Unverified50% confidenceFactExact time
Fully open source typically requires making datasets and training processes publicly available.
1
Sources
50%
Confidence
Long-term
Relevance
9/19/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe training of general-purpose large models relies on massive, publicly available, crawlable internet data.75% similarUnverifiedThe open-source approach emphasizes the public sharing of model weights, code, and training methods, lowering the barriers to technology access.72% similarVerifiedOpen weights differ from fully open source: the former makes model parameters public but does not necessarily disclose training data and complete training code.71% 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.70% similarUnverifiedHigh-quality training data available on the public internet is being rapidly consumed by large models and is becoming scarce.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/934169API
curl https://kongchang.com/api/v1/knowledge/claims/934169MCP
get_claim(id=934169)