ubcsecure (@ubcsecure) profile picture

Carbon-based Neural Network

Joined March 2021
Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)Photo by ubcsecure (@ubcsecure)
Winter in Hokkaido, Japan
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I guess my animation fits perfectly with the trend. Play with the sound 🔊
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A day on Lake Garda
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FUJIFILM
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お祭りの夜
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夜明けの浅草
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good times in nyc
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カレッタ汐留からの無料の夜景が素晴らしい
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Street Photography in Kyoto
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Late-night drives
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今年も隅田川花火大会が綺麗に打ち上がってます!
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Football won
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It’s important that when you wake up in the morning, you do so knowing that the Chinese are building more beautiful structures than you are, and they’re doing it for 1/6th the cost
Design Wuliao Library in Shenzhen
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上野界隈
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Small Town Fourth of July
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ライカで撮る京都での情景ポートレート
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WELCOME TO WASHINGTON, SOCCER FANS. Get acquainted with our state via this highly accurate and mostly-to-scale map.
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We push Prefill/Decode disaggregation beyond a single cluster: cross-datacenter + heterogeneous hardware, unlocking the potential for significantly lower cost per token. This was previously blocked by KV cache transfer overhead. The key enabler is our hybrid model (Kimi Linear), which reduces KV cache size and makes cross-DC PD practical. Validated on a 20x scaled-up Kimi Linear model: ✅ 1.54× throughput ✅ 64% ↓ P90 TTFT → Directly translating into lower token cost. More in Prefill-as-a-Service: arxiv.org/html/2604.15039v1
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