Guillaume Verdon: belief

Transcript context

…I do think that right now there’s a bias over a centralization of AI, because of a compute density and centralization of data and how we’re training models. I think over time we’re going to run out of data to scrape over the internet, and I think that, well, actually I’m working on, increasing the compute density so that compute can be everywhere and acquire information and test hypotheses in the environment in a distributed fashion. I think that fundamentally, centralized cybernetic control, so having one intelligence that is massive that fuses many sensors and is trying to perceive the world accurately, predict it accurately, predict many, many variables and control it, enact its will upon the world, I think that’s just never been the optimum, right? Like let’s say you have a company, if you have a company, I don’t know, of 10,000 people, they all report to the CEO. Even if that CEO is an AI, I think it would struggle to fuse all of the information that is coming to it and then predict the whole system and then to enact its will. What has emerged in nature and in corporations and all sorts of systems is a notion of sort of hierarchical cybernetic control, right. In a company it would be, you have like the individual contributors, they are self-interested and they’re trying to achieve their tasks and they have a fine, in terms of time and space if you will, control loop and field of perception, right. They have their code base, let’s say you’re in a software company, they have their code base, they iterate it on it intraday, right. And then the management maybe checks in, it has a wider scope, it has, let’s say five reports, right. And then it samples each person’s update once per week, and then you can go up the chain and you have larger timescale and greater scope. And that seems to have emerged as sort of the optimal way to control systems. And really that’s what capitalism gives us, right? You have these hierarchies and you can even have like parent companies and so on. And so that is far more fault tolerant, in quantum computing, that’s my feel that came from, we have a concept of this fault tolerance in quantum air correction, right? Quantum air correction is detecting a fault that came from noise, predicting how it’s propagated through the system and then correcting it, right, so it’s a cybernetic loop. And it turns out that decoders that are hierarchical and in each level, the hierarchy are local- icting how it’s propagated through the system and then correcting it, right, so it’s a cybernetic loop. And it turns out that decoders that are hierarchical and in each level, the hierarchy are local- … that are hierarchical. And at each level, the hierarchy are local, perform the best by far, and are far more fault-tolerant. The reason is, if you have a non-local decoder, then you have one fault at this control node and the whole system crashes. Similarly to if you have one CEO that everybody reports to and that CEO goes on vacation, the whole company comes to a crawl. To me, I think that yes, we’re seeing a tendency towards centralization of AI, but I think there’s going to be a correction over time, where intelligence is going to go closer to the perception. And we’re going to break up AI into smaller subsystems that communicate with one another and form a meta system. If you look at the hierarchies that are in the world today, there’s nations and those all hierarchical. But in relation to each other, nations are anarchic, so it’s an anarchy.…

Stored transcript either side of the excerpt. The highlighted words are the published quote; the surrounding text is unedited source, never generated.