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Colour me old-fashioned, but i am really sceptical about a zero-shot general-purpose LLM-based anomaly detector being able to outperform a trivial, not-obviousl
by glutamate 2y ago
Colour me old-fashioned, but i am really sceptical about a zero-shot general-purpose LLM-based anomaly detector being able to outperform a trivial, not-obviously-wrong ML/statistical model calibrated on a small subset of the data that makes training extremely fast, in entirely new domains. And in anomaly detection, false negatives (and even false positives) can be very expensive.
The most promising role for LLMs in timeseries prediction is in extracting covariates from unstructured data, in the wind example, weather reports and geographically proximal social media posts.
- thomashop 2y agoYou are skeptical about something that is explained quite thoroughly in the article. Did you read the article? Edit: I meant they never claim to outperform SOTA domain-specific approaches. So, I don't know whose claim you are refuting.
- glutamate 2y ago> While LLMs could not beat state-of-the-art deep learning models at anomaly detection, they did perform as well as some other AI approaches. I think one should also be sceptical about the current hype train