Verified claim · AI-ML · 100% confidence
Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 67bc6f4d2e49b32c
Structured fields
- Subject
- Yi (01.AI)
- Predicate
publicly_released_on- Object
- 2023-11-05 by 01.AI (Kai-Fu Lee)
- Confidence
- 100%
- Tags
- yi · 01-ai · kai-fu-lee · open-weights · released_on · 2023
Sources (2)
[1] preprint · arXiv (01.AI Team) · 2024-03-07
Yi: Open Foundation Models by 01.AI“We introduce the Yi model family, a series of language and multimodal models that demonstrate strong multi-dimensional capabilities. The Yi model family is based on 6B and 34B pretrained language models, then we extend them to chat models, 200K long context models, depth-upscaled models, and vision-language models.”
[2] model card · 01.AI · 2023-11-05
Yi-34B — Hugging Face model card
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Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee). — SourceScore Claim 67bc6f4d2e49b32c (verified 2026-05-16). https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.jsonEmbed this claim
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Frequently asked questions
Is the claim "Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee)." verified?
Yes — SourceScore verified this claim with 100% confidence as of 2026-05-16. The verification uses 2 primary sources cross-referenced against the SourceScore methodology (version veritas-v0.1). Full source list + signed JSON envelope linked below.
What is the evidence for "Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee)."?
Evidence comes from 2 primary sources: arXiv (01.AI Team), 01.AI. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.json includes an HMAC-SHA256 signature for audit verification.
When was this claim last verified by SourceScore?
Last verified 2026-05-16 under methodology version veritas-v0.1. The signed JSON envelope is dated and cryptographically signed for audit trail. Re-verification cadence depends on the claim type and source freshness.
How can I cite this SourceScore claim in my code or article?
Fetch the signed JSON envelope from https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.json which includes the verbatim claim, primary sources, confidence, methodology version, last-verified date, and HMAC-SHA256 signature for audit. The CC-BY-4.0 license permits commercial use with attribution to SourceScore.
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cURL
curl https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee)."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "Yi (01.AI) publicly released on: 2023-11-05 by 01.AI (Kai-Fu Lee)."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_yi_01_ai_fact() -> dict:
"""Fetch the verified SourceScore claim for Yi (01.AI)."""
r = httpx.get("https://sourcescore.org/api/v1/claims/67bc6f4d2e49b32c.json")
return r.json()