Unverified60% confidenceFactTime unknown
Karpathy identified three core problems with LLM programming: erroneous assumptions, over-complication, and out-of-scope modifications.
2
Sources
60%
Confidence
Long-term
Relevance
6/2/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedStrong reasoning models represented by DeepSeek-R1 and Kimi K3 suffer from an overthinking problem, spending a large number of tokens on simple questions, slowing responses and increasing inference costs.68% similarUnverifiedAutoregressive generation has three fundamental limitations: sequential dependency, information bottleneck, and error accumulation.68% similarUnverifiedThe study found three types of shortcomings of LLMs in TMP generation: over-generation of strategies, difficulty providing project-specific justifications, and inaccurate cost estimation.68% similarUnverifiedIn probabilistic LLM-driven systems, "errors" are often ambiguous and context-dependent, complicating fault-tolerant design67% similarUnverified当前LLM在代码生成上存在幻觉问题、上下文窗口限制和安全隐患三个系统性弱点67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/37618API
curl https://kongchang.com/api/v1/knowledge/claims/37618MCP
get_claim(id=37618)