We train and run Claude on a range of AI hardware—AWS Trainium, Google TPUs, and NVIDIA GPUs—which means we can match workloads to the chips best suited for them.
大多数人认为AI公司会依赖单一硬件供应商以获得最佳性能，但Anthropic采用多平台策略，挑战了行业共识。这种多元化方法虽然增加了复杂性，但提供了更好的性能和弹性，暗示了AI计算的未来可能更加分散而非集中。
over 500 business customers were each spending over $1 million on an annualized basis. Today that number exceeds 1,000, doubling in less than two months.
大多数人对AI企业客户的采用速度持保守态度，但Anthropic的高价值客户数量在短短两个月内翻倍，表明企业对AI的采用速度和投资规模远超行业预期，挑战了AI企业市场缓慢发展的普遍认知。
Demand from Claude customers has accelerated in 2026. Our run-rate revenue has now surpassed $30 billion—up from approximately $9 billion at the end of 2025.
大多数人认为AI公司仍处于烧钱阶段，但Anthropic的收入增长速度惊人，从2025年底的90亿美元年化收入飙升至2026年的300亿美元，这表明AI商业化速度远超市场预期，挑战了AI公司长期亏损的共识观点。
Figure 2. Four mechanisms support concurrent task execution in CORPGEN: hierarchical planning, isolated subagents, tiered memory, and adaptive summarization.
特别的微软
Clean Room as a Service
信创福音？
Some retailers / brands offer this on their website already, but it’s limited to their SKUs. We see an opportunity for AI consultants that have deep knowledge on a product category across different brands, and that learn more context on each user and their preferences over time (for example, if it helps you buy a sofa, it can later tailor chair recommendations to things that match).
一个符合需求的收纳箱
深势科技
https://www.dp.tech/knowledge
OJBench
https://arxiv.org/pdf/2506.16395v1 Comparison between CPP and Python
Multi Hop
PWA-enabled dashboard
类metero框架的机会？
A managed runtime environment
BaaS又复活了
consistently improves with more reinforcement learning (train-time compute) and with more time spent thinking (test-time compute)
RL for post-train, time spent thinking for inference? How?