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Every published item, in order · 27 items
10月22日
10月21日
IndustryUS vs ChinaMulti-sourceSelected79°13:09
DeepSeek V4.1F shows 5x-7.4x decode edge on Ascend 950DT vs GB200

The cost crossover at 6.8K tokens/s/chip reframes the Ascend-versus-Blackwell debate from raw benchmark losses to workload-dependent economics, suggesting DeepSeek could run its API on a sub-US$1B Blackwell cluster while pivoting post-training to Ascend. Practitioners tracking inference infrastructure or Huawei's CANN ecosystem get a rare concrete per-chip price and throughput comparison. The proposed 128-chip Ascend supernode topology has no Nvidia equivalent, which matters for anyone planning large-scale decode deployments.

Event
Teortaxes@teortaxesTex11 sourcesSource
10月20日
IndustryUS vs ChinaSelected20:10
DeepSeek V4.1 Would Need Thousands More Blackwell GPUs

The back-of-envelope math suggests DeepSeek's RL training pipeline is compute-bound at the GPU level, not CPU-bound, which changes how analysts should read its published infrastructure claims. Investors and policy watchers tracking US export-control impact on Chinese labs can use the 3,000-GPU figure as a yardstick for scaling bottlenecks. Compare it with NVIDIA Blackwell allocation tiers announced for US hyperscalers.

Teortaxes@teortaxesTexSource
10月19日
IndustryUS vs ChinaSelected23:52
NetEase LobsterAI releases second China office Agent user behaviour report

Cache hit rate alone is a poor proxy for cost: models with nearly identical hit rates showed a more than seven-fold gap in what users actually paid versus list price, making DeepSeek's pricing structure unusually favourable for long agent tasks. Teams deploying office agents in China can use the per-model effective-cost figures to pick cheaper backends, with LobsterAI reachable via desktop, WeChat and Feishu. The report is self-reported product data, so treat the absolute numbers as one product's view rather than market-wide evidence.

Event
宝玉@dotey2 sourcesSource
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9月23日
IndustryUS vs ChinaMulti-sourceSelected73°15:02
Goldman Sachs: US Outspends China on AI Compute $806bn vs $110bn

The compute gap is smaller than it looks, because efficiency gains let Chinese labs deliver competitive inference at a fraction of the infrastructure cost. Developers and procurement teams choosing between US and Chinese models should track OpenRouter usage rankings and token pricing rather than headline capex figures. Goldman expects the next competitive front to be virtual-worker use cases in finance, legal and accounting workloads.

Event
AI Will@FinanceYF54 sourcesSource
9月17日
AITOP16:09
Anthropic拟10月在新加坡设亚太第五个办事处 开...

Anthropic拟10月在新加坡设亚太第五个办事处 开放本地招聘 数据显示,按人口比例计算,新加坡的Claude.ai使用水平在121个国家中排名第二。 我们观察到,人工智能公司Anthropic计划于10月在新加坡设立其亚太地区的第五…

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9月10日
8月13日
8月7日
AITOP17:04
出口结构剧变:中国卖给世界的,不再是产品而是解法

中国出口"新新三样":从打火机到爬墙机器人,世界不再只是买便宜货 我们观察到一组清晰的数据信号:中国出口的"新新三样"已经从过去的服装、家具、家电,换成机器人、AI模型和创新药物。这不是产业升级的修辞游戏,而是发生在澳大利亚和巴西的实证样…

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8月2日