Unverified50% confidenceFactExact time
RSC基于英伟达GPU构建,设计目标是支持万亿参数级别的模型训练
1
Sources
50%
Confidence
Long-term
Relevance
7/10/2026
First Seen
Sources
扎克伯格直言:AI智能体尚未达到预期,技术瓶颈在哪里?
hackernewshackernews7/5/2026
Related Claims
Unverified可利用大模型基于领域文档自动生成合成训练数据来构造问答对,通常需要数千至数万对训练样本才能取得显著效果68% similarUnverified大模型训练主要消耗来自数以万计的高端GPU(如NVIDIA A100/H100)的算力67% similarUnverifiedSWE-bench公开的训练方案覆盖了数据准备、模型选择、微调策略、推理框架等关键环节67% similarUnverifiedSISA 方法将训练数据分片后独立训练子模型,删除数据时只需重训相关分片,但需要从架构设计一开始就纳入规划65% similarUnverified智谱GLM-5.3基于743B(7430亿参数)基座进行后训练,主打编程与智能体两大核心场景65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/459365API
curl https://kongchang.com/api/v1/knowledge/claims/459365MCP
get_claim(id=459365)