The future of AI is fast, secure and decentralized.
The future of artificial intelligence lies in being fast, secure, and decentralized, and Veea’s Edge Platform is at the forefront of this innovation. By combining the power of embedded Linux servers and edge computing, VeeaHub Edge Servers are uniquely designed to collect and process data for deep learning applications at the edge, while also seamlessly integrating with centralized AI servers. Veea’s Edge Platform is ideally suited for Edge AI models, ensuring maximum privacy and security with local data processing capabilities.
Compute
VeeaHub units are equipped with embedded Linux servers, providing robust and reliable edge computing capabilities for deep learning and AI applications.
3rd Party Integration
The platform supports seamless integration with GPU, NPU, and TPU hardware accelerators, enabling high-performance AI processing tailored to specific use cases.
Decentralized Model Training
VeeaHub units serve as decentralized nodes, capable of training AI models locally at the edge, reducing dependence on central servers and enhancing real-time processing capabilities.
With support for federated learning, VeeaHub nodes play a critical role in decentralizing AI processing by collecting data and performing model training directly at the edge. By incorporating blockchain technology, the Veea Edge Platform enhances efficiency and responsiveness while maintaining strong data privacy. Furthermore, the platform’s software architecture easily integrates with third-party GPU, NPU, or TPU hardware accelerators, providing the flexibility to meet diverse AI processing needs.
The application of Edge AI within Veea’s ecosystem goes beyond VeeaHubs, extending to mobile and IoT devices. VeeaHubs can provide essential network resources to mobile devices, serving as blockchain nodes within the federated learning network. Using validators, the system offloads computational tasks while ensuring robust security, making Veea’s Edge Platform a leader in decentralized AI.
Key Features
The Edge AI for Veea Edge Platform use cases at the edge can be expanded beyond VeeaHub units to mobile and IoT devices.
Depending on the AI model, some smartphones may be able to compute the local model updates with on-device data samples.
VeeaHub units:
can provide network resources to the resource-constraint mobile devices
serve as nodes in the blockchain network of FLchain.
FLwBC can effectively reduce the communication overhead by maintaining a fixed number of active parameters during training and peer-to-peer communication.
The framework introduces ‘‘validators’’ (similar to cryptocurrency miners) in order to offload the computational burden of the trainers while reinforcing the security of the decentralized system.
The role of the central server in centralized federated learning is achieved by the smart contracts.
The nodes on a VeeaHub cluster performs local training and, afterwards, the local model updates are sent to the “consensus committee” on one VeeaHub node that verifies and assigns scores to the model updates.
Subsequently, the updated global model is incorporated into the blockchain.
AI model is updated by the VeeaHub units and blockchain network.
Developer Tools
Discover how you can get started with Edge AI using VeeaHub Toolkit and IoT Toolkit
Enhanced Privacy & Security: Veea’s Edge Platform processes data locally at the edge, ensuring that sensitive information remains secure while reducing the risk of exposure. By leveraging federated learning and blockchain, Veea guarantees privacy and trust at every level.
Decentralized AI Processing: VeeaHubs enable decentralized AI model training at the edge, reducing reliance on centralized servers. This leads to faster processing, lower latency, and improved responsiveness for real-time applications.
Scalable & Flexible Architecture: Veea’s software architecture seamlessly integrates with third-party hardware accelerators such as GPUs, NPUs, and TPUs, allowing organizations to customize their AI deployments for optimal performance.
Efficient Resource Management: VeeaHubs provide critical network resources to support resource-constrained devices, such as smartphones and IoT units, ensuring efficient AI model updates and reducing communication overhead in decentralized networks.
Blockchain-Powered Security: By incorporating blockchain technology and validators, Veea’s platform reinforces the security of decentralized systems while offloading computational tasks, ensuring a highly secure and scalable AI environment.
Edge AI In Action
O.N.E. Amazon
Veea has enabled Internet of Forest for O.N.E. Amazon to redefine the value of our planet’s biomes, from the lush rainforests of the Amazon to the vast Savannahs of Africa, the dense forests of Southeast Asia, and beyond, by leveraging the power of blockchain technology.
