Unverified50% confidenceOpinionExact time
A growing number of researchers believe that simply scaling up model size cannot solve the discovery problem, and that real progress comes from system-level design.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
9/11/2026
First Seen
Valid until: 12/10/2026
Sources
Related Entities
Related Claims
Unverified单纯追求更强大的AI模型不足以带来科学的实质飞跃，真正的进步取决于整个科研体系能否协同演进71% similarUnverified经典统计学习理论的框架并不能完全解释超大规模模型的行为70% similarUnverified涌现能力现象仍是学术界积极研究的课题，研究者无法完全解释为什么模型会表现出某些能力70% similarUnverified提示工程类工作难以提供严格的理论分析，其有效性更多依赖实验观察69% similarUnverifiedFor complex tasks requiring open-ended research and deep cross-page reasoning, small models are difficult to match even after fine-tuning, making large models indispensable.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/904346API
curl https://kongchang.com/api/v1/knowledge/claims/904346MCP
get_claim(id=904346)