Verified claim · AI-ML · 100% confidence
TensorFlow publicly released on: 2015-11-09 by Google.
Last verified 2026-05-16 · Methodology veritas-v0.1 · fc71d09cd60b84ab
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Structured fields
- Subject
- TensorFlow
- Predicate
publicly_released_on- Object
- 2015-11-09 by Google
- Confidence
- 100%
- Tags
- tensorflow · google · framework · open-source · released_on · 2015
Sources (2)
[1] official blog · Google Research · 2015-11-09
TensorFlow — Google's latest machine learning system, open sourced for everyone“Today we're proud to announce the open source release of TensorFlow — our second-generation machine learning system, specifically designed to correct the shortcomings of DistBelief, the system used by Google researchers and product teams since 2011.”
[2] docs · Wikipedia · 2015-11-09
TensorFlowWikipedia is rated by SourceScore — see its reliability →
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TensorFlow publicly released on: 2015-11-09 by Google. — SourceScore Claim fc71d09cd60b84ab (verified 2026-05-16). https://sourcescore.org/api/v1/claims/fc71d09cd60b84ab.jsonEmbed this claim
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Frequently asked questions
Is the claim "TensorFlow publicly released on: 2015-11-09 by Google." 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 "TensorFlow publicly released on: 2015-11-09 by Google."?
Evidence comes from 2 primary sources: Google Research, Wikipedia. Each source is listed below with verbatim excerpts and URLs. The signed JSON envelope at https://sourcescore.org/api/v1/claims/fc71d09cd60b84ab.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/fc71d09cd60b84ab.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.
Use this claim in your code
Fetch this signed envelope from your application. The response includes the verbatim excerpt, primary source URLs, and an HMAC-SHA256 signature you can verify locally for audit trails.
cURL
curl https://sourcescore.org/api/v1/claims/fc71d09cd60b84ab.jsonJavaScript / TypeScript
const r = await fetch("https://sourcescore.org/api/v1/claims/fc71d09cd60b84ab.json");
const envelope = await r.json();
console.log(envelope.claim.statement);
// "TensorFlow publicly released on: 2015-11-09 by Google."Python
import httpx
r = httpx.get("https://sourcescore.org/api/v1/claims/fc71d09cd60b84ab.json")
envelope = r.json()
print(envelope["claim"]["statement"])
# "TensorFlow publicly released on: 2015-11-09 by Google."LangChain (retrieve-then-cite)
from langchain_core.tools import tool
import httpx
@tool
def get_tensorflow_fact() -> dict:
"""Fetch the verified SourceScore claim for TensorFlow."""
r = httpx.get("https://sourcescore.org/api/v1/claims/fc71d09cd60b84ab.json")
return r.json()