agents often lack a dependable way to access the databases containing the information they need.
大多数人认为AI的主要挑战在于理解和推理复杂信息，但作者认为AI在生物学领域面临的核心问题是无法可靠地访问所需数据库。这一观点颠覆了人们对AI能力瓶颈的认知，表明问题不在于AI的理解能力，而在于数据访问的可靠性。
2 Matching Annotations
- Last 7 days
-
www.anthropic.com www.anthropic.com
-
- Apr 2026
-
developer.nvidia.com developer.nvidia.com
-
For higher-interactivity scenarios, execution time for MoE models is bound by expert weight load time. By splitting, or sharding, the experts across multiple GPUs across NVL72 nodes, this bottleneck is reduced, improving end-to-end performance.
大多数人认为MoE模型的主要瓶颈在于计算能力，但作者指出专家权重加载时间是真正的瓶颈，并提出通过跨GPU分片专家权重来解决问题，这挑战了AI模型优化的传统认知，暗示了I/O可能比计算更重要。
-