相关论文: SAKSHI: Decentralized AI Platforms
Recent research in Internet of things has been widely applied for industrial practices, fostering the exponential growth of data and connected devices. Henceforth, data-driven AI models would be accessed by different parties through certain…
The rapid advancement of ML models in critical sectors such as healthcare, finance, and security has intensified the need for robust data security, model integrity, and reliable outputs. Large multimodal foundational models, while crucial…
Centralization enhances the efficiency of Artificial Intelligence (AI) but also introduces critical challenges, including single points of failure, inherent biases, data privacy risks, and scalability limitations. To address these issues,…
There has been an unprecedented surge in the number of service providers offering a wide range of machine learning prediction APIs for tasks such as image classification, language translation, etc. thereby monetizing the underlying data and…
Blockchain, also coined as decentralized AI, has the potential to empower AI to be more trustworthy by creating a decentralized trust of privacy, security, and audibility. However, systematic studies on the design principle of blockchain as…
In the domain of spatial crowdsourcing drone services, which includes tasks like delivery, surveillance, and data collection, secure communication is paramount. The Public Key Infrastructure (PKI) ensures this by providing a system for…
Digital platforms increasingly support collaboration across organizations, yet many remain constrained by fragmented data and limited transparency. This paper presents the Global Solutions Initiative (GSI) D-Hub, a data-driven coordination…
The rapid expansion of distributed Artificial Intelligence (AI) workloads beyond centralized data centers creates a demand for new communication substrates. These substrates must operate reliably in heterogeneous and permissionless…
As artificial intelligence (AI) systems become increasingly integral to critical infrastructure and global operations, the need for a unified, trustworthy governance framework is more urgent that ever. This paper proposes a novel approach…
Blockchain introduces decentralized trust in peer-to-peer networks, advancing security and democratizing systems. Yet, a unified definition for decentralization remains elusive. Our Systematization of Knowledge (SoK) seeks to bridge this…
The Internet of Things (IoT) bears unprecedented security and scalability challenges due to the magnitude of data produced and exchanged by IoT devices and platforms. Some of those challenges are currently being addressed by coupling IoT…
To counter fragmented, high-risk adoption of commercial AI tools, we built and ran an institutional AI platform in a six-month, 300-user pilot, showing that a university of applied sciences can offer advanced AI with fair access,…
Large Reasoning Models (LRMs) and Multi-Agent Systems (MAS) in high-stakes domains demand reliable verification, yet centralized approaches suffer four limitations: (1) Robustness, with single points of failure vulnerable to attacks and…
We present a blockchain based system that allows data owners, cloud vendors, and AI developers to collaboratively train machine learning models in a trustless AI marketplace. Data is a highly valued digital asset and central to deriving…
Aiming to support a cross-sector and cross-border eGovernance paradigm for sharing common public services, this paper introduces an AI-enhanced solution that enables beneficiaries to participate in a decenntralized network for effective big…
Social Explainable AI (SAI) is a new direction in artificial intelligence that emphasises decentralisation, transparency, social context, and focus on the human users. SAI research is still at an early stage. Consequently, it concentrates…
Decentralized AI systems, such as federated learning, can play a critical role in further unlocking AI asset marketplaces (e.g., healthcare data marketplaces) thanks to increased asset privacy protection. Unlocking this big potential…
Artificial Intelligence (AI) has the potential to significantly benefit or harm humanity. At present, a few for-profit companies largely control the development and use of this technology, and therefore determine its outcomes. In an effort…
The convergence of blockchain and artificial intelligence (AI) has led to the emergence of AI-based tokens, which are cryptographic assets designed to power decentralized AI platforms and services. This paper provides a comprehensive review…
The rise of space AI is reshaping government and industry through applications such as disaster detection, border surveillance, and climate monitoring, powered by massive data from commercial and governmental low Earth orbit (LEO)…