yeah.
Just like the crypto people and the crypto VCs.
Some of them made a killing in 2017 and 2018.
Multicoin, one of the best performing funds of all time.
How many of their tokens have any traction ever?
Zero.
And so it's just like, I mean, play fiat games, win fiat prizes.
if you're that money hungry, enjoy in the short run.
Meanwhile, companies that are building
for 2100, we'll see you there.
All right.
I think we need to wrap. That's a good way. It's a good place
to wrap it. Max and I are agreeing with each
other. We laid out a vision. There you go.
Love it. All right. Let's go.
Until next time. Good chat, guys.
All right.
Bye-bye.
Man.
Oh, still alive. Bye, guys.
Keep