tensorfeed.ai

AI safety incident exposure analytics. Per-developer and per-deployer incident counts with recency-weighted exposure_score (1.0 last 30d, 0.5 days 31-90, 0.25 older), risk_domain and SEP-view (Security/Ethics/Performance) distributions, top affected artifacts. Derived over the AVID (avidml/avid-db, MIT) snapshot refreshed daily. The "which AI vendors have the most recent reported safety incidents"

Top 100 recent AI papers ranked by the share of their total citations earned in the most recent calendar year. Papers published in the last 2 years with 3+ citations. Surfaces papers that are still gaining traction now. OpenAlex CC0.

Last 30 days of arXiv preprints flagged as milestone candidates by an offline Qwen 3.6 27B per-paper extraction pass. Each paper carries structured reasoning naming the benchmark + quantified delta, model release, or novel architecture justification. Conservative; false positives are worse than false negatives.

Forward and backward calendar over the AI policy registry. Each entry classified relative to now (past / active / upcoming), days-until-effective, with next-3-milestones for upcoming items. Filter by jurisdiction (EU, US, UK, etc) and time window. The "what AI rules are about to bite" feed.

AI-stack CVE intelligence. Filters fresh security disclosures to vendors and products in the AI inference, agent framework, training, vector DB, model gateway, and MCP tool layers. Each paper carries a tf_ai_category tag and a severity_rank, sorted with exploited-in-wild and critical-severity first. 99.8% of underlying data is from GitHub Security Advisories (CC BY 4.0).