training language models to follow instructions with human feedback — search2

Chronological history of training language models to follow instructions with human feedback. Key events, milestones, sentiment shifts, first appearances, and patent filings with full provenance.

Data Sources

Results synthesized from web crawls, academic citations (Semantic Scholar), patent filings (USPTO), corporate ownership records (SEC EDGAR, Companies House), software dependency graphs (npm, PyPI, crates.io), infrastructure records (DNS, TLS certificates, IP ranges), temporal archives (Wayback Machine), government datasets (Data.gov), and conversational sources (Hacker News, Reddit).

View Modes

• Overview — key facts and cross-graph signals
• Trace — ownership connection map
• Timeline — chronological evolution
• Drift — consensus shift analysis
• Predict — trajectory projection
• Verify — evidence for and against
• Inverse — historical pattern matching