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I think this is a legit read about the utility.

> why should predictors be so coddled by their observers?

I suppose that in the RIM example the predictor correctly identified causes and concerns. The timelines are off. But highlighting the causes are interesting to me, as a datapoint.

If someone says "hey there's a problem here", you can somewhat independently look at the problem and validate its seriousness on your end.

Some people in this thread are like "well the value is in the prediction", but from my perspective I'm thinking "the value is in the causal analysis". Because if you merely think the timelines are wrong you can easily just change numbers around.

Obviously Zitron is not "always right", and isn't getting all causal analysis right IMO. I do think he's bringing up things though.

 help



If the causal analysis is the real value, then it could be presented without a prediction, or at least without a specific prediction.

In 2024, if Ed Zitron presented all his analysis of AI companies without the specific “model capabilities have peaked this year” style statements that Dan Luu scrutinized, that would be more honest and provide the value you are looking for.

Similarly for the RIM example nobody would have to claim that RIM would fail in a particular year, or that “RIM is cooked”, they could present their data about the present without any projection.




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