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Indirect tax teams process thousands of transactions every day. Most are correct. Some are not. A tax rate changes when … The post How AI-powered anomaly detection catches indirect...
On March 13, 2023, an alarm went off.Continue reading on Medium »
The first time most teams encounter a hallucination in production, they treat it like a bug. They investigate the specific output, trace it back to a prompt or a context window, ad...
Anomaly detection has become one of the most critical technologies of the modern connected world, quietly guarding everything from hospital patients to water treatment plants. Ever...
A payments agent approves a batch it should have held. A reconciliation model books an exception
Some of the most damaging outages are the ones your monitoring never flags: a slice...
AI monitoring tracks latency, tokens, cost, errors and output quality of AI systems in production. See what to track per system and how to set alert thresholds.
Researchers at Sichuan University have developed a collaborative framework that combines multi-window concept drift detection with an evolving fuzzy system to precisely locate dist...
AI agent monitoring explained: tool calls, side effects, handoffs, cost and loops to watch, how to alert on drift, which tools help, and what monitoring misses.
Over the past year, we watched a new class of alert appear in enterprise security operations centers and grow faster than anything else in the stream: alerts that were triggered by...
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My AI detectors flagged many genuine reviews, and filtering them made the sentiment model less accurate. The post AI Slop Is Already in Your Training Dataset. I Tested Three Ways t...
Through the partnership, Anomaly will provide Inova with additional data and analytics to evaluate payer behavior and payment outcomes.
AI's infamous tendency to occasionally generate false information, also known as "hallucinations," remains untamed by even the world's largest accounting firms.
I spent the first six months of a project convinced we had a model quality problem. Our anomaly detection system for manufacturing telemetry was missing obvious defects; things a h...
Every mature engineering team has a Security Incident Response Plan, refined over years of postmortems. But when the incident involves AI — a toxic hallucination with real conseque...
Your AI Model Is Drifting Right Now. Would You Know? A validated model went quietly wrong. Here’s the ladder that catches it. Quality Dig...
As artificial intelligence changes how companies compete, accountants may increasingly confront an unusual valuation problem
When someone uploads an image to your application, it might look perfectly fine at first glance. It might open correctly, pass file validation, and avoid triggering any obvious red...
Why You Should Double-Check AI Output (Before It Ships) When AI output goes unchecked, the costs compound. A single hallucinated fact takes a few minutes to produce and hours, da...
A controlled test of Gemini, DeepSeek, ChatGPT, and Claude on leakage, reporting delays, promotion effects, and structural breaks. The post I Hid Four Traps in a Forecasting Task....
Why autonomous agents expose a new explainability problem in fraud detection The post What SHAP Can't Explain About Agentic AI Fraud appeared first on Towards Data Science.
AI fraud detection now hinges on data quality, not model sophistication, because fragmented data drives false positives that erode client trust.
This Applied AI edition looks at what organizations actually did with AI over the past two weeks, drawn from our Use-Case Library and from SEC filings. Three things stand out: AI n...
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