Unverified50% confidenceFactExact time
The training of general-purpose large models relies on massive, publicly available, crawlable internet data.
1
Sources
50%
Confidence
Long-term
Relevance
9/18/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedHigh-quality training data available on the public internet is being rapidly consumed by large models and is becoming scarce.76% similarUnverifiedEnsuring that training data contains a sufficient proportion of genuine human-original content has become a key issue in large model development, and companies such as OpenAI and Anthropic invest substantial resources in data filtering and quality control for this purpose.74% similarUnverifiedLarge models can be used to automatically generate synthetic training data based on domain documents to construct question-answer pairs, and typically thousands to tens of thousands of training pairs are needed to achieve significant results.74% similarUnverifiedTraining-time methods enhance explanation capability by modifying training objectives, which is costly and requires full access to model weights and large-scale GPU computing resources.74% similarUnverifiedThe vast majority of large model training data comes from human publicly available knowledge such as web text, books, code, and forum discussions.72% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/931719API
curl https://kongchang.com/api/v1/knowledge/claims/931719MCP
get_claim(id=931719)