Montenegro is nice

This weekend I was at the AI x Crypto event at Zuzalu, a pop-up city in Montenegro.

It is really very nice there, do swing by Tivat.

It was great to meet the awesome folk trying hard to figure out this crazy time, I will speak more on the various things in upcoming posts (awesome to meet the amazing Vitalik Buterin in person (I’m a huge fan) & Grimes had some super interesting insights even if we completely disagreed on some things - stable diffusion moment for music incoming). 

On AI x Crypto

(credit: )

AI x Crypto

When I moved Stability AI to focus on generative AI following some interesting experiences working on AI & Covid  at the end of 2021 one of the original ideas was to have a DAO of DAOs for supporting the various communities for open source AI.

We experimented with various potential models for this with a goal of making it so that AI was not an inherently centralising force, but the infrastructure and tools were just not there.

This has been something interesting about crypto, in that while there is clearly interesting things in there it is questionable how much value has been able to be created.

Creating a system outside of the existing system has meant that much of the money has been made and lost on the interface between the two, be it hacks or speculation or otherwise.

The fundamental of crypto however is in the name - cryptography enables identity.

Identity and the flow of information against this was at the core of the Bitcoin whitepaper by the eponymous Satoshi Nakamoto, with the headline of the abstract being:

“A purely peer-to-peer version of electronic cash would allow online payments to be sent directly from one party to another without going through a financial institution.”

This is an interesting thing with elements around sovereignty, coordination and more, but there was always something missing.

Something there that wasn’t there before

The existing web was made of identity (Google, Facebook login) and centralised AI.

This routed information back and forth but was largely built on ads.

I always thought it was weird that there was no AI in Web3 as it was called.

This is because partially the big data systems required a lot of heft and standardisation to work, one reason you saw centralised exchanges and more emerge, especially at the interface between decentralised networks and the existing systems.

Existing systems are actually often slower on purpose too - things like remittances and instant payments are easy, but when you get instant payments you also get.. Silicon Valley Bank collapses (more on that soon too..).

The interesting thing about generative AI is that it is not big data, it is dense models trained on giant compute and structured datasets so the output is this curious thing, a model weight.

This is a file that compresses the principles extracted from the data in an impossibly small format that requires large energy up front but very little relatively speaking to run.

Stable diffusion was 100,000 gigabytes of images, 2 billion, into a 2 gigabyte file that powered 4 of the top 10 apps on the App Store in December.

That’s the whole back end, not multiple dependencies and complex software. 

It runs on a phone now so we have infinite images in our pockets. 

How cool is that.

This enables new design patterns, especially when combined with identity and value transfer rails, where value can be considered equivalent to information that is important in changing a state (classic information theory a la Shannon encapsulated).

The Intelligent Internet

The moving of intelligence to the edge enables a concept I like to call the intelligent internet:

Standardised models customised to individuals under their own ownership, to paraphrase the classic crypto statement, not your crypto - not your weights, not your brain as we rely more on these will become important.

The governance of open systems is something we can learn a lot from all the hard work that has gone on in the crypto space (while hopefully avoiding some of the excesses).

Who should be deciding how datasets and models are built?

These things are not unbiased nor can they be I think.

Who should control the distribution and access?

Who should have access?

Satoshi Nakamoto also had an interesting statement :

“It takes advantage of the nature of information being easy to spread but hard to stifle.”

The spreading of model weights and customisations of those weights that are even smaller is something with similar properties and combined with identity & value transfer rails can lead to some very interesting outcomes for the benefit of society.

How we deal with these is going to be very important to our communal future and something quite important to bring a range of viewpoints in.

Open source AI is critical for private knowledge and ownership and is not going away, but some more thoughts on what I have seen in this journey coming soon..