WhatsApp Scam Alert shows how on-device ML, confidential analytics, transparency logs, and fail-closed verification can protect E2EE messaging.
Meta 多阶段广告排序把长序列计算移出请求链路，并用迁移效率、延迟和业务结果共同约束扩容。
Meta multi-stage ads ranking separates long user modeling from online scoring. Learn its scaling laws, transfer ratio, and release gates.
从参考实现、参数容差、模拟真值、数值诊断到真实数据，建立科学 Agent 的五层验证栈。
A five-layer verification stack for scientific AI agents, from reference parity and parameter tolerances to simulation truth and stewardship.
Meta GEM 将端到端 MFU 提升至 20% 至 25%。真正可复用的是围绕真实负载持续识别并转移瓶颈的方法。
Meta GEM training efficiency shows why LLM-scale recommenders need workload-specific kernels, precision, parallelism, memory, and profiling.
California DROP reaches 600+ data brokers. Use status, matching, deadlines, and follow-up checks to build a verifiable deletion workflow.
产品的 AI 可用性要看 Agent 能否完成真实任务，并通过外部状态、恢复能力、成本与回归稳定性验证。
Test whether AI agents can use your product with dynamic task evals that measure correct state changes, recovery, cost, and regression stability.
