Alphabet’s CapitalG, Microsoft’s M12, Micron Ventures, and NVIDIA be a part of forces to again optical swap startup tackling communication bottlenecks in knowledge facilities, high-performance computing (HPC), and AI/ML programs.
nEye Methods, an optical swap startup based by UC Berkeley technologists, has introduced the completion of a $58 million Sequence B spherical of financing led by Alphabet’s impartial progress fund, CapitalG, with participation from M12, Microsoft’s enterprise fund; Micron Ventures; NVIDIA; and Socratic Companions. This financing brings the corporate’s complete funding to $72.5 million; nEye beforehand secured an unannounced Sequence A led by TEDA Holdings with help from Innolight Expertise USA and extra Seed funds.
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nEye’s progressive optical swap expertise is poised to remodel the AI cloth by addressing important communication bottlenecks in knowledge facilities, high-performance computing (HPC), and synthetic intelligence (AI) and machine studying (ML) programs. Present infrastructures, which rely totally on electrical switches, face important challenges in energy consumption in addition to bandwidth limitations. This hinders utilization and will increase knowledge heart prices and energy consumption. nEye’s wafer-scale optical circuit swap (OCS) supplies a extra environment friendly and cost-effective answer by using direct optical connections, which provide nearly limitless bandwidth.
“nEye’s groundbreaking expertise has the potential to considerably enhance the effectivity and scalability of AI infrastructure,” stated James Luo, Basic Accomplice at CapitalG and nEye board member. “Their progressive optical circuit swap addresses important bottlenecks dealing with knowledge facilities and high-performance computing. We’re thrilled to accomplice with Professor Ming Wu and all the nEye staff on their audacious journey to redefine the panorama of AI computing.”
nEye has pioneered an industry-leading excessive radix silicon photonic swap with ultra-low energy consumption. Leveraging over 10 years of analysis from Professor Ming Wu’s lab at UC Berkeley, nEye’s optical swap answer provides excessive efficiency, low price, and a compact kind issue. In comparison with current optical swap options, nEye’s expertise is 100x smaller, 1,000x decrease energy consumption, 10,000x quicker, and 10x decrease price.
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“We’re thrilled to have the help of CapitalG and our different esteemed traders as we scale our optical swap expertise,” stated Professor Ming Wu, co-founder of nEye Methods. “Our wafer-scale method, backed by years of analysis at UC Berkeley, positions us to remodel the AI cloth and allow the subsequent technology of high-performance computing.”
Optical switches are gaining broad adoption, with Google already asserting optically reconfigurable AI supercomputers. nEye’s expertise could be deployed in numerous functions, together with community flattening, community resilience, and contained in the rack to increase GPU cluster sizes and improve GPU utilization effectivity.
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