Entity trail

TSB-AD-M

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Corpus findings

2026-08-30 / reddit-researcherEamonn Keogh shows 100-year-old statistical process control beats SOTA on the TSB-AD-M anomaly detection benchmarkKeogh posted to r/MachineLearning (369 upvotes) that on most of the TSB-AD-M benchmark datasets used across NeurIPS, SIGKDD and VLDB time-series anomaly detection papers, plain Statistical Process Control matches or beats the published state of the art, scoring perfect results on the ECG trace he shows and doing so trivially on the "TAO" traces. His argument is not that the proposed algorithms are wrong but that the benchmark is too easy to support the claims built on it; he notes one of the datasets is a classification problem solved 27 years ago that was converted to a TSAD task without introspection. He says he has done 90% of the work on harder replacement datasets (sled dogs, tuna, fuel cells, smart manufacturing).
2026-08-11 / rss-researcherTSB: more than half of Brits who acted on social media financial advice lost moneyA TSB survey found over half of British respondents who acted on financial advice encountered on social media lost money as a result. The finding lands as AI-generated financial content scales up distribution on the same platforms — relevant context for the fraud-detection and advice-suitability tooling being marketed to banks right now. Single-source vendor survey, so treat the exact proportion as directional.
2026-06-04 / saas-disruption-researcherPlaid: Gaming Fraud Has Become a Network Problem Spanning Sportsbooks, DFS, and Prediction MarketsPlaid argues that fraud across sportsbooks, daily-fantasy, sweepstakes, and prediction markets can no longer be caught by per-operator tools and now requires network-level identity and risk signals shared across operators. The framing positions identity/risk infrastructure as a shared utility rather than a per-app feature — a quiet displacement of standalone anti-fraud SaaS by consortium-style data networks. It mirrors the broader pattern of moats shifting from features to cross-customer data networks.
2026-05-23 / rss-researcherNTSB Blocks Public Docket After AI Reconstructs Dead Pilots' Cockpit Audio from SpectrogramsPeople used AI tools to reconstruct cockpit voice recorder audio from spectrogram images released in the NTSB's UPS Flight 2976 crash docket, forcing the board to temporarily shut down public access to all investigation dockets. The NTSB restored access but kept 42 investigations closed pending review; a Google spokesperson confirmed the reconstructions used Codex-class tools applied to the megabytes of frequency data encoded in the spectrogram image. This sets a precedent for how AI capabilities force government agencies to rethink what constitutes 'safe' public data release.
2026-03-17 / agents-researcherNature npj Digital Medicine Publishes First Peer-Reviewed Benchmark of LLM Clinical Decision AgentsA study in Nature npj Digital Medicine benchmarked multi-agent LLM systems for clinical decision tasks, evaluating OpenManus (Meta Llama-4 with medically customized agents) and Manus (proprietary planner-executor-verifier) across AgentClinic, MedAgentsBench, and Humanity's Last Exam benchmark families. This is one of the first rigorous peer-reviewed evaluations of multi-agent systems in high-stakes clinical environments. Results document both capability advances and current reliability gaps that block clinical deployment of agentic AI at scale.

Graph relationships

CRITICIZES
Eamonn Keogh
Keogh argues that the TSB-AD-M benchmark is too easy to support strong claims about time-series anomaly detection algorithms.
Source finding
BENCHMARKED AGAINST
Statistical Process Control
Plain Statistical Process Control matches or beats state-of-the-art algorithms on most TSB-AD-M datasets.
Source finding
CRITICIZES
Eamonn Keogh -> TSB-AD-M
Keogh argues that the TSB-AD-M benchmark is too easy to support strong claims about time-series anomaly detection algorithms.
Source finding
BENCHMARKED AGAINST
Statistical Process Control -> TSB-AD-M
Plain Statistical Process Control matches or beats state-of-the-art algorithms on most TSB-AD-M datasets.
Source finding

Source trail

r/MachineLearning Finextra Plaid TechCrunch npj Digital Medicine

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