墨芯成立稀疏计算产学研联盟，以生态协同突破产业化壁垒
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TL;DR - Chinese AI chip startup Moffett AI (墨芯) has launched a "Sparse Computing Industry-Academia-Research Alliance" to push sparse computing from a niche technique into mainstream AI inference infrastructure. It matters because inference token volumes are exploding and the industry is shifting from raw scale to compute efficiency and TCO reduction.
- The alliance frames sparse computing as a key path to lower inference TCO, citing claims that China's daily AI token processing grew from ~hundreds of billions in early 2024 to ~hundred-trillion scale by 2026 (roughly 1000x in two years).
- Moffett positions its self-developed "dual sparsity" (双稀疏) core technology plus a full software/hardware stack as already commercially deployed, having addressed sparsity at the algorithm, compiler, and chip-architecture layers.
- Roadmap is built on a "6S technology architecture" with three tracks: energy-efficiency breakthroughs, R&D-to-product conversion via end-to-end algorithm/software/chip co-optimization, and ecosystem enablement (standards, joint research, technical evaluation).
- Members include Tsinghua, Fudan, Xi'an Jiaotong, Nankai, plus BGI, China Mobile, Shanghai INESA, VeriSilicon, and ASR Microelectronics; joint projects on sparse algorithm optimization and hardware/software co-adaptation are underway, with results promised later.
- Note: this is a company-supplied press release republished by 量子位 — no benchmarks or quantitative efficiency results are provided.
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墨芯成立稀疏计算产学研联盟，以生态协同突破产业化壁垒
TL;DR - Chinese AI chip startup Moffett AI (墨芯) has launched a "Sparse Computing Industry-Academia-Research Alliance" to push sparse computing from a niche technique into mainstream AI inference infrastructure. It matters because inference token volumes are exploding and the industry is shifting from raw scale to compute efficiency and TCO reduction.
- The alliance frames sparse computing as a key path to lower inference TCO, citing claims that China's daily AI token processing grew from ~hundreds of billions in early 2024 to ~hundred-trillion scale by 2026 (roughly 1000x in two years).
- Moffett positions its self-developed "dual sparsity" (双稀疏) core technology plus a full software/hardware stack as already commercially deployed, having addressed sparsity at the algorithm, compiler, and chip-architecture layers.
- Roadmap is built on a "6S technology architecture" with three tracks: energy-efficiency breakthroughs, R&D-to-product conversion via end-to-end algorithm/software/chip co-optimization, and ecosystem enablement (standards, joint research, technical evaluation).
- Members include Tsinghua, Fudan, Xi'an Jiaotong, Nankai, plus BGI, China Mobile, Shanghai INESA, VeriSilicon, and ASR Microelectronics; joint projects on sparse algorithm optimization and hardware/software co-adaptation are underway, with results promised later.
- Note: this is a company-supplied press release republished by 量子位 — no benchmarks or quantitative efficiency results are provided.