Qualcomm Vets Join Blockchain RISC-V Chip Developer
Nitin Dahad, EETimes
8/1/2018 00:01 AM EDT
LONDON — An organization developing what it claims is the world’s first blockchain chip and a network of hyper-scalable blockchain IoT networks to create an “intelligent machine economy” has taken on a number of former Qualcomm engineers to develop the chip and the ecosystem.
The Skynet project, launched by the OpenSingularity Foundation, envisions a network of intelligent machines (as in the movie “Terminator”), utilizing blockchain, IoT, and AI to create secure trusted networks of devices that can intelligently communicate with each other autonomously and on a large scale. The organization says that this will enable billions of interconnected identifiable IoT devices to participate effortlessly in a global machine-to-machine (M2M) economy powered by self-organizing AI networks with data integrity facilitated by blockchains, which provide solutions for device identity, secure decentralized micro-payments, and trusted communication.
To read the full article, click here
Related Semiconductor IP
- Gen#2 of 64-bit RISC-V core with out-of-order pipeline based complex
- Compact Embedded RISC-V Processor
- Multi-core capable 64-bit RISC-V CPU with vector extensions
- 64 bit RISC-V Multicore Processor with 2048-bit VLEN and AMM
- RISC-V AI Acceleration Platform - Scalable, standards-aligned soft chiplet IP
Related News
- What RISC-V Means for the Future of Chip Development
- Jmem Tek and Andes Technology Partner on the World’ s First Quantum-Secure RISC-V Chip
- RISC-V Breakthrough: SpacemiT Develops Server CPU Chip V100 for Next-Generation AI Applications
- Minima qualifies to join Arm Flexible Access Program to bring the Minima Chip to Life
Latest News
- RISC-V Exceeding Expectations in AI, China Deployment
- BrainChip and Parsons Sign Strategic Agreement to Accelerate Edge AI Defense Systems
- Ainekko Brings Open-Source Principles to AI Hardware with Launch of AI Foundry
- Arteris Selected by Axelera AI to Accelerate Computer Vision for Edge Devices
- Preliminary Characterisation Report for Perceptia’s pPLL08W in GF 22FDX Now Available