This research examines the polycentric governance of digital assets in blockchain-based Decentralized Autonomous Organizations (DAOs). It offers a theoretical framework and addresses a critical challenge facing decentralized governance by developing a method to identify sybils, or spurious identities. Sybils pose significant organizational sustainability threats to DAOs and other, commons-based online communities, and threat models are identified. The experimental method uses graph deep learning techniques to identify sybil activity in a DAO governance dataset (snapshot.org). Specifically, a Graph Convolutional Neural Network (GCNN) learned voting behaviours and a fast k-means vector clustering algorithm (FAISS) used high-dimensional embeddings to identify similar nodes in a graph. The results reveal that deep learning can effectively identify sybils, reducing the voting graph by 2-5%. This research underscores the importance of sybil resistance in DAOs and offers a novel perspective on decentralized governance, informing future policy, regulation, and governance practices.

SingularityNET's founding mission of creating beneficial decentralized AGI is a large one and has a number of different aspects, all of which need to work together tightly. There's the decentralized-platform software layer, which is needed to make it feasible to run AI systems across large numbers of computers without any central owner or controller. The SingularityNET protocol and platform provide one portion of this layer, the NuNet decentralized compute resource network provides another, and the HyperCycle AI-customized ledgerless blockchain provides another. Decentralized-AI-platform tools are mainly agnostic in regards to how AGI is achieved -- be it neural nets, artificial life systems, brain simulations, logical reasoning engines, emergent combinations of different AI agents and paradigms, or something new and yet unforeseen. However, our team at SingularityNET has been putting significant effort into one particular approach to AGI, which is the OpenCog Hyperon framework, bringing together neural nets, logical reasoning, evolutionary learning, and other methods in the context of a distributed self-modifying knowledge metagraph.

Speaking at BlockShow Asia 2019, Todalarity CEO Toufi Saliba posed a hypothetical question to the audience: "How many people would take a pill that made you smarter, knowing they can be controlled by a social entity?" No one raised their hand, and he was unsurprised. "That's the response that I get, zero percent of you," he continued. "Now imagine at the same time the pill has autonomous decentralized governance so that no one can control or repurpose that pill but the host – yourself." This time hands were raised in abundance.