Uh-huh, okay.

Okay, what was the name of the technology we’re talking about?

Okay, great.

Was it using this technology? Updatable public key?

But you had a separate funding round?

Hmm, okay. So, if I want to replicate this for the next presidential hackathon or whatever, what should I do?

Okay. So, well then, this challenge becomes just to get everybody updatable public key pairs.

Okay, so it’s not like… because when I participate in the Zuzalu online pods, I don’t notice anything like that happening. I don’t have a public key that I can update.

Is it already used for on-chain governance in any form?

Okay. A nice design.

I see. So, the upload public key part is like, it can happen in a different point in time?

But what if that program also updates my public key?

I see.

No, no, it’s before that.

But if there’s a voting period, certainly the briber can specify that with a trusted timestamp service, you can only run over the last couple milliseconds of the voting period.

Yeah. So, but just to check my understanding, you’re saying that if I’m somewhat eligible for quadratic voting, and even if I, in my computer, run a program of this briber’s design that does my vote for me, still, I can somehow cancel that to run it only in a ...

Yeah, it encourages collusion, actually.

Really? Even if they’re standing next to you?

A secret ballot, yeah.

So, zero-knowledge or Ethereum only enters the picture when it becomes isomorphic to what we just talked about, when permissionless participants want to get into the action.

Well, if the participants are bounded, then it’s exactly the same as the Presidential Hackathon or the RadicalxChange board meetings, right? And for that, we have spreadsheets. It’s good technology. And collaborative spreadsheets that tell you automatically based on quadratic formula, that’s already a thing, right?

I see, government procurement. So, what you’re saying is that the people who evaluate procurements, they vote on a spreadsheet with quadratic formula?

What kind of bidding process?

We do QV all the time.

Sure, of course.

Yeah, and the Plurality section is like an embedding of plurality, in the Department of Democracy Network. Yeah.

Yeah. Yes, we have a team of people in charge of talking to telecoms about this. They’re on the same floor, very close to me. It is the Department of Plural Innovations.

And I think ZK is one of the main routes going there. Like I’m heading in this direction, I want to see, if I keep going in this direction, would I hit a point where I cannot physically keep physical distance?

Exactly, exactly. And that can be actually very privacy-infringing, right? And we want it to be like, even with quantum computers, you cannot re-identify anyone.

So, this is one of those pandemic-resilient things that I’ve been constantly thinking, like when the next Greek letter comes, right? Where we need to have a much better privacy-preserving layer to do whatever we did during the pandemic, but in a zero-knowledge way. So, I think that’s also one ...

But what we would like, the world would like to see is for the telecoms to feel at ease that they’re not giving away any private data of their customers, that they’re not giving away their trade secrets, but can still attest so that in real-time, this tourism place is ...

But this is, as you said, just to familiarize the researchers with the data formats. It’s not actually useful for any real-time stuff, unless you’re a historian, which is still very useful, right?

And we will send, as part of national apps and alerts and so on, to people. But that needs to be done in an entirely privacy-resilient way because signal data, if it’s fine-grained enough, is like surveillance, right? So of course, for research purposes, the telecoms already publish as open ...

With signal data, we’ve actually used signal data during the pandemic to warn people of the areas where you cannot physically keep physical distance without going three-dimensional. So, the signal data would tell us which areas of tourism or things like that are our danger zones and so on.

Because that’s important for, for example, signal data, right?

Many telecoms in Taiwan are very interested in that.

Yeah, it’s the open algorithm, like the reverse flow.

Exactly.

I don’t think there are any remaining software or ecosystem bottlenecks. It’s currently just really slow. And so, when it becomes fast, maybe in one year or two years down the road, I think we need to plan for that future now. Just assume that it will happen — FHE ...

It has some interesting moral repercussions. But anyway… the point I’m making is that I think the only bottleneck now is really just the degree of hardware investments that people have to do to get FHE working.

And so, like general purpose FHE for everyone is one of those holy grails, right? It’s like a general-purpose GPU moment. And if they do go to production… Their proof is that they’ve made one of the fastest Bitcoin hashing chips, and that’s how they fund themselves. Anyway…

There was a presentation I received a couple of weeks ago about a hardware accelerator, an ASIC accelerator, from a startup called Chain Reaction. They promise to make FHE only 10 times slower instead of 10,000 or 100,000 times slower.

It’s been implemented in Taiwan. But as you said, it requires pre-commitment and constant interaction between the parties to make it a reality. There’s no way to join asynchronously or in a permissionless fashion. But fully homomorphic encryption might just be the ticket.

Yes, we’ve been working on federated learning for quite a while now. So, if you have a bounded, many clinics and hospitals agree on the same data formats, then federated learning, including split learning of sci-fi tuning and so on, is not research.

Yeah, definitely. It gives the signals that can actually be just applied directly to AI without a central curator of sorts to interpret it. And that’s the main insight behind Alignment Assemblies.

Yes. So, a social, interoperable provenance layer, not just for documents, but for contribution histories and everything.

Exactly.

So, we need to talk about the strategy to get people excited about the privacy layer, now that the underlying capability now matches ChatGPT. Because if the capability doesn’t match, then it doesn’t help, right? Because you’ll be comparing passport images, and it gives a lot of false positives or ...

And so, I think the layer one prerequisites have already been made. So now, we need to talk about the ways to share such models in an interoperable way, because currently, the open-source community around huggingface and so on, like zero-knowledge or privacy-preserving sharing is not one of the priorities.

So, for language, for image, or for multi-modality, and for things like that, I think we need to make state-of-the-art, like reaching ChatGPT level models in open source that can be run in a reasonable speed on networks.