ChainCatcher Message, recently, NeuroMesh, a company focused on embodied intelligence, announced the completion of a $5 million strategic funding round, with the company’s post-investment valuation reaching $50 million. This round of financing was jointly invested by @alphacapital_vc and @CoinvestorV.
NeuroMesh is dedicated to providing edge-side intelligent solutions for robots and smart devices. Through its device-side intelligent stack, it enables robots to achieve real-time perception, planning, and execution without relying on the cloud. Meanwhile, the experiences gained by machines during learning are synchronized to a decentralized “collective brain,” enabling continuous evolution and shared learning through network effects.
This model allows the learning outcomes between intelligent agents to be verifiable and accumulative, driving the entire network to become smarter with use. NeuroMesh aims to build a truly native, verifiable, and shared autonomous intelligent world, making decentralized machine intelligence the infrastructure for the next generation of human-machine collaboration.
It is reported that the funds from this round will be used to accelerate technological research and development, expand the team size, and further develop applications in industrial automation, service robots, and other scenarios.
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NeuroMesh completes a $5 million strategic round of financing to promote embodied intelligence development through a decentralized "collective brain".
ChainCatcher Message, recently, NeuroMesh, a company focused on embodied intelligence, announced the completion of a $5 million strategic funding round, with the company’s post-investment valuation reaching $50 million. This round of financing was jointly invested by @alphacapital_vc and @CoinvestorV.
NeuroMesh is dedicated to providing edge-side intelligent solutions for robots and smart devices. Through its device-side intelligent stack, it enables robots to achieve real-time perception, planning, and execution without relying on the cloud. Meanwhile, the experiences gained by machines during learning are synchronized to a decentralized “collective brain,” enabling continuous evolution and shared learning through network effects.
This model allows the learning outcomes between intelligent agents to be verifiable and accumulative, driving the entire network to become smarter with use. NeuroMesh aims to build a truly native, verifiable, and shared autonomous intelligent world, making decentralized machine intelligence the infrastructure for the next generation of human-machine collaboration.
It is reported that the funds from this round will be used to accelerate technological research and development, expand the team size, and further develop applications in industrial automation, service robots, and other scenarios.